CN103824446A - Sub-area multi-intersection group decision-making control method - Google Patents

Abstract

The invention discloses a sub-area multi-intersection group decision-making control method. The method comprises: based on a traffic flow continuity idea, bringing forward an adjacent intersection coordination rate, and giving a calculation formula of the adjacent intersection coordination rate and a sub-area multi-intersection total coordination rate; through research into a sub-area multi-intersection group intelligent coordination control strategy, designing a sub-area multi-intersection group decision-making control optimization architecture, and bringing forward an adjacent intersection decision-making control method and model; and by taking the size of the sub-area intersection total coordination rate as a signal timing basis, establishing a sub-area multi-intersection group decision-making control model, constructing a common signal period, a green ratio and a phase difference colony optimization function, designing a signal timing optimization process, and bringing forward an optimization algorithm based on genetic algorithms-simulated annealing such that sub-area multi-intersection group coordination control is realized. The method provided by the invention is applied to sub-area multi-intersection signal timing optimization under various traffic states of a medium-sized city, can improve the area coordination control capability, effectively reduces parking frequency and driving delay, and alleviates traffic congestion.

Description

One seed zone multi-intersection group decision control method

Technical field

The present invention relates to regional traffic and coordinate control field, refer in particular to a seed zone multi-intersection group decision control method.

Background technology

Along with the growth of the modern urban road volume of traffic, the enhancing of road network density, the correlativity between crossing is day by day obvious.In a region or whole city, the adjustment of crossing traffic signals tends to have influence on the operation conditions of adjacent several crossing traffic flows, and As time goes on blocking up of a crossing may progressively feed through to all crossings of the several crossings of periphery and even region.Therefore, city becomes more and more higher to the requirement of traffic signals control, and using certain region, even whole city is also more and more subject to researchist's attention as the regional signal coordination control theory method research of research object.How guaranteeing to coordinate under the substantially unimpeded prerequisite of each crossing traffic between crossing Traffic Signal Timing scheme to increase the key that the traffic capacity of whole road network is regional traffic signal controlling.

In a regional extent in whole city or city, traffic is coordinated to control, no matter from point of theory, or practical term, be all extremely complicated, a difficult large system control problem.The control of traffic signals regional coordination is an emphasis in traffic signals control, is also a difficult point.Domestic and international many scholars are from point of theory, and application system, large system and the theory of optimal control, study this typical large system of urban transportation, obtained certain achievement.But these regional coordination control system are only applicable to, under non-hustle traffic situation, limit to a certain extent the actual motion effect of regional coordination control system.

Summary of the invention

The object of the invention is to overcome the deficiencies in the prior art, a kind of subarea multi-intersection group decision control method being applicable under various traffic behaviors is provided, make can not stop continuously and roll the vehicle flowrate increase of crossing away from the unit interval, the traffic circulation benefit of intersection group improves.

For achieving the above object, technical scheme provided by the present invention is: a seed zone multi-intersection group decision control method, comprises the following steps:

1) traffic parameter---the crossing coordination rate based on a quantitative description crossing harmony power of wagon flow continuity theory proposition, and provide the computing formula of crossing coordination rate, comprise the computing formula that Adjacent Intersections coordination rate and subarea multi-intersection chief coordinator lead;

2) according to the computing formula of Adjacent Intersections coordination rate, set up the Adjacent Intersections Decision Control Model based on Adjacent Intersections coordination rate, structure Adjacent Intersections wagon flow input/output relation formula, coordinates to control for intersection group and prepares;

3) set up subarea multi-intersection group decision control model, determine common signal cycle and each crossing Split Optimization method, then set up with subarea multi-intersection chief coordinator and lead the phase differential population effect function model that is optimization aim to the maximum;

4) according to common signal cycle and phase differential population effect function model, in conjunction with Adjacent Intersections wagon flow input/output relation formula, adopt Global Genetic Simulated Annealing Algorithm to solve subarea multi-intersection group decision control model, obtain optimizing decision variable, generate best intersection signal timing scheme, feasible region signal timing dial optimization and coordination control.

Described step 1) comprises the following steps:

1.1) Adjacent Intersections coordination rate refers between the green zone of crossing, upstream in the situation that postponing certain hour, is mapped to downstream intersection, with the degree that overlaps between downstream intersection respective phase green zone.It is a traffic parameter that harmony between Adjacent Intersections is carried out to quantitative description, the objective impact on Adjacent Intersections harmony by the road section traffic volume operation conditions between concentrated expression Adjacent Intersections and signal controlling demand difference; For thing craspedodrome phase place, thing craspedodrome phase coordination rate is defined as the two-way coordination rate between eastern import and western import, among eastern import coordination rate and western import coordination rate, get little, i.e. k signal period crossing I _i,jthe coordination rate of thing craspedodrome phase place

for:

${\mathrm{\ξ}}_{i,j}^{1k}=\min \{\frac{H_{i+1,j\→i,j}^k\∩\left({\mathrm{\Σ}}_{k=0}^{\∞}{H}_{i,j}^{1k}\right)}{\left|H_{i+1,j}^k\right|},\frac{H_{i-1,j\→i,j}^k\∩\left({\mathrm{\Σ}}_{k=0}^{\∞}{H}_{i,j}^{1k}\right)}{\left|H_{i-1,j}^k\right|}\}$

In formula, | ﹒ ﹒ ﹒ | be burst length, be k cycle crossing I _i,jbetween the green zone of thing craspedodrome phase place,

for crossing I _{i+1, j}output wagon flow Interval Maps is to downstream intersection I _i,jthe interval at place,

be k cycle thing craspedodrome phase place crossing I _i,jwith I _{i+1, j}coordination;

1.2) Adjacent Intersections coordination rate is four of crossings phase coordination rate sum, i.e. k cycle Adjacent Intersections coordination rate

for:

${\mathrm{\ξ}}_{i,j}^k={\mathrm{\Σ}}_{l=1}^4{\mathrm{\ξ}}_{i,j}^{1k};$

1.3) be tolerance Adjacent Intersections coordination rate, introduce the concept of non-Coordination below, crossing, upstream I _{i+1, j}between green zone, be mapped to downstream intersection I _i,j, and and downstream intersection respective phase green zone between not intersection, be called non-Coordination

k signal period crossing I _i,jbetween the green zone in craspedodrome direction with Adjacent Intersections I _{i+1, j}the non-Coordination of wagon flow output interval

be expressed as follows:

1.4), based on the above-mentioned analysis to Adjacent Intersections coordination rate, lead and can be calculated by following formula for the subarea multi-intersection chief coordinator of M × N crossing of k signal period subarea multi-intersection group:

${\mathrm{\ξ}}^k=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N}{\mathrm{\Σ}}}{\mathrm{\Σ}}_{l=1}^4{\mathrm{\ξ}}_{i,j}^{\mathrm{lk}};$

Described step 2) comprise the following steps:

2.1) thing craspedodrome phase coordination rate is calculated

For crossing I _i,jthing craspedodrome phase place, main considering intersection I _{i-1, j}and I _{i+1, j}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between thing craspedodrome green zone, place, k signal period crossing I _i,jthing craspedodrome between green zone is:

$H_{i,j}^{1k}=[T_{i,j}+(k-1)C_{i,j},T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1]$

Crossing I _{i-1, j}output wagon flow interval comprise that thing keeps straight on and the interval of two phase places of north and south left/right rotation:

$H_{i-1,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}{T}_{i-1,j}+(k-1)C_{i-1,j}{+g}_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1{+g}_{i-1,j}^2]$

Crossing I so _{i-1, j}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$H_{i-1,j\&RightArrow;i,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^3-Q_{i,j}^{8k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^3-Q_{i,j}^{8k}}{v}]$

Wherein, establish C _i,jwith C _{i-1, j}lowest common multiple be

phase differential will be with so do periodically to change; Order

crossing I _{i-1, j}α _{i-1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing craspedodrome green zone at place is used

represent, its computing formula is as follows:

$M_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^1}{H}_{i,j}^{1k}\right)$

Now crossing I _i,jin western importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}$

In like manner, crossing I _{i+1, j}output wagon flow interval comprise that thing keeps straight on and the interval of two phase places of north and south left/right rotation:

$H_{i+1,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2]$

Crossing I so _{i+1, j}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$H_{i+1,j\&RightArrow;i,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j}+\frac{l_{i,j}^1-Q_{i,j}^{2k}}{v},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^1-Q_{i,j}^{2k}}{v}]$

Wherein, establish C _i,jwith C _{i+1, j}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i+1, j}α _{i+1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing craspedodrome green zone at place is used

represent, its computing formula is as follows:

$M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i+1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^2}{H}_{i,j}^{1k}\right)$

Now crossing I _i,jin eastern importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}|H_{i+1,j}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of thing craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11},{\mathrm{\&xi;}}_{i,j}^{12})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

2.2) thing left/right rotation phase coordination rate is calculated

For crossing I _i,jthing left/right rotation phase place, main considering intersection I _{i-1, j}and I _{i+1, j}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between thing left/right rotation green zone, place; K signal period crossing I _i,jthing left/right rotation between green zone is:

$H_{i,j}^{4k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i,j}^3]$

According to formula between thing craspedodrome and two phase regions of north and south left/right rotation, crossing I _{i-1, j}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$H_{i-1,j\&RightArrow;i,j}^{\&prime;k}=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^3-Q_{i,j}^{9k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^3-Q_{i,j}^{9k}}{v}]$

By upper known

crossing I _{i-1, j}α _{i-1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing left-hand rotation green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{41}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^{\&prime;k}\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^1}{H}_{i,j}^{4k}\right)$

Now crossing I _i,jin western importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{41}=\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}$

In like manner, according to formula between thing craspedodrome and two phase regions of north and south left/right rotation, crossing I _{i+1, j}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

${H\&prime;}_{i+1,j\&RightArrow;i,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j}+\frac{l_{i,j}^1-Q_{i,j}^{1k}}{v},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^1-Q_{i,j}^{1k}}{v}]$

By upper known

crossing I _{i+1, j}α _{i+1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing left-hand rotation green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{42}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i+1,j}}{H}_{i+1,j\&RightArrow;i,j}^{\&prime;k}\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^2}{H}_{i,j}^{4k}\right)$

Now crossing I _i,jin eastern importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{42}=\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}|H_{i+1,j}^k|}=\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of thing left turn phase is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="4"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^4=\min ({\mathrm{\&xi;}}_{i,j}^{41},{\mathrm{\&xi;}}_{i,j}^{42})=\min (\frac{{|M}_{i,j}^{41}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

2.3) north and south craspedodrome phase coordination rate is calculated

For crossing I _i,jnorth and south craspedodrome phase place, main considering intersection I _{i, j-1}and I _{i, j+1}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between craspedodrome green zone, north and south, place; K signal period crossing I _i,jnorth and south between craspedodrome green zone is:

$H_{i,j}^{3k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i,j}^3]$

Crossing I _{i, j-1}output wagon flow interval comprise the keep straight on interval of two phase places of thing left/right rotation and north and south:

$H_{i,j-1}^k=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1},T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3]$

Crossing I so _{i, j-1}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$\begin{array}{c}{H}_{i,j-1\&RightArrow;i,j}^k=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1}+\frac{l_{i,j}^2-Q_{i,j}^{5k}}{v},\\ T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3+\frac{l_{i,j}^2-Q_{i,j}^{5k}}{v}]\end{array}$

Wherein, establish C _i,jwith C _{i, j-1}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i, j-1}α _{i, j-1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the craspedodrome green zone, north and south at place is used represent, its computing formula is as follows:

$M_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j-1}}{H}_{i,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^3}{H}_{i,j}^{3k}\right)$

Now crossing I _i,jcoordination rate in southing mouth direction is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

In like manner, crossing I _{i, j+1}output wagon flow interval comprise the keep straight on interval of two phase places of thing left/right rotation and north and south:

$H_{i,j+1}^k=[T_{i,j+1}+g_{i,j+1}^1+(k-1)C_{i,j+1}{T}_{i,j+1}+(k-1)C_{i,j+1}{+g}_{i,j+1}^1{+g}_{i,j+1}^2+g_{i,j+1}^3]$

Crossing I so _{i, j+1}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$\begin{array}{c}{H}_{i,j+1\&RightArrow;i,j}^k=[T_{i,j+1}+g_{i,j+1}^1+(k-1)C_{i,j+1}+\frac{l_{i,j}^4-Q_{i,j}^{14k}}{v},\\ T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3+\frac{l_{i,j}^4-Q_{i,j}^{11k}}{v}]\end{array}$

Wherein, establish C _i,jwith C _{i, j+1}lowest common multiple be phase differential will be with so

do periodically to change; Order

crossing I _{i, j+1}α _{i, j+1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the craspedodrome green zone, north and south at place is used

represent, its computing formula is as follows:

$M_{i,j}^{32}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j+1}}{H}_{i,j+1\&RightArrow;i,j}^k\right)\&cap;\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^4}{H}_{i,j}^{3k}\right)$

Now crossing I _i,jcoordination rate in northing mouth direction is:

${\mathrm{\&xi;}}_{i,j}=\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^1+g_{i,j+1}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of north and south craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31},{\mathrm{\&xi;}}_{i,j}^{32})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

2.4) north and south left/right rotation phase coordination rate is calculated

For crossing I _i,jnorth and south left/right rotation phase place, main considering intersection I _{i, j-1}and I _{i, j+1}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between left/right rotation green zone, north and south, place; K signal period crossing I _i,jnorth and south between left-hand rotation green zone is:

$H_{i,j}^{2k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1{,T}_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,j}^2]$

According to formula between thing left/right rotation and north and south craspedodrome phase region, crossing I _{i, j-1}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$\begin{array}{c}{H}_{i,j-1\&RightArrow;i,j}^{\&prime;k}=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1}+\frac{l_{i,j}^2-Q_{i,j}^{6k}}{v},\\ T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3+\frac{l_{i,j}^2-Q_{i,j}^{6k}}{v}]\end{array}$

By upper known

crossing I _{i, j-1}α _{i, j-1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the left-hand rotation green zone, north and south at place is used

represent, its computing formula is as follows:

Now crossing I _i,jcoordination rate in southing mouth direction is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

In like manner, according to formula between thing left/right rotation and two phase regions of north and south craspedodrome, crossing I _{i, j+1}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$\begin{array}{c}{H}_{i,j+1\&RightArrow;i,j}^{\&prime;k}=[T_{i,j+1}+g_{i,j+1}^1+(k-1)C_{i,j+1}+\frac{l_{i,j}^4-Q_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}}{v},\\ T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3+\frac{l_{i,j}^4-Q_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}}{v}]\end{array}$

By upper known

crossing I _{i, j+1}α _{i, j+1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the left-hand rotation green zone, north and south at place is used

represent, its computing formula is as follows:

Now crossing I _i,jcoordination rate in northing mouth direction is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of north and south craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21},{\mathrm{\&xi;}}_{i,j}^{22})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

2.5)

calculate

East import

with

value be by

determine, according to

the different situations of value,

with

value have following six kinds of situations,

for upstream outgoing vehicles is to the time in downstream, discuss respectively below in various situations

with

value:

1. work as

and time, can try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

In like manner, western import with

be by

determine, according to

the different situations of value, with value there are following six kinds of situations, discuss respectively below in various situations

with value:

1. work as

and

time, try to achieve

2. work as

and time, try to achieve

3. work as

and

time, try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

Southing mouth

with

be by

determine, according to

the different situations of value, with

value there are following six kinds of situations, discuss respectively below in various situations

with

value:

1. work as

time, and time, try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

In like manner, northing mouth

with

by

determine, according to

the different situations of value,

with

value there are following six kinds of situations, discuss respectively below in various situations

with

value:

1. work as

time, and

try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, can try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

2.6) set up Adjacent Intersections Decision Control Model, comprise the following steps:

2.6.1) establish

while being k end cycle, pass through the vehicle number of upstream and downstream, l track detecting device along a direction, be the vehicle number being detained between this respective direction upstream and downstream, track coil when the k-1 cycle, green light signals finished, the vehicle number between this track upstream and downstream detecting device is when k end cycle:

$Q_{i,j}^{\mathrm{lk}}=q_{i,j}^l-z_{i,j}^l+Q_{i,j}^{l(k-1)}$

$Q_{i,j}^{\lim }=\frac{L}{h}$

In formula: L is the distance between upstream and downstream detecting device, h is space headway, for the maximum vehicle number that can hold between the detecting device of upstream and downstream, track.

2.6.2) take vehicle average latency minimum as optimization aim, maximize and fall into the interval vehicle number that overlaps, consider the each entrance driveway magnitude of traffic flow in crossing simultaneously, the Adjacent Intersections Decision Control Model of foundation based on coordination rate is as follows:

$\begin{array}{c}\max f\left(N_{i,j}\right)=\max (q_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,q_{i,j}^8){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+\max (q_{i,\mathrm{<figure-callout\; id="6"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^6,q_{i,j}^{12}){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2\\ +\max (q_{i,\mathrm{<figure-callout\; id="5"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^5,q_{i,j}^{11}){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3+\max (q_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3,q_{i,j}^9){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="4"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^4\end{array}$

In formula:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11},{\mathrm{\&xi;}}_{i,j}^{12})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21},{\mathrm{\&xi;}}_{i,j}^{22})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i-1,j}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i+1,j}^3)});$

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31},{\mathrm{\&xi;}}_{i,j}^{32})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="4"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^4=\min ({\mathrm{\&xi;}}_{i,j}^{41},{\mathrm{\&xi;}}_{i,j}^{42})=\min (\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}^1(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

be the maximal value of eastern import and western import straight-going traffic flow in the first phase place thing craspedodrome phase place,

for the maximal value of southing mouth in the left/right rotation phase place of north and south and northing mouth left turn traffic amount,

for the maximal value of southing mouth in north and south craspedodrome phase place and northing mouth straightgoing vehicle flow,

for the maximal value of eastern import in thing left/right rotation phase place and western import left turn traffic amount;

2.7) structure Adjacent Intersections wagon flow input/output relation formula, comprises the following steps:

Suppose that road network structure is M × N, when known boundaries is sailed the cycle arrival rate of control area into time, utilize the steering flow distribution ratio of the each import in each crossing, can be for the M in control area × (N-1)+N bar unknown flow rate crossing inlet road, set up M × (N-1)+N discharge relation equation, be shown below, the relation between cycle vehicle arrival rate and crossing, upstream output rating to all unknown flow rate crossing inlets road is calculated and is solved:

$\begin{array}{c}{q}_{\mathrm{1,2}}^7=u_{\mathrm{1,2}}^7\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^7\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^8=u_{\mathrm{1,2}}^8\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^8\&CenterDot;(q_{\mathrm{1,1}}^4+u_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^9=u_{\mathrm{1,2}}^9\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^9\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ q_{M,N}^7=u_{M,N}^7\&CenterDot;z_{M,N-1}^1=u_{M,N}^7\&CenterDot;\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^8=u_{M,N}^8\&CenterDot;Z_{M,N-1}^1=u_{M,N}^8(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^9=u_{M,N}^9\&CenterDot;z_{M,N-1}^1=u_{m,n}^9\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\end{array}$

In formula:

for the steering flow distribution ratio in crossing inlet road;

Described step 3) comprises the following steps:

3.1) the common signal cycle is optimized

3.1.1) obtain the Webster optimal period duration of each crossing by single-point timing signal timing method, the formula of reduction of Webster optimum signal cycle duration is:

${\mathrm{<figure-callout\; id="0"\; label="C"\; filenames="HDA0000436798500000071.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">C</figure-callout>}}_0=\frac{1.5L+5}{1-Y}$

3.1.2) getting the wherein cycle duration of crucial crossing is reference signal cycle C _cri, therefore, reference signal cycle C _crifor

C _cri＝max(C ₁,...,C _n)

3.1.3) on the basis in reference signal cycle, design the span in common signal cycle, the permission variation range in common signal cycle is

[C _cri-M,C _cri+M]

Wherein, the value of M is actual traffic traffic state value between 10-15 as required, and the optimal value in common signal cycle is solved in conjunction with the optimization of phase differential by pattern search strategy;

3.2) Split Optimization

Take crossing, crucial vehicle mean delay minimal time is as target, and using the total saturation degree minimum in saturation degree approximately equal, crossing of each strand of key flow as split distribution principle, designed phase split should be directly proportional to its magnitude of traffic flow ratio:

$\frac{{\mathrm{\&lambda;}}_i}{{\mathrm{\&lambda;}}_j}=\frac{y_i}{y_j}$

In formula: i, j are signal phase sequence number, the magnitude of traffic flow ratio that y is key flow;

3.3) offset optimization

Choose the craspedodrome phase place starting point moment of a certain crossing as the corresponding time point of its phase differential setting, utilize relative phase difference, the signal phase sequence set-up mode of upstream and downstream crossing, intersection signal timing parameter between Adjacent Intersections, can extrapolate crossing I _i,jinitial relative phase difference O with each Adjacent Intersections _i,j, its computing formula is as follows:

$\begin{array}{c}{O}_{i+1,j}=T_{i+1,j}-T_{i,j}\\ O_{i-1,j}=T_{i-1,j}-T_{i,j}\\ O_{i,j+1}=T_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2-T_{i,j}-g_{i,j}^1-g_{i,j}^2\\ O_{i,j-1}=T_{i,j-1}+g_{i,g-1}^1+g_{i,j-1}^2-T_{i,j-1}-g_{i,j}^1-g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2;\end{array}$

3.4) according to crossing wagon flow input/output relation, be minimised as target with the vehicle average latency in road network, lead maximum with all crossing chief coordinators of road network and turn to target, set up subarea multi-intersection group decision control model:

$\begin{array}{c}\max F(C,T)=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}[\max (q_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,q_{i,j}^8){\mathrm{\&xi;}}_{i,j}^{1k}+\max (q_{i,\mathrm{<figure-callout\; id="6"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^6,q_{i,j}^{12}){\mathrm{\&xi;}}_{i,j}^{2k}\\ +\max (q_{i,\mathrm{<figure-callout\; id="5"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^5,q_{i,j}^{11}){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}+\max (q_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3,q_{i,j}^9){\mathrm{\&xi;}}_{i,j}^{4k}]\end{array}$

In formula:

${\mathrm{\&xi;}}_{i.j}^{1k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}i=1\\ {\mathrm{\&xi;}}_{i.j}^{11k}=\frac{\left|M_{i,j}^{11k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}i=M\\ \min ({\mathrm{\&xi;}}_{i.j}^{11k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k})=\min (\frac{\left|M_{i,j}^{11k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)})i\&NotEqual;1,M\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{2k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)}j=1\\ {\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)}j=N\\ \min ({\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k})=\min (\frac{\left|M_{i,\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)})j\&NotEqual;1,N\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{3k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.j}^{3k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="32k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{32k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)}j=1\\ {\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="31k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="31k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)}j=N\\ \min ({\mathrm{\&xi;}}_{i.j}^{3k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="32k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{32k})=\min (\frac{\left|M_{i,\mathrm{<figure-callout\; id="31k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="32k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{32k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)})j\&NotEqual;1,N\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{4k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}i=1\\ {\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}i=M\\ \min ({\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k})=\min (\frac{\left|M_{i,\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)})i\&NotEqual;1,M\end{array}\right.$

$\begin{array}{c}{q}_{\mathrm{1,2}}^7=u_{\mathrm{1,2}}^7\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^7\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^8=u_{\mathrm{1,2}}^8\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^8\&CenterDot;(q_{\mathrm{1,1}}^4+u_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^9=u_{\mathrm{1,2}}^9\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^9\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ q_{M,N}^7=u_{M,N}^7\&CenterDot;z_{M,N-1}^1=u_{M,N}^7\&CenterDot;\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^8=u_{M,N}^8\&CenterDot;Z_{M,N-1}^1=u_{M,N}^8(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^9=u_{M,N}^9\&CenterDot;z_{M,N-1}^1=u_{m,n}^9\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\end{array}$

C _cri-M＜C _i,j＜C _cri+M

Described step 4) comprises the following steps:

4.1) algorithm search strategy

The timing parameter of subarea multi-intersection group decision control model comprises common signal cycle, split, phase differential, wherein split can be according to the magnitude of traffic flow ratio in crossing inlet road, solve according to key flow saturation degree principle, common signal cycle and phase differential can, according to subarea multi-intersection group decision control model, utilize intelligent algorithm to be optimized and solve.Select Global Genetic Simulated Annealing Algorithm to common signal cycle C herein _i,jwith phase differential O _i,jbe optimized, lead maximum or vehicle average latency minimum to realize subarea multi-intersection chief coordinator.Therefore still adoption rate distributes coding/decoding method, chooses proportionality factors lambda _ifor decision variable, i=1 ...., n, λ ₀=0, n is crossing, subarea number, supposes that a crossing green light initial time in n crossing is given, λ so ₁-λ _n-1be used for calculating the green light initial time of all the other crossings, λ _nbe used for calculating common signal cycle duration.λ after every generation is evolved ₁-λ _nsubstitution following formula is asked its corresponding signal timing dial parameter respectively.Signal timing dial parameter substitution subarea multi-intersection group decision model formation after every generation optimization is tried to achieve to target function value and the fitness value that each decision variable is corresponding, genetic algorithm is carried out follow-on selection according to fitness value, until algorithm finishes while meeting end condition:

T _i,j＝(C _i,j-1)·λ _l,i＝1,...,M,j＝1,...,N,l＝1,...,n-1

C _i,j＝C _min+int[(C _max-C _min)·λ _n]

4.2) Algorithm for Solving step

The Global Genetic Simulated Annealing Algorithm that solves subarea multi-intersection group decision control model, comprises the following steps:

4.2.1) initialization: the crossover probability p that determines genetic algorithm _c, variation Probability p _m, individuality sum N and the maximum evolutionary generation M of every generation population, each individuality shows one group of signal time distributing conception by e fragment gene string list, determines the interior cycle index H of simulated annealing, the initial value T of temperature ₀, make T=T ₀;

4.2.2), from multiple individualities of random generation and calculate fitness value, the probability distribution determining by fitness function is therefrom selected good N the individual initial population P of composition (0);

4.2.3) the target function value F (C, T) of calculating population, according to target function value, calculates each individual fitness value

evaluate the fitness value of colony;

4.2.4) carry out genetic manipulation, comprise selection, crossover and mutation operator;

4.2.5) population P (gen) is carried out to simulated annealing operation, makes i=1:

If 1. i=N, goes to Step6; Otherwise make circulation round counting k=1;

2. utilize state to produce function and produce the new state of individual P (gen), and calculate its fitness;

3. accepting formula with Metropolis probability accepts new individual;

If 4. k=H, makes i=i+1, go to step 1.; Otherwise make k=k+1, go to step 2.;

4.2.6) output new population, moves back temperature, makes T=0.5T, goes to step 4.2.7);

4.2.7) judge whether genetic algebra reaches maximum, is to stop calculating output optimum solution, otherwise go to step 4.2.3).

Compared with prior art, tool has the following advantages and beneficial effect in the present invention:

1, the present invention introduces the concept of Adjacent Intersections harmony, provide the computing formula that subarea multi-intersection chief coordinator leads, set up the Adjacent Intersections Decision Control Model based on coordination rate, study on this basis the Intelligent Coordinating Control Strategy of subarea intersection group, analyze the wagon flow input/output relation between Adjacent Intersections, thereby set up subarea multi-intersection group decision control model, this model leads and is optimization aim to the maximum with subarea multi-intersection chief coordinator, therefore the signal timing dial optimization under various traffic behaviors is all suitable for, feasible region signal timing dial is optimized and signal coordinated control well, to regional coordination, control has great Research Significance and actual application value,

2, the invention enables in the unit interval and can not stop continuously and roll the vehicle flowrate increase of crossing away from, the traffic circulation benefit of intersection group improves.

Accompanying drawing explanation

Fig. 1 is the coordination spirogram of Adjacent Intersections thing craspedodrome phase place.

Fig. 2 is the coordination rate figure of the each entrance driveway in crossing.

Fig. 3 is the degree analyzing figure that overlaps between eastern import green zone.

Fig. 4 is the degree analyzing figure that overlaps between western import green zone.

Fig. 5 is the degree analyzing figure that overlaps between southing mouth green zone.

Fig. 6 is the degree analyzing figure that overlaps between northing mouth green zone.

Fig. 7 is that subarea multi-intersection group road network and phase sequence arrange figure.

Fig. 8 is Global Genetic Simulated Annealing Algorithm process flow diagram.

Fig. 9 is subarea 1 optimal objective value and decision variable performance tracing figure.

Figure 10 is the average stop frequency comparison diagram of vehicle before and after coordinate each crossing.

Figure 11 is vehicle mean delay comparison diagram before and after coordinate each crossing.

Figure 12 is vehicle average fuel consumption comparison diagram before and after coordinate each crossing.

Figure 13 is the average oxynitride discharge comparison diagram of vehicle before and after coordinate each crossing.

Figure 14 is the average VOC discharge of vehicle comparison diagram before and after coordinate each crossing.

Figure 15 is the average carbon monoxide emission comparison diagram of vehicle before and after coordinate each crossing.

Embodiment

Below in conjunction with specific embodiment, the invention will be further described.

Subarea multi-intersection group decision control method described in the present embodiment, its concrete condition is as follows:

1) traffic parameter---the crossing coordination rate based on a quantitative description crossing harmony power of wagon flow continuity theory proposition, and provide the computing formula of crossing coordination rate, comprise the computing formula that Adjacent Intersections coordination rate and subarea multi-intersection chief coordinator lead;

2) according to the computing formula of Adjacent Intersections coordination rate, set up the Adjacent Intersections Decision Control Model based on Adjacent Intersections coordination rate, structure Adjacent Intersections wagon flow input/output relation formula, coordinates to control for intersection group and prepares;

3) set up subarea multi-intersection group decision control model, determine common signal cycle and each crossing Split Optimization method, then set up with subarea multi-intersection chief coordinator and lead the phase differential population effect function model that is optimization aim to the maximum;

4) according to common signal cycle and phase differential population effect function model, in conjunction with Adjacent Intersections wagon flow input/output relation formula, adopt Global Genetic Simulated Annealing Algorithm to solve subarea multi-intersection group decision control model, obtain optimizing decision variable, generate best intersection signal timing scheme, feasible region signal timing dial optimization and coordination control.

Described step 1) comprises the following steps:

1.1) Adjacent Intersections coordination rate refers between the green zone of crossing, upstream in the situation that postponing certain hour, is mapped to downstream intersection, with the degree that overlaps between downstream intersection respective phase green zone; It is a traffic parameter that harmony between Adjacent Intersections is carried out to quantitative description, the objective impact on Adjacent Intersections harmony by the road section traffic volume operation conditions between concentrated expression Adjacent Intersections and signal controlling demand difference; As shown in Figure 1, thing craspedodrome phase coordination rate is defined as the two-way coordination rate between eastern import and western import, among eastern import coordination rate and western import coordination rate, get little, i.e. k signal period crossing I _i,jthe coordination rate of thing craspedodrome phase place

for:

${\mathrm{\&xi;}}_{i,j}^{1k}=\min \{\frac{H_{i+1,j\&RightArrow;i,j}^k\&cap;\left({\mathrm{\&Sigma;}}_{k=0}^{\&infin;}{H}_{i,j}^{1k}\right)}{\left|H_{i+1,j}^k\right|},\frac{H_{i-1,j\&RightArrow;i,j}^k\&cap;\left({\mathrm{\&Sigma;}}_{k=0}^{\&infin;}{H}_{i,j}^{1k}\right)}{\left|H_{i-1,j}^k\right|}\}$

In formula, | ﹒ ﹒ ﹒ | be burst length, be k cycle crossing I _i,jbetween the green zone of thing craspedodrome phase place,

for crossing I _{i+1, j}output wagon flow Interval Maps is to downstream intersection I _i,jthe interval at place,

be k cycle thing craspedodrome phase place crossing I _i,jwith I _{i+1, j}coordination;

1.2) Adjacent Intersections coordination rate is four of crossings phase coordination rate sum, i.e. k cycle Adjacent Intersections coordination rate

for:

${\mathrm{\&xi;}}_{i,j}^k={\mathrm{\&Sigma;}}_{l=1}^4{\mathrm{\&xi;}}_{i,j}^{1k};$

1.3) be tolerance Adjacent Intersections coordination rate, introduce the concept of non-Coordination below, as shown in Figure 1, non-Coordination

for crossing, upstream I _{i+1, j}between green zone, be mapped to downstream intersection I _i,j, and and downstream intersection respective phase green zone between not intersection; K signal period crossing I _i,jbetween the green zone in craspedodrome direction with Adjacent Intersections I _{i+1, j}the non-Coordination of wagon flow output interval be expressed as follows:

1.4), based on the above-mentioned analysis to Adjacent Intersections coordination rate, lead and can be calculated by following formula for the subarea multi-intersection chief coordinator of M × N crossing of k signal period subarea multi-intersection group:

${\mathrm{\&xi;}}^k=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{\mathrm{\&Sigma;}}_{l=1}^4{\mathrm{\&xi;}}_{i,j}^{\mathrm{lk}};$

As shown in Figure 2, wherein multilane adopts same numbering to the imported car road Unified number of crossing in the same way, and the vehicle of downstream intersection entrance driveway can roll away from from the craspedodrome of upstream thing and two phase place green times of north and south left/right rotation.Therefore during these two phase place green times of crossing, upstream, all can continue has vehicle to travel from upstream, and these vehicles are selected corresponding craspedodrome, left-hand rotation or right-hand rotation special lane according to its destination of travelling, and forms specific entrance driveway steering flow allocation proportion.

Described step 2) comprise the following steps:

2.1) thing craspedodrome phase coordination rate is calculated

For crossing I _i,jthing craspedodrome phase place, main considering intersection I _{i-1, j}and I _{i+1, j}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between thing craspedodrome green zone, place, k signal period crossing I _i,jthing craspedodrome between green zone is:

$H_{i,j}^{1k}=[T_{i,j}+(k-1)C_{i,j},T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1]$

Crossing I _{i-1, j}output wagon flow interval comprise that thing keeps straight on and the interval of two phase places of north and south left/right rotation:

$H_{i-1,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}{T}_{i-1,j}+(k-1)C_{i-1,j}{+g}_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1{+g}_{i-1,j}^2]$

Crossing I so _{i-1, j}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$H_{i-1,j\&RightArrow;i,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^3-Q_{i,j}^{8k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^3-Q_{i,j}^{8k}}{v}]$

Wherein, establish C _i,jwith C _{i-1, j}lowest common multiple be

phase differential will be with so do periodically to change; Order

crossing I _{i-1, j}α _{i-1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing craspedodrome green zone at place is used

represent, its computing formula is as follows:

$M_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^1}{H}_{i,j}^{1k}\right)$

Now crossing I _i,jin the western importer of phase place 1 coordination rate be upwards:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}$

In like manner, crossing I _{i+1, j}output wagon flow interval comprise that thing keeps straight on and the interval of two phase places of north and south left/right rotation:

$H_{i+1,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2]$

Crossing I so _{i+1, j}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$H_{i+1,j\&RightArrow;i,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j}+\frac{l_{i,j}^1-Q_{i,j}^{2k}}{v},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^1-Q_{i,j}^{2k}}{v}]$

Wherein, establish C _i,jwith C _{i+1, j}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i+1, j}α _{i+1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing craspedodrome green zone at place is used

represent, its computing formula is as follows:

$M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i+1,j}}{H}_{i+1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^2}{H}_{i,j}^{1k}\right)$

Now crossing I _i,jin the eastern importer of phase place 1 coordination rate be upwards:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}|H_{i+1,j}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of thing craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11},{\mathrm{\&xi;}}_{i,j}^{12})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

2.2) thing left/right rotation phase coordination rate is calculated

For crossing I _i,jthing left/right rotation phase place, main considering intersection I _{i-1, j}and I _{i+1, j}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between thing left/right rotation green zone, place; K signal period crossing I _i,jthing left/right rotation between green zone is:

$H_{i,j}^{4k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3,T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3,g_{i,j}^4]$

According to formula between thing craspedodrome and two phase regions of north and south left/right rotation, crossing I _{i-1, j}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$H_{i-1,j\&RightArrow;i,j}^{\&prime;k}=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^3-Q_{i,j}^{9k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^3-Q_{i,j}^{9k}}{v}]$

By upper known

crossing I _{i-1, j}α _{i-1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing left-hand rotation green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{41}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^{\&prime;k}\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^1}{H}_{i,j}^{4k}\right)$

Now crossing I _i,jin the western importer of phase place 4 coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{41}=\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}$

In like manner, according to formula between thing craspedodrome and two phase regions of north and south left/right rotation, crossing I _{i+1, j}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

${H\&prime;}_{i+1,j\&RightArrow;i,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j}+\frac{l_{i,j}^1-Q_{i,j}^{1k}}{v},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+\frac{l_{i,j}^1-Q_{i,j}^{1k}}{v}]$

By upper known

crossing I _{i+1, j}α _{i+1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing left-hand rotation green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{42}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i+1,j}}{H}_{i+1,j\&RightArrow;i,j}^{\&prime;k}\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^2}{H}_{i,j}^{4k}\right)$

Now crossing I _i,jin the eastern importer of phase place 4 coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{42}=\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}|H_{i+1,j}^k|}=\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of thing left turn phase is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="4"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^4=\min ({\mathrm{\&xi;}}_{i,j}^{41},{\mathrm{\&xi;}}_{i,j}^{42})=\min (\frac{{|M}_{i,j}^{41}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

2.3) north and south craspedodrome phase coordination rate is calculated

For crossing I _i,jnorth and south craspedodrome phase place, main considering intersection I _{i, j-1}and I _{i, j+1}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between craspedodrome green zone, north and south, place; K signal period crossing I _i,jnorth and south between craspedodrome green zone is:

$H_{i,j}^{3k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i,j}^3]$

Crossing I _{i, j-1}output wagon flow interval comprise the keep straight on interval of two phase places of thing left/right rotation and north and south:

$H_{i,j-1}^k=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1},T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3]$

Crossing I so _{i, j-1}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$\begin{array}{c}{H}_{i,j-1\&RightArrow;i,j}^k=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1}+\frac{l_{i,j}^2-Q_{i,j}^{5k}}{v},\\ T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3+\frac{l_{i,j}^2-Q_{i,j}^{5k}}{v}]\end{array}$

Wherein, establish C _i,jwith C _{i, j-1}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i, j-1}α _{i, j-1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the craspedodrome green zone, north and south at place is used represent, its computing formula is as follows:

$M_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j-1}}{H}_{i,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^3}{H}_{i,j}^{3k}\right)$

Now crossing I _i,jcoordination rate in the southing mouth direction of phase place 3 is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

In like manner, crossing I _{i, j+1}output wagon flow interval comprise the keep straight on interval of two phase places of thing left/right rotation and north and south:

$H_{i,j+1}^k=[T_{i,j+1}+g_{i,j+1}^1(k-1)C_{i,j+1}{T}_{i,j+1}+(k-1)C_{i,j+1}{+g}_{i,j+1}^1{+g}_{i,j+1}^2+g_{i,j+1}^3]$

Crossing I so _{i, j+1}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$\begin{array}{c}{H}_{i,j+1\&RightArrow;i,j}^k=[T_{i,j+1}+g_{i,j+1}^1+(k-1)C_{i,j+1}+\frac{l_{i,j}^4-Q_{i,j}^{11k}}{v},\\ T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3+\frac{l_{i,j}^4-Q_{i,j}^{11k}}{v}]\end{array}$

Wherein, establish C _i,jwith C _{i, j+1}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i, j+1}α _{i, j+1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the craspedodrome green zone, north and south at place is used

represent, its computing formula is as follows:

$M_{i,j}^{32}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j+1}}{H}_{i,j+1\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^4}{H}_{i,j}^{3k}\right)$

Now crossing I _i,jcoordination rate in the northing mouth direction of phase place 3 is:

${\mathrm{\&xi;}}_{i,j}^{32}=\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of north and south craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31},{\mathrm{\&xi;}}_{i,j}^{32})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="23"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{23}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i,j+1}^2+g_{i,j+1}^3)});$

2.4) north and south left/right rotation phase coordination rate is calculated

For crossing I _i,jnorth and south left/right rotation phase place, main considering intersection I _{i, j-1}and I _{i, j+1}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between left/right rotation green zone, north and south, place; K signal period crossing I _i,jnorth and south between left-hand rotation green zone is:

$H_{i,j}^{2k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1{,T}_{i,j}+(k-1)C_{i,j}+g_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i,j}^2]$

According to formula between thing left/right rotation and north and south craspedodrome phase region, crossing I _{i, j-1}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$\begin{array}{c}{H}_{i,j-1\&RightArrow;i,j}^{\&prime;k}=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1}+\frac{l_{i,j}^2-Q_{i,j}^{6k}}{v},\\ T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3+\frac{l_{i,j}^2-Q_{i,j}^6}{v}]\end{array}$

By upper known

crossing I _{i, j-1}α _{i, j-1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the left-hand rotation green zone, north and south at place is used

represent, its computing formula is as follows:

Now crossing I _i,jcoordination rate in the southing mouth direction of phase place 2 is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

In like manner, according to formula between thing left/right rotation and two phase regions of north and south craspedodrome, crossing I _{i, j+1}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$\begin{array}{c}{H}_{i,j+1\&RightArrow;i,j}^{\&prime;k}=[T_{i,j+1}+g_{i,j-1}^1+(k-1)C_{i,j+1}+\frac{l_{i,j}^4-Q_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}}{v},\\ T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3+\frac{l_{i,j}^4-Q_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}}{v}]\end{array}$

By upper known

crossing I _{i, j+1}α _{i, j+1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the left-hand rotation green zone, north and south at place is used

represent, its computing formula is as follows:

Now crossing I _i,jcoordination rate in the northing mouth direction of phase place 2 is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of north and south craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21},{\mathrm{\&xi;}}_{i,j}^{22})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i,j-1}^2+g_{i,j-1}^3)});$

2.5)

calculate

East import

with value be by

determine, according to

the different situations of value,

with

value have following six kinds of situations, as shown in Figure 3, in figure, the longitudinal axis represents the time, transverse axis represents different signal spacings,

for upstream outgoing vehicles is to the time in downstream, discuss respectively below in various situations

with value:

1. work as

and

time, for the first situation in Fig. 3, can try to achieve

2. work as

and

time, for the second situation in Fig. 3, try to achieve

3. work as

and

time, for the third situation in Fig. 3, try to achieve

4. work as

time, for the 4th kind of situation in Fig. 3, try to achieve

5. work as

time, for the 5th kind of situation in Fig. 3, try to achieve

6. work as

time, for the 6th kind of situation in Fig. 3, try to achieve

In like manner, western import with

be by

determine, according to

the different situations of value,

with value there are following six kinds of situations, as shown in Figure 4, discuss respectively below in various situations

with

value:

1. work as

and

time, for the first situation in Fig. 4, try to achieve

2. work as

and

time, for the second situation in Fig. 4, try to achieve

3. work as

and

time, for the third situation in Fig. 4, try to achieve

4. work as

time, for the 4th kind of situation in Fig. 4, try to achieve

5. work as

time, for the 5th kind of situation in Fig. 4, try to achieve

6. work as

time, for the 6th kind of situation in Fig. 4, try to achieve

Southing mouth

with be by

determine, according to

the different situations of value,

with value there are following six kinds of situations, as shown in Figure 5, discuss respectively below in various situations

with

value:

1. work as

time, and

time, for the first situation in Fig. 5, try to achieve

2. work as

and time, for the second situation in Fig. 5, try to achieve

3. work as and

time, for the third situation in Fig. 5, try to achieve

4. work as

time, for the 4th kind of situation in Fig. 5, try to achieve

5. work as

time, for the 5th kind of situation in Fig. 5, try to achieve

6. work as

time, for the 6th kind of situation in Fig. 5, try to achieve

In like manner, northing mouth

with

by determine, according to

the different situations of value,

with

value there are following six kinds of situations, as shown in Figure 6, discuss respectively below in various situations

with value:

1. work as

time, and

for the first situation in Fig. 6, try to achieve

2. work as

and

time, for the second situation in Fig. 6, try to achieve

3. work as

and

time, for the third situation in Fig. 6, can try to achieve

4. work as

time, for the 4th kind of situation in Fig. 6, try to achieve

5. work as

time, for the 5th kind of situation in Fig. 6, try to achieve

6. work as time, for the 6th kind of situation in Fig. 6, try to achieve

2.6) set up Adjacent Intersections Decision Control Model, comprise the following steps:

2.6.1) establish

while being k end cycle, pass through the vehicle number of upstream and downstream, l track detecting device along a direction,

be the vehicle number being detained between this respective direction upstream and downstream, track coil when the k-1 cycle, green light signals finished, the vehicle number between this track upstream and downstream detecting device is when k end cycle:

$Q_{i,j}^{\mathrm{lk}}=q_{i,j}^l-z_{i,j}^l+Q_{i,j}^{l(k-1)}$

$Q_{i,j}^{\lim }=\frac{L}{h}$

In formula: L is the distance between upstream and downstream detecting device, h is space headway,

for the maximum vehicle number that can hold between the detecting device of upstream and downstream, track.

2.6.2) take vehicle average latency minimum as optimization aim, maximize and fall into the interval vehicle number that overlaps, consider the each entrance driveway magnitude of traffic flow in crossing simultaneously, the Adjacent Intersections Decision Control Model of foundation based on coordination rate is as follows:

$\begin{array}{c}\max f\left(N_{i,j}\right)=\max (q_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,q_{i,j}^8){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+\max (q_{i,\mathrm{<figure-callout\; id="6"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^6,q_{i,j}^{12}){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2\\ +\max (q_{i,\mathrm{<figure-callout\; id="5"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^5,q_{i,j}^{11}){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3+\max (q_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3,q_{i,j}^9){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="4"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^4\end{array}$

In formula:

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11},{\mathrm{\&xi;}}_{i,j}^{12})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="12"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21},{\mathrm{\&xi;}}_{i,j}^{22})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="21"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i-1,j}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="22"\; label="j"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2+g_{i+1,j}^3)});$

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3=\min ({\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31},{\mathrm{\&xi;}}_{i,j}^{32})=\min (\frac{{|M}_{i,\mathrm{<figure-callout\; id="31"\; label="j"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

${\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="4"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^4=\min ({\mathrm{\&xi;}}_{i,j}^{41},{\mathrm{\&xi;}}_{i,j}^{42})=\min (\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}^1(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)});$

be the maximal value of eastern import and western import straight-going traffic flow in the first phase place thing craspedodrome phase place,

for the maximal value of southing mouth in the left/right rotation phase place of north and south and northing mouth left turn traffic amount,

for the maximal value of southing mouth in north and south craspedodrome phase place and northing mouth straightgoing vehicle flow,

for the maximal value of eastern import in thing left/right rotation phase place and western import left turn traffic amount;

2.7) structure Adjacent Intersections wagon flow input/output relation formula, comprises the following steps:

Suppose that road network structure is M × N, when known boundaries is sailed the cycle arrival rate of control area into

time, utilize the steering flow distribution ratio of the each import in each crossing, can be for the M in control area × (N-1)+N bar unknown flow rate crossing inlet road, set up M × (N-1)+N discharge relation equation, be shown below, the relation between cycle vehicle arrival rate and crossing, upstream output rating to all unknown flow rate crossing inlets road is calculated and is solved:

$\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="2"\; label="q"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,2}}^7=u_{\mathrm{1,2}}^7\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">z</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^7\&CenterDot;({\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^4+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^8+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^{12})\\ {\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="2"\; label="q"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,2}}^8=u_{\mathrm{1,2}}^8\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">z</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^8\&CenterDot;({\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^4+u_{\mathrm{1,1}}^8+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^{12})\\ {\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="2"\; label="q"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,2}}^9=u_{\mathrm{1,2}}^9\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">z</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^9\&CenterDot;({\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^4+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^8+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^{12})\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ q_{M,\mathrm{<figure-callout\; id="7"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^7=u_{M,\mathrm{<figure-callout\; id="7"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^7\&CenterDot;z_{M,N-1}^1=u_{M,\mathrm{<figure-callout\; id="7"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^7\&CenterDot;\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,\mathrm{<figure-callout\; id="8"\; label="N"\; filenames="HDA0000436798500000021.png,HDA0000436798500000041.png"\; state="\{\{state\}\}">N</figure-callout>}}^8=u_{M,\mathrm{<figure-callout\; id="8"\; label="N"\; filenames="HDA0000436798500000021.png,HDA0000436798500000041.png"\; state="\{\{state\}\}">N</figure-callout>}}^8\&CenterDot;Z_{M,N-1}^1=u_{M,N}^8(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,\mathrm{<figure-callout\; id="9"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^9=u_{M,\mathrm{<figure-callout\; id="9"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^9\&CenterDot;z_{M,N-1}^1=u_{m,\mathrm{<figure-callout\; id="9"\; label="n"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">n</figure-callout>}}^9\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\end{array}$

In formula:

for the steering flow distribution ratio in crossing inlet road;

Described step 3) comprises the following steps:

3.1) the common signal cycle is optimized

3.1.1) obtain the Webster optimal period duration of each crossing by single-point timing signal timing method, the formula of reduction of Webster optimum signal cycle duration is:

${\mathrm{<figure-callout\; id="0"\; label="C"\; filenames="HDA0000436798500000071.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">C</figure-callout>}}_0=\frac{1.5L+5}{1-Y};$

3.1.2) getting the wherein cycle duration of crucial crossing is reference signal cycle C _cri, therefore, reference signal cycle C _crifor

C _cri＝max(C ₁,...,C _n)

3.1.3) on the basis in reference signal cycle, design the span in common signal cycle, the permission variation range in common signal cycle is

[C _cri-M,C _cri+M]

Wherein, the value of M is actual traffic traffic state value between 10-15 as required, and the optimal value in common signal cycle is solved in conjunction with the optimization of phase differential by pattern search strategy;

3.2) Split Optimization

Take crossing, crucial vehicle mean delay minimal time is as target, and using the total saturation degree minimum in saturation degree approximately equal, crossing of each strand of key flow as split distribution principle, designed phase split should be directly proportional to its magnitude of traffic flow ratio:

$\frac{{\mathrm{\&lambda;}}_i}{{\mathrm{\&lambda;}}_j}=\frac{y_i}{y_j}$

In formula: i, j are signal phase sequence number, the magnitude of traffic flow ratio that y is key flow;

3.3) offset optimization

Choose the craspedodrome phase place starting point moment of a certain crossing as the corresponding time point of its phase differential setting, utilize relative phase difference, the signal phase sequence set-up mode of upstream and downstream crossing, intersection signal timing parameter between Adjacent Intersections, can extrapolate crossing I _i,jinitial relative phase difference O with each Adjacent Intersections _i,j, its computing formula is as follows:

$\begin{array}{c}{O}_{i+1,j}=T_{i+1,j}-T_{i,j}\\ O_{i-1,j}=T_{i-1,j}-T_{i,j}\\ O_{i,j+1}=T_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2-T_{i,j}-g_{i,j}^1-g_{i,j}^2\\ O_{i,j-1}=T_{i,j-1}+g_{i,g-1}^1+g_{i,j-1}^2-T_{i,j-1}-g_{i,j}^1-g_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2;\end{array}$

3.4) according to crossing wagon flow input/output relation, as shown in Figure 7, be minimised as target with the vehicle average latency in road network, lead maximum with all crossing chief coordinators of road network and turn to target, set up subarea multi-intersection group decision control model:

$\begin{array}{c}\max F(C,T)=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}[\max (q_{i,\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^2,q_{i,j}^8){\mathrm{\&xi;}}_{i,j}^{1k}+\max (q_{i,\mathrm{<figure-callout\; id="6"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^6,q_{i,j}^{12}){\mathrm{\&xi;}}_{i,j}^{2k}\\ +\max (q_{i,\mathrm{<figure-callout\; id="5"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^5,q_{i,j}^{11}){\mathrm{\&xi;}}_{i,\mathrm{<figure-callout\; id="11"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">j</figure-callout>}}^{11}+\max (q_{i,\mathrm{<figure-callout\; id="3"\; label="j"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">j</figure-callout>}}^3,q_{i,j}^9){\mathrm{\&xi;}}_{i,j}^{4k}]\end{array}$

In formula:

${\mathrm{\&xi;}}_{i.j}^{1k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}i=1\\ {\mathrm{\&xi;}}_{i.j}^{11k}=\frac{\left|M_{i,j}^{11k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}i=M\\ \min ({\mathrm{\&xi;}}_{i.j}^{11k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k})=\min (\frac{\left|M_{i,j}^{11k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)})i\&NotEqual;1,M\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{2k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)}j=1\\ {\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)}j=N\\ \min ({\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k})=\min (\frac{\left|M_{i,\mathrm{<figure-callout\; id="21k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{21k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="22k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{22k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)})j\&NotEqual;1,N\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{3k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.j}^{3k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="32k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{32k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)}j=1\\ {\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="31k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="31k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)}j=N\\ \min ({\mathrm{\&xi;}}_{i.j}^{3k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="32k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{32k})=\min (\frac{\left|M_{i,\mathrm{<figure-callout\; id="31k"\; label="j"\; filenames="HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^{31k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="32k"\; label="j"\; filenames="HDA0000436798500000051.png"\; state="\{\{state\}\}">j</figure-callout>}}^{32k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)})j\&NotEqual;1,N\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{4k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)}i=1\\ {\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k}=\frac{\left|M_{i,\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)}i=M\\ \min ({\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k},{\mathrm{\&xi;}}_{i.\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k})=\min (\frac{\left|M_{i,\mathrm{<figure-callout\; id="41k"\; label="j"\; filenames="HDA0000436798500000012.png,HDA0000436798500000031.png"\; state="\{\{state\}\}">j</figure-callout>}}^{41k}\right|}{(g_{i-1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i-1,j}^2)},\frac{\left|M_{i,\mathrm{<figure-callout\; id="42k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{42k}\right|}{(g_{i+1,\mathrm{<figure-callout\; id="1"\; label="j"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">j</figure-callout>}}^1+g_{i+1,j}^2)})i\&NotEqual;1,M\end{array}\right.$

$\begin{array}{c}{M}_{i,j}^{11k}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{\&infin;}{H}_{i,j}^{1k}\right)\\ M_{i,\mathrm{<figure-callout\; id="12k"\; label="j"\; filenames="HDA0000436798500000021.png"\; state="\{\{state\}\}">j</figure-callout>}}^{12k}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i+1,j}}{H}_{i+1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{\&infin;}{H}_{i,j}^{1k}\right)\end{array}$

$\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="2"\; label="q"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,2}}^7=u_{\mathrm{1,2}}^7\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">z</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^7\&CenterDot;({\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^4+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^8+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^{12})\\ {\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="2"\; label="q"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,2}}^8=u_{\mathrm{1,2}}^8\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">z</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^8\&CenterDot;({\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^4+u_{\mathrm{1,1}}^8+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^{12})\\ {\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="2"\; label="q"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,2}}^9=u_{\mathrm{1,2}}^9\&CenterDot;{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="z"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">z</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^9\&CenterDot;({\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^4+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^8+{\mathrm{<figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">\; <figure-callout\; id="1"\; label="q"\; filenames="HDA0000436798500000011.png,HDA0000436798500000012.png"\; state="\{\{state\}\}">q</figure-callout>\; </figure-callout>}}_{\mathrm{1,1}}^{12})\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ q_{M,\mathrm{<figure-callout\; id="7"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^7=u_{M,\mathrm{<figure-callout\; id="7"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^7\&CenterDot;z_{M,N-1}^1=u_{M,\mathrm{<figure-callout\; id="7"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^7\&CenterDot;\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,\mathrm{<figure-callout\; id="8"\; label="N"\; filenames="HDA0000436798500000021.png,HDA0000436798500000041.png"\; state="\{\{state\}\}">N</figure-callout>}}^8=u_{M,\mathrm{<figure-callout\; id="8"\; label="N"\; filenames="HDA0000436798500000021.png,HDA0000436798500000041.png"\; state="\{\{state\}\}">N</figure-callout>}}^8\&CenterDot;Z_{M,N-1}^1=u_{M,N}^8(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,\mathrm{<figure-callout\; id="9"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^9=u_{M,\mathrm{<figure-callout\; id="9"\; label="N"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">N</figure-callout>}}^9\&CenterDot;z_{M,N-1}^1=u_{m,\mathrm{<figure-callout\; id="9"\; label="n"\; filenames="HDA0000436798500000082.png,HDA0000436798500000083.png"\; state="\{\{state\}\}">n</figure-callout>}}^9\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\end{array}$

C _cri-M＜C _i,j＜C _cri+M

Subarea multi-intersection group decision control model is the phase differential of all Adjacent Intersections in subarea to be optimized to design simultaneously, and therefore subarea multi-intersection group decision optimization has three features on model construction:

1. in subarea multi-intersection group decision control, the signal period equal and opposite in direction of Nei Ge crossing, subarea, the coordination rate in each cycle is also identical, and the chief coordinator who only considers one-period leads and just can describe all sidedly vehicle and arrive and sail out of situation, therefore ${\mathrm{\&alpha;}}_{i-1,j}=C_{i,j}^{i-1,j}/C_{i-1,j}=1;$

2. in subarea, offset model need not be considered the harmony between other adjacent subareas, and the coordination rate of therefore controlling each entrance driveway on border, subarea is 0, in the time of i=1, in the time of i=M,

in the time of j=1,

in the time of j=N,

3. in Adjacent Intersections Decision Control Model, decision variable is signal period C, phase place green time g and thing craspedodrome phase place green light Startup time T; In multi-intersection phase differential colony Optimized model, decision variable is common signal cycle C, each crossing thing craspedodrome phase place green light Startup time T, and wherein phase place green time in crossing designs separately;

Described step 4) comprises the following steps:

4.1) algorithm search strategy

The timing parameter of subarea multi-intersection group decision control model comprises common signal cycle, split, phase differential, wherein split can be according to the magnitude of traffic flow ratio in crossing inlet road, solve according to key flow saturation degree principle, common signal cycle and phase differential can, according to subarea multi-intersection group decision control model, utilize intelligent algorithm to be optimized and solve.Select Global Genetic Simulated Annealing Algorithm to common signal cycle C herein _i,jwith phase differential O _i,jbe optimized, lead maximum or vehicle average latency minimum to realize subarea multi-intersection chief coordinator.Therefore still adoption rate distributes coding/decoding method, chooses proportionality factors lambda _ifor decision variable, i=1 ...., n, λ ₀=0, n is crossing, subarea number, supposes that a crossing green light initial time in n crossing is given, λ so ₁-λ _n-1be used for calculating the green light initial time of all the other crossings, λ _nbe used for calculating common signal cycle duration.λ after every generation is evolved ₁-λ _nsubstitution following formula is asked its corresponding signal timing dial parameter respectively.Signal timing dial parameter substitution subarea multi-intersection group decision model formation after every generation optimization is tried to achieve to target function value and the fitness value that each decision variable is corresponding, genetic algorithm is carried out follow-on selection according to fitness value, until algorithm finishes while meeting end condition:

T _i,j＝(C _i,j-1)?λ _l,i＝1,...,M,j＝1,...,N,l＝1,...,n-1

C _i,j＝C _min+int[(C _max-C _min)·λ _n]

4.2) Algorithm for Solving step

The Global Genetic Simulated Annealing Algorithm that solves subarea multi-intersection group decision control model, as shown in Figure 8, comprises the following steps:

4.2.1) initialization: the crossover probability p that determines genetic algorithm _c, variation Probability p _m, individuality sum N and the maximum evolutionary generation M of every generation population, each individuality shows one group of signal time distributing conception by e fragment gene string list, determines the interior cycle index H of simulated annealing, the initial value T of temperature ₀, make T=T ₀;

4.2.2), from multiple individualities of random generation and calculate fitness value, the probability distribution determining by fitness function is therefrom selected good N the individual initial population P of composition (0);

4.2.3) the target function value F (C, T) of calculating population, according to target function value, calculates each individual fitness value

evaluate the fitness value of colony;

4.2.4) carry out genetic manipulation, comprise selection, crossover and mutation operator;

4.2.5) population P (gen) is carried out to simulated annealing operation, makes i=1:

If 1. i=N, goes to Step6; Otherwise make circulation round counting k=1;

2. utilize state to produce function and produce the new state of individual P (gen), and calculate its fitness;

3. accepting formula with Metropolis probability accepts new individual;

If 4. k=H, makes i=i+1, go to step 1.; Otherwise make k=k+1, go to step 2.;

4.2.6) output new population, moves back temperature, makes T=0.5T, goes to step 4.2.7);

4.2.7) judge whether genetic algebra reaches maximum, is to stop calculating output optimum solution, otherwise go to step 4.2.3).

Below take West Road, Huan Shi main road, Nansha District, Guangzhou as example, West Road, Huan Shi main road, Nansha District, described Guangzhou is positioned at the southeast, Nansha District, it is now two-way six-lane, north taps into crossing, main road, port, reach crossing, Yi Hui road in the south, approximately 10 kilometers of total lengths, totally 21 crossings, are the strategic roads that connects north and south, Nansha District.

The traffic flow data at ordinary times of the each entrance driveway in crossing is as shown in table 1.The volume of traffic on West Road, Huan Shi main road is not very large, and saturation degree is moderate.Each crossing left-hand rotation flow is suitable with right-hand rotation flow, the eastern import craspedodrome flow in Shang Chu crossing, West Road, Huan Shi main road 3 and 21, the western import craspedodrome in crossing 16 flow, the eastern import craspedodrome in crossing 21 flow much more relatively outside, the flow of other crossings is not very outstanding.

West Road, table 1 Huan Shi main road each crossing inlet directional flow statistical form

1) Single Intersection signal timing dial

According to the data on flows shown in table 1, can determine key flow and the magnitude of traffic flow ratio thereof of each intersection signal phase place, utilize Webster optimum signal computation of Period formula

obtain the independent design signal period of each crossing.

2) control sub-area division

The each Adjacent Intersections spacing in known arterial highway, the spacing of crossing 20 and 21 is 880m, according to Adjacent Intersections spacing maximum-minimum principle, in the time that Adjacent Intersections spacing is greater than 800m, Adjacent Intersections puts two different subareas under, therefore crossing 21Wei subarea 1, crossing 1 to 20 is temporarily subarea 2.

Utilize intersection group clustering algorithm to carry out sub-area division to initial subarea 1, according to gathering degree formula, wherein get q=2, p=2.If threshold gamma=0.8, calculate, crossing 1 is all greater than threshold value to the gathering degree of any two crossings in crossing 6, the gathering degree size of crossing 2 and 7 is 0.788, the gathering degree of crossing 3 and 7 is 0.642, all be less than threshold value, therefore disconnect from crossing 7, crossing 1 will be divided into a subarea to crossing 6; Crossing 7 is all greater than threshold value to the gathering degree of any two crossings in crossing 16, the gathering degree of crossing 8 and 17 is 0.461, and the gathering degree of crossing 12 and 17 is 0.772, is all less than threshold value, therefore disconnect from crossing 17, crossing 7 will be divided into a subarea to crossing 16; In 17Dao crossing 20, crossing, the gathering degree of any two crossings is all greater than threshold value, therefore can be put under same subarea.

To sum up, road network will be divided into 4 subareas, and wherein crossing 1-6 is first subarea, and crossing 7-16 is second subarea, and crossing 17-20 is the 3rd subarea, and crossing 21 is the 4th subarea.

3) timing scheme optimization

(1) common signal cycle span

First ask for reference signal cycle C _cri, the reference signal cycle is the maximal value in all intersection signal cycles in subarea.Therefore the reference signal cycle in subarea 1

the reference signal cycle in subarea 2

the reference signal cycle in subarea 3

the reference signal cycle in subarea 4 is 105s.Suppose M=15s, the common signal cycle span in each subarea is as shown in table 2, and wherein subarea 4 only has a crossing 21, and therefore its single point signals timing cycle is its common signal cycle.

Span of each subarea common signal cycle of table 2

?	Subarea 1	Subarea 2	Subarea 3	Subarea 4
					The reference signal cycle (s)	106	115	97	105
Span (s)	[91,121]	[100,130]	[82,112]	105

(2) split

Reach minimum as split distribution principle, with λ using the total saturation degree in saturation degree approximately equal, crossing of each strand of key flow ₁: λ ₂: λ ₃: λ ₄=y ₁: y ₂: y ₃: y ₄proportionate relationship intersection signal phase place split is distributed.Intersection signal phase place split assigning process under best sub-area division scheme is as shown in table 3.

The each intersection signal phase place of table 3 split distributes

Crossing sequence number	1	2	3	4	5	6	7
								Phase place 1 magnitude of traffic flow ratio	0.242	0.231	0.284	0.267	0.269	0.250	0.267
Phase place 2 magnitude of traffic flow ratios	0.056	0.072	0.077	0.075	0.072	0.078	0.125
								Phase place 3 magnitude of traffic flow ratios	0.167	0.194	0.175	0.154	0.149	0.167	0.175
Phase place 4 magnitude of traffic flow ratios	0.083	0.111	0.064	0.117	0.091	0.083	0.061
								Phase place 1 split accounts for total split ratio	0.44	0.38	0.47	0.44	0.46	0.43	0.42
Phase place 2 splits account for total split ratio	0.10	0.12	0.13	0.12	0.12	0.13	0.20
								Phase place 3 splits account for total split ratio	0.30	0.32	0.29	0.25	0.26	0.29	0.28
Phase place 4 splits account for total split ratio	0.15	0.18	0.11	0.19	0.16	0.14	0.10
								Crossing sequence number	8	9	10	11	12	13	14
Phase place 1 magnitude of traffic flow ratio	0.228	0.211	0.246	0.281	0.222	0.247	0.250
								Phase place 2 magnitude of traffic flow ratios	0.100	0.082	0.069	0.059	0.111	0.067	0.069
Phase place 3 magnitude of traffic flow ratios	0.194	0.167	0.175	0.208	0.125	0.194	0.222
								Phase place 4 magnitude of traffic flow ratios	0.043	0.103	0.111	0.056	0.111	0.067	0.092
Phase place 1 split accounts for total split ratio lambda 1	0.40	0.38	0.41	0.46	0.39	0.43	0.39
								Phase place 2 splits account for total split ratio lambda 2	0.18	0.15	0.12	0.10	0.20	0.12	0.11
Phase place 3 splits account for total split ratio lambda 3	0.34	0.30	0.29	0.34	0.22	0.34	0.35
								Phase place 4 splits account for total split ratio lambda 4	0.08	0.18	0.18	0.09	0.20	0.12	0.14
Crossing sequence number	15	16	17	18	19	20	21
								Phase place 1 magnitude of traffic flow ratio	0.264	0.283	0.217	0.228	0.250	0.244	0.306
Phase place 2 magnitude of traffic flow ratios	0.111	0.097	0.064	0.054	0.056	0.069	0.056
								Phase place 3 magnitude of traffic flow ratios	0.153	0.183	0.156	0.175	0.208	0.153	0.139

Phase place 4 magnitude of traffic flow ratios	0.067	0.081	0.125	0.067	0.058	0.111	0.111
								Phase place 1 split accounts for total split ratio lambda 1	0.44	0.44	0.39	0.44	0.44	0.42	0.50
Phase place 2 splits account for total split ratio lambda 2	0.19	0.15	0.11	0.10	0.10	0.12	0.09
								Phase place 3 splits account for total split ratio lambda 3	0.26	0.28	0.28	0.33	0.36	0.26	0.23
Phase place 4 splits account for total split ratio lambda 4	0.11	0.13	0.22	0.13	0.10	0.19	0.18

On this basis, intersection signal phase time is calculated by following formula:

$t_i=(C-L)\&CenterDot;{\mathrm{\&lambda;}}_I+\frac{\mathrm{<figure-callout\; id="4"\; label="L"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">L</figure-callout>}}{4}$

(3) optimization of phase differential and signal period

First the optimization of phase differential and signal period is carried out in subarea 1.The optimization aim in subarea 1 is vehicle average latency minimum in subarea.According to crossing 1-6 input and output traffic flow data, suppose that each section vehicle average overall travel speed is 15m/s, the crossing total losses time is 24s, T _irepresent crossing i thing craspedodrome green light initial time, ξ _ijthe Adjacent Intersections coordination rate that represents j phase place of crossing i, wherein the coordination rate on the entrance driveway of border, subarea is all 0, the objective optimization function in subarea 1 is

$\begin{array}{c}\max F(C,T)=0.12{\mathrm{\&xi;}}_{11}+0.042{\mathrm{\&xi;}}_{14}+{0.115\mathrm{\&xi;}}_{21}+{0.056\mathrm{\&xi;}}_{24}+0.142{\mathrm{\&xi;}}_{31}+0.032{\mathrm{\&xi;}}_{34}\\ +0.133{\mathrm{\&xi;}}_{41}+{0.058\mathrm{\&xi;}}_{44}+0.135{\mathrm{\&xi;}}_{51}+0.045{\mathrm{\&xi;}}_{54}+{0.125\mathrm{\&xi;}}_{61}+{0.042\mathrm{\&xi;}}_{64}\end{array}$

Wherein,

$\begin{array}{cccc}{\mathrm{\&xi;}}_{11}=\frac{\left|{\mathrm{<figure-callout\; id="11"\; label="M"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">M</figure-callout>}}_{11}^2\right|}{0.044C},& {\mathrm{\&xi;}}_{14}=\frac{\left|{\mathrm{<figure-callout\; id="14"\; label="M"\; filenames="HDA0000436798500000082.png,HDA0000436798500000092.png"\; state="\{\{state\}\}">M</figure-callout>}}_{14}^2\right|}{0.15C},& {\mathrm{\&xi;}}_{21}=\min (\frac{\left|{\mathrm{<figure-callout\; id="21"\; label="M"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">M</figure-callout>}}_{21}^1\right|}{0.38C},\frac{\left|{\mathrm{<figure-callout\; id="21"\; label="M"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">M</figure-callout>}}_{21}^2\right|}{0.38C}),& {\mathrm{\&xi;}}_{24}=\min (\frac{\left|{\mathrm{<figure-callout\; id="24"\; label="M"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">M</figure-callout>}}_{24}^1\right|}{0.18C},\frac{\left|{\mathrm{<figure-callout\; id="24"\; label="M"\; filenames="HDA0000436798500000082.png"\; state="\{\{state\}\}">M</figure-callout>}}_{24}^2\right|}{0.18C})\\ {\mathrm{\&xi;}}_{31}=\min (\frac{\left|{\mathrm{<figure-callout\; id="31"\; label="M"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">M</figure-callout>}}_{31}^1\right|}{0.47C},\frac{\left|{\mathrm{<figure-callout\; id="31"\; label="M"\; filenames="HDA0000436798500000041.png,HDA0000436798500000082.png"\; state="\{\{state\}\}">M</figure-callout>}}_{31}^2\right|}{0.47C}),& {\mathrm{\&xi;}}_{34}=\min (\frac{\left|M_{34}^1\right|}{0.11C},\frac{\left|M_{34}^2\right|}{0.11C})& & \\ {\mathrm{\&xi;}}_{41}=\min (\frac{\left|M_{41}^1\right|}{0.44C},\frac{\left|M_{41}^2\right|}{0.44C}),& {\mathrm{\&xi;}}_{44}=\min (\frac{\left|M_{44}^1\right|}{0.19C},\frac{\left|M_{44}^2\right|}{0.19C})& & \\ {\mathrm{\&xi;}}_{51}=\min (\frac{\left|M_{51}^1\right|}{0.46C},\frac{\left|M_{51}^2\right|}{0.46C}),& {\mathrm{\&xi;}}_{54}=\min (\frac{\left|M_{54}^1\right|}{0.16C},\frac{\left|M_{54}^2\right|}{0.16C}),& {\mathrm{\&xi;}}_6=\frac{\left|M_{61}^1\right|}{0.43C},& {\mathrm{\&xi;}}_{64}=\frac{\left|M_{64}^1\right|}{0.14C}\end{array}$

$\begin{array}{c}{M}_{11}^2=[T_2+21,T_2+21+0.5C]\&cap;{\mathrm{\&Sigma;}}_{k=1}^2[T_1+(k-1)C,T_1+(k-1)C+0.44C]\\ M_{14}^2=[T_2+21,T_2+21+0.5C]\&cap;{\mathrm{\&Sigma;}}_{k=1}^2[T_1+(k-1)C+0.85C,T_1+(k-1)C+C]\\ M_{21}^1=[T_1+21,T_1+21+0.54C]\&cap;{\mathrm{\&Sigma;}}_{k=1}^2[T_2+(k-1)C,T_2+(k-1)C+0.38C]\\ M_{21}^2=[T_3+15,T_3+15+0.6C]\&cap;{\mathrm{\&Sigma;}}_{k=1}^2[T_2+(k-1)C,T_2+(k-1)C+0.38C]\\ M_{24}^1=[T_1+21,T_1+21+0.54C]\&cap;{\mathrm{\&Sigma;}}_{k=1}^2[T_2+(k-1)C+0.82C,T_2+(k-1)C+C]\end{array}$

91≤C≤121

Take common signal cycle C and each crossing thing craspedodrome phase place green light initial time T as decision variable, according to Global Genetic Simulated Annealing Algorithm, using Matlab and Visual C++ programming to calculate can be in the hope of the correlationship between average latency and signal period, each crossing thing craspedodrome green light initial time between interior each crossing, subarea 1, as shown in Figure 9.Wherein Population Size is 1000, and stopping evolutionary generation is 50, crossover probability p _c=0.8, variation Probability p _m=0.1, decision variable number is 7, and the number of bits of variable is 10, and adopting binary-coded chromosome is 1000 × 70 matrixes.

As can be known from Fig. 9, optimization objective function value and best decision variate-value are respectively F=0.69, C=112s, T ₁=84s, T ₂=53s, T ₃=74s, T ₄=51s, T ₅=97s, T ₆=46s.Take crossing 1 thing craspedodrome phase place green light initial time as starting point, calculate crossing 2-6 according to Adjacent Intersections formula in subarea as shown in table 4 with respect to the phase differential of crossing 1, wherein 1-2 represents the relative phase difference of 1 leading crossing 2, crossing.The optimum signal cycle C obtaining and signal phase split substitution subarea multi-intersection group decision model can be obtained to the each signal phase time value in each crossing.

Table 4 subarea 1 optimum signal timing scheme result of calculation

In like manner, try to achieve subarea 2 common signal computation of Period results as shown in table 5:

Table 5 subarea 1 optimum signal timing scheme result of calculation

Subarea 3 common signal computation of Period results are as shown in table 6:

Table 6 subarea 3 optimum signal timing scheme result of calculations

Subarea 4 only has a crossing 21, and its cycle is 105s, and each phase time is respectively 46s, 14s, 24s and 21s, does not need to calculate phase differential.

(4) traffic simulation analysis

For access control sub-area division is theoretical and the rationality of traffic zone coordination control model method, utilize the microscopic traffic simulation software VISSIM5.0 of German PTV company exploitation, carry out respectively simulation analysis and comparative evaluation for present situation signal time distributing conception and the optimum signal timing design proposal controlled under sub-area division scheme.

Build the western basic emulation road network in Huan Shi main road according to the physical conditions such as present situation link length, width, number of track-lines, crossing canalization situation and traffic control organizational information, to coordinating front signal timing scheme and coordinating rear optimum signal timing scheme distribution and carry out traffic simulation analysis, the emulated datas such as the average stop frequency of vehicle, delay time at stop and the fuel consumption of each intersection signal phase place are as shown in Figure 10 to Figure 15, and the emulated datas such as the average stop frequency of the vehicle of whole control area, delay time at stop and fuel consumption are as shown in table 7.In figure, the simulation run result of front signal timing scheme is coordinated in red pattern representative, and the simulation run result of rear signal optimum signal timing scheme is coordinated in blue pattern representative.

Can find out from Figure 10 to Figure 11, the average stop frequency of Nei Ge crossing, control area vehicle and delay time at stop all obviously reduce, and wherein 3 vehicle average stop frequency in crossing improves maximum, is 40%; The 14 vehicle mean delay times of crossing improve maximum, are 33%.

The emulated data of contrast Figure 12 to Figure 15 can be found out, each crossing coordinate before and after vehicle average fuel consumption, oxynitride discharge, VOC(volatile organic compounds (Volatile Organic Compounds)) discharge is consistent with the improvement in performance amplitude of carbon monoxide emission, except the improvement ratio of crossing 2 is-1%, other each crossings all improve a lot at aspects such as reducing fuel consumption and exhaust emissions.

As can be seen from Table 7, after coordinating, there have been obvious improvement the average stop frequency of vehicle and the delay time at stop of whole control area, and wherein stop frequency has improved 27.03%, and the delay time at stop has improved 22.67%.The improvement in performance ratio of fuel consumption, oxynitrides, VOC and carbon monoxide emission is identical, be all 6.95%, this illustrates that these four performance index properties are similar, and Fuel Consumption is fewer, and the exhaust pollutant discharge capacitys such as oxynitrides, VOC and carbon monoxide will be fewer.

Front and back vehicle average behavior index contrast is coordinated in the whole control area of table 7

(5) real system operating analysis

Control system drops into after normal use, by implementing coordinating control of traffic signals optimizing design scheme, the traffic efficiency of arterial highway craspedodrome wagon flow is significantly improved, contrast effect before and after control system enforcement is obvious, reach system Construction expection technical indicator completely, part index number data are more as shown in table 8.

Table 8 control system is implemented front and rear part achievement data comparison

Performance index

Average stop frequency

The mean delay time

Average speeds

Automotive emission amount

Expection improves effect

Reduce 27%

Reduce

22%

Shorten

20%

Reduce

7%

Reality is improved effect

Reduce 32%

Reduce

30%

Shorten 26%

Reduce

10%

The examples of implementation of the above are only the present invention's preferred embodiment, not limit practical range of the present invention with this, therefore the variation that all shapes according to the present invention, principle are done all should be encompassed in protection scope of the present invention.

Claims (2)

1. a seed zone multi-intersection group decision control method, is characterized in that, comprises the following steps:

1) traffic parameter---the crossing coordination rate based on a quantitative description crossing harmony power of wagon flow continuity theory proposition, and provide the computing formula of crossing coordination rate, comprise the computing formula that Adjacent Intersections coordination rate and subarea multi-intersection chief coordinator lead;

2) according to the computing formula of Adjacent Intersections coordination rate, set up the Adjacent Intersections Decision Control Model based on Adjacent Intersections coordination rate, structure Adjacent Intersections wagon flow input/output relation formula, coordinates to control for intersection group and prepares;

3) set up subarea multi-intersection group decision control model, determine common signal cycle and each crossing Split Optimization method, then set up with subarea multi-intersection chief coordinator and lead the phase differential population effect function model that is optimization aim to the maximum;

4) according to common signal cycle and phase differential population effect function model, in conjunction with Adjacent Intersections wagon flow input/output relation formula, adopt Global Genetic Simulated Annealing Algorithm to solve subarea multi-intersection group decision control model, obtain optimizing decision variable, generate best intersection signal timing scheme, feasible region signal timing dial optimization and coordination control.

2. a seed zone multi-intersection group decision control method according to claim 1, is characterized in that, described step 1) comprises the following steps:

1.1) Adjacent Intersections coordination rate refers between the green zone of crossing, upstream in the situation that postponing certain hour, is mapped to downstream intersection, with the degree that overlaps between downstream intersection respective phase green zone; It is a traffic parameter that harmony between Adjacent Intersections is carried out to quantitative description, the objective impact on Adjacent Intersections harmony by the road section traffic volume operation conditions between concentrated expression Adjacent Intersections and signal controlling demand difference; For thing craspedodrome phase place, thing craspedodrome phase coordination rate is defined as the two-way coordination rate between eastern import and western import, among eastern import coordination rate and western import coordination rate, get little, i.e. k signal period crossing I _i,jthe coordination rate of thing craspedodrome phase place

for:

${\mathrm{\&xi;}}_{i,j}^{1k}=\min \{\frac{H_{i+1,j\&RightArrow;i,j}^k\&cap;\left({\mathrm{\&Sigma;}}_{k=0}^{\&infin;}{H}_{i,j}^{1k}\right)}{\left|H_{i+1,j}^k\right|},\frac{H_{i-1,j\&RightArrow;i,j}^k\&cap;\left({\mathrm{\&Sigma;}}_{k=0}^{\&infin;}{H}_{i,j}^{1k}\right)}{\left|H_{i-1,j}^k\right|}\}$

In formula, | ﹒ ﹒ ﹒ | be burst length,

be k cycle crossing I _i,jbetween the green zone of thing craspedodrome phase place,

for crossing I _{i+1, j}output wagon flow Interval Maps is to downstream intersection I _i,jthe interval at place,

be k cycle thing craspedodrome phase place crossing I _i,jwith I _{i+1, j}coordination;

1.2) Adjacent Intersections coordination rate is four of crossings phase coordination rate sum, i.e. k cycle Adjacent Intersections coordination rate

for:

${\mathrm{\&xi;}}_{i,j}^k={\mathrm{\&Sigma;}}_{l=1}^4{\mathrm{\&xi;}}_{i,j}^{1k};$

1.3) be tolerance Adjacent Intersections coordination rate, introduce the concept of non-Coordination below, crossing, upstream I _{i+1, j}between green zone, be mapped to downstream intersection I _i,j, and and downstream intersection respective phase green zone between not intersection, be called non-Coordination k signal period crossing I _i,jbetween the green zone in craspedodrome direction with Adjacent Intersections I _{i+1, j}the non-Coordination of wagon flow output interval

be expressed as follows:

1.4), based on the above-mentioned analysis to Adjacent Intersections coordination rate, lead and can be calculated by following formula for the subarea multi-intersection chief coordinator of M × N crossing of k signal period subarea multi-intersection group:

${\mathrm{\&xi;}}^k=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{\mathrm{\&Sigma;}}_{l=1}^4{\mathrm{\&xi;}}_{i,j}^{\mathrm{lk}};$

Described step 2) comprise the following steps:

2.1) thing craspedodrome phase coordination rate is calculated

For crossing I _i,jthing craspedodrome phase place, main considering intersection I _{i-1, j}and I _{i+1, j}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between thing craspedodrome green zone, place, k signal period crossing I _i,jthing craspedodrome between green zone is:

$H_{i,j}^{1k}=[T_{i,j}+(k-1)C_{i,j},T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1]$

Crossing I _{i-1, j}output wagon flow interval comprise that thing keeps straight on and the interval of two phase places of north and south left/right rotation:

$H_{i-1,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}{T}_{i-1,j}+(k-1)C_{i-1,j}{+g}_{i-1,j}^1{+g}_{i-1,j}^2]$

Crossing I so _{i-1, j}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$H_{i-1,j\&RightArrow;i,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^3-Q_{i,j}^{8k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,j}^1+g_{i-1,j}^2+\frac{l_{i,j}^3-Q_{i,j}^{8k}}{v}]$

Wherein, establish C _i,jwith C _{i-1, j}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i-1, j}α _{i-1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing craspedodrome green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{11}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^1}{H}_{i,j}^{1k}\right)$

Now crossing I _i,jin western importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{11}=\frac{\left|M_{i,j}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,j}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)}$

In like manner, crossing I _{i+1, j}output wagon flow interval comprise that thing keeps straight on and the interval of two phase places of north and south left/right rotation:

$H_{i+1,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,j}^1+g_{i+1,j}^2]$

Crossing I so _{i+1, j}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$H_{i+1,j\&RightArrow;i,j}^k=[T_{i+1,j}+(k-1)C_{i+1,j}+\frac{l_{i,j}^1-Q_{i,j}^{2k}}{v},T_{i+1,j}+(k-1)C_{i+1,j}+g_{i+1,j}^1+g_{i+1,j}^2+\frac{l_{i,j}^1-Q_{i,j}^{2k}}{v}]$

Wherein, establish C _i,jwith C _{i+1, j}lowest common multiple be

phase differential will be with so

do periodically to change; Order

crossing I _{i+1, j}α _{i+1, j}individual output wagon flow Interval Maps is to I _{i, j place}after, with I _i,jcoincidence degree between the thing craspedodrome green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{12}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i+1,j}}{H}_{i+1,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^2}{H}_{i,j}^{1k}\right)$

Now crossing I _i,jin eastern importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{12}=\frac{\left|M_{i,j}^{12}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,j}^{12}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of thing craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,j}^1=\min ({\mathrm{\&xi;}}_{i,j}^{11},{\mathrm{\&xi;}}_{i,j}^{12})=\min (\frac{\left|M_{i,j}^{11}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,j}^1+g_{i+1,j}^2)});$

2.2) thing left/right rotation phase coordination rate is calculated

For crossing I _i,jthing left/right rotation phase place, main considering intersection I _{i-1, j}and I _{i+1, j}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between thing left/right rotation green zone, place; K signal period crossing I _i,jthing left/right rotation between green zone is:

$H_{i,j}^{4k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1+g_{i,j}^2+g_{i,j}^3,T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1+g_{i,j}^2+g_{i,j}^3,g_{i,j}^4]$

According to formula between thing craspedodrome and two phase regions of north and south left/right rotation, crossing I _{i-1, j}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$H_{i-1,j\&RightArrow;i,j}^{\&prime;k}=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^3-Q_{i,j}^{9k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,j}^1+g_{i-1,j}^2+\frac{l_{i,j}^3-Q_{i,j}^{9k}}{v}]$

By upper known

crossing I _{i-1, j}α _{i-1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing left-hand rotation green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{41}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i-1,j\&RightArrow;i,j}^{\&prime;k}\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^1}{H}_{i,j}^{4k}\right)$

Now crossing I _i,jin western importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{41}=\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)}$

In like manner, according to formula between thing craspedodrome and two phase regions of north and south left/right rotation, crossing I _{i+1, j}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

${H\&prime;}_{i-1,j\&RightArrow;i,j}^k=[T_{i-1,j}+(k-1)C_{i-1,j}+\frac{l_{i,j}^1-Q_{i,j}^{1k}}{v},T_{i-1,j}+(k-1)C_{i-1,j}+g_{i-1,j}^1+g_{i-1,j}^2+\frac{l_{i,j}^1-Q_{i,j}^{1k}}{v}]$

By upper known

crossing I _{i+1, j}α _{i+1, j}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the thing left-hand rotation green zone at place is used

represent, its computing formula is as follows:

$M_{i,j}^{42}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i+1,j\&RightArrow;i,j}^{\&prime;k}\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^2}{H}_{i,j}^{4k}\right)$

Now crossing I _i,jin eastern importer coordination rate be upwards:

${\mathrm{\&xi;}}_{i,j}^{42}=\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i-1,j}|H_{i-1,j}^k|}=\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of thing left turn phase is:

${\mathrm{\&xi;}}_{i,j}^4=\min ({\mathrm{\&xi;}}_{i,j}^{41},{\mathrm{\&xi;}}_{i,j}^{42})=\min (\frac{{|M}_{i,j}^{41}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,j}^1+g_{i+1,j}^2)});$

2.3) north and south craspedodrome phase coordination rate is calculated

For crossing I _i,jnorth and south craspedodrome phase place, main considering intersection I _{i, j-1}and I _{i, j+1}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between craspedodrome green zone, north and south, place; K signal period crossing I _i,jnorth and south between craspedodrome green zone is:

$H_{i,j}^{3k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1+g_{i,j}^2,T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1+g_{i,j}^2+g_{i,j}^3]$

Crossing I _{i, j-1}output wagon flow interval comprise the keep straight on interval of two phase places of thing left/right rotation and north and south:

$H_{i,j-1}^k=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1},T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3]$

Crossing I so _{i, j-1}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$\begin{array}{c}{H}_{i,j-1\&RightArrow;i,j}^k=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1}+\frac{l_{i,j}^2-Q_{i,j}^{5k}}{v},\\ T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3+\frac{l_{i,j}^2-Q_{i,j}^{5k}}{v}]\end{array}$

Wherein, establish C _i,jwith C _{i, j-1}lowest common multiple be

phase differential will be with so

do periodically to change; Order crossing I _{i, j-1}α _{i, j-1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the craspedodrome green zone, north and south at place is used

represent, its computing formula is as follows:

$M_{i,j}^{31}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j-1}}{H}_{i,j\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^3}{H}_{i,j}^{3k}\right)$

Now crossing I _i,jcoordination rate in southing mouth direction is:

${\mathrm{\&xi;}}_{i,j}^{31}=\frac{\left|M_{i,j}^{31}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,j}^{31}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

In like manner, crossing I _{i, j+1}output wagon flow interval comprise the keep straight on interval of two phase places of thing left/right rotation and north and south:

$H_{i,j+1}^k=[T_{i,j+1}+(k-1)C_{i,j+1},T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3]$

Crossing I so _{i, j+1}output wagon flow Interval Maps to I _i,jthe interval that place keeps straight on is:

$\begin{array}{c}{H}_{i,j+1\&RightArrow;i,j}^k=[T_{i,j+1}+g_{i,j-1}^1+(k-1)C_{i,j+1}+\frac{l_{i,j}^4-Q_{i,j}^{11k}}{v},\\ T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3+\frac{l_{i,j}^4-Q_{i,j}^{11k}}{v}]\end{array}$

Wherein, establish C _i,jwith C _{i, j+1}lowest common multiple be

phase differential will be with so do periodically to change; Order crossing I _{i, j+1}α _{i, j+1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the craspedodrome green zone, north and south at place is used

represent, its computing formula is as follows:

$M_{i,j}^{32}=\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i-1,j}}{H}_{i,j+1\&RightArrow;i,j}^k\right)\&cap;\left({\mathrm{\&Sigma;}}_{k=1}^{{\mathrm{\&alpha;}}_{i,j}^4}{H}_{i,j}^{3k}\right)$

Now crossing I _i,jcoordination rate in northing mouth direction is:

${\mathrm{\&xi;}}_{i,j}^{32}=\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of north and south craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,j}^3=\min ({\mathrm{\&xi;}}_{i,j}^{31},{\mathrm{\&xi;}}_{i,j}^{32})=\min (\frac{{|M}_{i,j}^{31}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

2.4) north and south left/right rotation phase coordination rate is calculated

For crossing I _i,jnorth and south left/right rotation phase place, main considering intersection I _{i, j-1}and I _{i, j+1}output wagon flow Interval Maps to I _i,jplace, with I _i,jregistration between left/right rotation green zone, north and south, place; K signal period crossing I _i,jnorth and south between left-hand rotation green zone is:

$H_{i,j}^{2k}=[T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1,T_{i,j}+(k-1)C_{i,j}+g_{i,j}^1+g_{i,j}^2]$

According to formula between thing left/right rotation and north and south craspedodrome phase region, crossing I _{i, j-1}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$\begin{array}{c}{H}_{i,j-1\&RightArrow;i,j}^{\&prime;k}=[T_{i,j-1}+g_{i,j-1}^1+(k-1)C_{i,j-1}+\frac{l_{i,j}^2-Q_{i,j}^{6k}}{v},\\ T_{i,j-1}+(k-1)C_{i,j-1}+g_{i,j-1}^1+g_{i,j-1}^2+g_{i,j-1}^3+\frac{l_{i,j}^2-Q_{i,j}^{6k}}{v}]\end{array}$

By upper known

crossing I _{i, j-1}α _{i, j-1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the left-hand rotation green zone, north and south at place is used

represent, its computing formula is as follows:

Now crossing I _i,jcoordination rate in southing mouth direction is:

${\mathrm{\&xi;}}_{i,j}^{21}=\frac{\left|M_{i,j}^{21}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,j}^{21}\right|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)}$

In like manner, according to formula between thing left/right rotation and two phase regions of north and south craspedodrome, crossing I _{i, j+1}output wagon flow Interval Maps to I _i,jthe interval of turning left in place is:

$\begin{array}{c}{H}_{i,j+1\&RightArrow;i,j}^{\&prime;k}=[T_{i,j+1}+g_{i,j+1}^1+(k-1)C_{i,j+1}+\frac{l_{i,j}^4-Q_{i,j}^{12k}}{v},\\ T_{i,j+1}+(k-1)C_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2+g_{i,j+1}^3+\frac{l_{i,j}^4-Q_{i,j}^{12k}}{v}]\end{array}$

By upper known

crossing I _{i, j+1}α _{i, j+1}individual output wagon flow Interval Maps is to I _i,jbehind place, with I _i,jcoincidence degree between the left-hand rotation green zone, north and south at place is used

represent, its computing formula is as follows:

Now crossing I _i,jcoordination rate in northing mouth direction is:

${\mathrm{\&xi;}}_{i,j}^{22}=\frac{\left|M_{i,j}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j-1}|H_{i,j-1}^k|}=\frac{\left|M_{i,j}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)}$

Therefore, crossing I in control time section _i,jthe coordination rate calculating formula of north and south craspedodrome phase place is:

${\mathrm{\&xi;}}_{i,j}^2=\min ({\mathrm{\&xi;}}_{i,j}^{21},{\mathrm{\&xi;}}_{i,j}^{22})=\min (\frac{{|M}_{i,j}^{21}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{22}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

2.5)

calculate

East import

with

value be by determine, according to

the different situations of value,

with

value have following six kinds of situations,

for upstream outgoing vehicles is to the time in downstream, discuss respectively below in various situations

with

value:

1. work as

and time, can try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

In like manner, western import

with

be by determine, according to

the different situations of value,

with value there are following six kinds of situations, discuss respectively below in various situations

with value:

1. work as

and

time, try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, try to achieve

4. work as

time, try to achieve

5. work as time, try to achieve

6. work as

time, try to achieve

Southing mouth

with

be by

determine, according to

the different situations of value,

with

value there are following six kinds of situations, discuss respectively below in various situations

with

value:

1. work as

time, and time, try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

In like manner, northing mouth

with

by

determine, according to

the different situations of value, with

value there are following six kinds of situations, discuss respectively below in various situations

with

value:

1. work as

time, and

try to achieve

2. work as

and

time, try to achieve

3. work as

and

time, can try to achieve

4. work as

time, try to achieve

5. work as

time, try to achieve

6. work as

time, try to achieve

2.6) set up Adjacent Intersections Decision Control Model, comprise the following steps:

2.6.1) establish

while being k end cycle, pass through the vehicle number of upstream and downstream, l track detecting device along a direction,

be the vehicle number being detained between this respective direction upstream and downstream, track coil when the k-1 cycle, green light signals finished, the vehicle number between this track upstream and downstream detecting device is when k end cycle:

$Q_{i,j}^{\mathrm{lk}}=q_{i,j}^l-z_{i,j}^l+Q_{i,j}^{l(k-1)}$

$Q_{i,j}^{\lim }=\frac{L}{h}$

In formula: L is the distance between upstream and downstream detecting device, h is space headway,

for the maximum vehicle number that can hold between the detecting device of upstream and downstream, track;

2.6.2) take vehicle average latency minimum as optimization aim, maximize and fall into the interval vehicle number that overlaps, consider the each entrance driveway magnitude of traffic flow in crossing simultaneously, the Adjacent Intersections Decision Control Model of foundation based on coordination rate is as follows:

$\begin{array}{c}\max f\left(N_{i,j}\right)=\max (q_{i,j}^2,q_{i,j}^8){\mathrm{\&xi;}}_{i,j}^1+\max (q_{i,j}^6,q_{i,j}^{12}){\mathrm{\&xi;}}_{i,j}^2\\ +\max (q_{i,j}^5,q_{i,j}^{11}){\mathrm{\&xi;}}_{i,j}^3+\max (q_{i,j}^3,q_{i,j}^9){\mathrm{\&xi;}}_{i,j}^4\end{array}$

In formula:

${\mathrm{\&xi;}}_{i,j}^1=\min ({\mathrm{\&xi;}}_{i,j}^{11},{\mathrm{\&xi;}}_{i,j}^{12})=\min (\frac{{|M}_{i,j}^{11}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{12}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,j}^1+g_{i+1,j}^2)});$

${\mathrm{\&xi;}}_{i,j}^2=\min ({\mathrm{\&xi;}}_{i,j}^{21},{\mathrm{\&xi;}}_{i,j}^{22})=\min (\frac{{|M}_{i,j}^{21}|}{{\mathrm{\&alpha;}}_{i-1,j}(g_{i-1,j}^2+g_{i-1,j}^3)},\frac{\left|M_{i,j}^{22}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,j}^2+g_{i+1,j}^3)});$

${\mathrm{\&xi;}}_{i,j}^3=\min ({\mathrm{\&xi;}}_{i,j}^{31},{\mathrm{\&xi;}}_{i,j}^{32})=\min (\frac{{|M}_{i,j}^{31}|}{{\mathrm{\&alpha;}}_{i,j-1}(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{32}\right|}{{\mathrm{\&alpha;}}_{i,j+1}(g_{i,j+1}^2+g_{i,j+1}^3)});$

${\mathrm{\&xi;}}_{i,j}^4=\min ({\mathrm{\&xi;}}_{i,j}^{41},{\mathrm{\&xi;}}_{i,j}^{42})=\min (\frac{\left|M_{i,j}^{41}\right|}{{\mathrm{\&alpha;}}_{i-1,j}^1(g_{i-1,j}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42}\right|}{{\mathrm{\&alpha;}}_{i+1,j}(g_{i+1,j}^1+g_{i+1,j}^2)});$

be the maximal value of eastern import and western import straight-going traffic flow in the first phase place thing craspedodrome phase place, for the maximal value of southing mouth in the left/right rotation phase place of north and south and northing mouth left turn traffic amount,

for the maximal value of southing mouth in north and south craspedodrome phase place and northing mouth straightgoing vehicle flow, for the maximal value of eastern import in thing left/right rotation phase place and western import left turn traffic amount;

2.7) structure Adjacent Intersections wagon flow input/output relation formula

Suppose that road network structure is M × N, when known boundaries is sailed the cycle arrival rate of control area into

time, utilize the steering flow distribution ratio of the each import in each crossing, can be for the M in control area × (N-1)+N bar unknown flow rate crossing inlet road, set up M × (N-1)+N discharge relation equation, the relation between cycle vehicle arrival rate and crossing, upstream output rating to all unknown flow rate crossing inlets road is calculated and is solved:

$\begin{array}{c}{q}_{\mathrm{1,2}}^7=u_{\mathrm{1,2}}^7\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^7\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^8=u_{\mathrm{1,2}}^8\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^8\&CenterDot;(q_{\mathrm{1,1}}^4+u_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^9=u_{\mathrm{1,2}}^9\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^9\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ q_{M,N}^7=u_{M,N}^7\&CenterDot;z_{M,N-1}^1=u_{M,N}^7\&CenterDot;\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^8=u_{M,N}^8\&CenterDot;Z_{M,N-1}^1=u_{M,N}^8(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^9=u_{M,N}^9\&CenterDot;z_{M,N-1}^1=u_{m,n}^9\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\end{array}$

In formula:

for the steering flow distribution ratio in crossing inlet road;

Described step 3) comprises the following steps:

3.1) the common signal cycle is optimized

3.1.1) obtain the Webster optimal period duration of each crossing by single-point timing signal timing method, the formula of reduction of Webster optimum signal cycle duration is:

$C_0=\frac{1.5L+5}{1-Y};$

3.1.2) getting the wherein cycle duration of crucial crossing is reference signal cycle C _cri, therefore, reference signal cycle C _crifor:

C _cri＝max(C ₁,...,C _n)；

3.1.3) on the basis in reference signal cycle, design the span in common signal cycle, the permission variation range in common signal cycle is:

[C _cri-M,C _cri+M]

Wherein, the value of M is actual traffic traffic state value between 10-15 as required, and the optimal value in common signal cycle is solved in conjunction with the optimization of phase differential by pattern search strategy;

3.2) Split Optimization

Take crossing, crucial vehicle mean delay minimal time is as target, and using the total saturation degree minimum in saturation degree approximately equal, crossing of each strand of key flow as split distribution principle, designed phase split should be directly proportional to its magnitude of traffic flow ratio:

$\frac{{\mathrm{\&lambda;}}_i}{{\mathrm{\&lambda;}}_j}=\frac{y_i}{y_j}$

In formula: i, j are signal phase sequence number, the magnitude of traffic flow ratio that y is key flow;

3.3) offset optimization

Choose the craspedodrome phase place starting point moment of a certain crossing as the corresponding time point of its phase differential setting, utilize relative phase difference, the signal phase sequence set-up mode of upstream and downstream crossing, intersection signal timing parameter between Adjacent Intersections, can extrapolate crossing I _i,jinitial relative phase difference O with each Adjacent Intersections _i,j, its computing formula is as follows:

$\begin{array}{c}{O}_{i+1,j}=T_{i+1,j}-T_{i,j}\\ O_{i-1,j}=T_{i-1,j}-T_{i,j}\\ O_{i,j+1}=T_{i,j+1}+g_{i,j+1}^1+g_{i,j+1}^2-T_{i,j}-g_{i,j}^1-g_{i,j}^2\\ O_{i,j-1}=T_{i,j-1}+g_{i,g-1}^1+g_{i,j-1}^2-T_{i,j-1}-g_{i,j}^1-g_{i,j}^2;\end{array}$

3.4) according to crossing wagon flow input/output relation, be minimised as target with the vehicle average latency in road network, lead maximum with all crossing chief coordinators of road network and turn to target, set up subarea multi-intersection group decision control model:

$\begin{array}{c}\max F(C,T)=\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}[\max (q_{i,j}^2,q_{i,j}^8){\mathrm{\&xi;}}_{i,j}^{1k}+\max (q_{i,j}^6,q_{i,j}^{12}){\mathrm{\&xi;}}_{i,j}^{2k}\\ +\max (q_{i,j}^5,q_{i,j}^{11}){\mathrm{\&xi;}}_{i,j}^{11}+\max (q_{i,j}^3,q_{i,j}^9){\mathrm{\&xi;}}_{i,j}^{4k}]\end{array}$

In formula:

${\mathrm{\&xi;}}_{i.j}^{1k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.j}^{12k}=\frac{\left|M_{i,j}^{12k}\right|}{(g_{i+1,j}^1+g_{i+1,j}^2)}i=1\\ {\mathrm{\&xi;}}_{i.j}^{11k}=\frac{\left|M_{i,j}^{11k}\right|}{(g_{i-1,j}^1+g_{i-1,j}^2)}i=M\\ \min ({\mathrm{\&xi;}}_{i.j}^{11k},{\mathrm{\&xi;}}_{i.j}^{12k})=\min (\frac{\left|M_{i,j}^{11k}\right|}{(g_{i-1,j}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{12k}\right|}{(g_{i+1,j}^1+g_{i+1,j}^2)})i\&NotEqual;1,M\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{2k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.j}^{22k}=\frac{\left|M_{i,j}^{22k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)}j=1\\ {\mathrm{\&xi;}}_{i.j}^{21k}=\frac{\left|M_{i,j}^{21k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)}j=N\\ \min ({\mathrm{\&xi;}}_{i.j}^{21k},{\mathrm{\&xi;}}_{i.j}^{22k})=\min (\frac{\left|M_{i,j}^{21k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{22k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)})j\&NotEqual;1,N\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{3k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.j}^{3k}=\frac{\left|M_{i,j}^{32k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)}j=1\\ {\mathrm{\&xi;}}_{i.j}^{31k}=\frac{\left|M_{i,j}^{31k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)}j=N\\ \min ({\mathrm{\&xi;}}_{i.j}^{3k},{\mathrm{\&xi;}}_{i.j}^{32k})=\min (\frac{\left|M_{i,j}^{31k}\right|}{(g_{i,j-1}^2+g_{i,j-1}^3)},\frac{\left|M_{i,j}^{32k}\right|}{(g_{i,j+1}^2+g_{i,j+1}^3)})j\&NotEqual;1,N\end{array}\right.$

${\mathrm{\&xi;}}_{i.j}^{4k}=\left\{\begin{array}{c}{\mathrm{\&xi;}}_{i.j}^{42k}=\frac{\left|M_{i,j}^{42k}\right|}{(g_{i+1,j}^1+g_{i+1,j}^2)}i=1\\ {\mathrm{\&xi;}}_{i.j}^{41k}=\frac{\left|M_{i,j}^{41k}\right|}{(g_{i-1,j}^1+g_{i-1,j}^2)}i=M\\ \min ({\mathrm{\&xi;}}_{i.j}^{41k},{\mathrm{\&xi;}}_{i.j}^{42k})=\min (\frac{\left|M_{i,j}^{41k}\right|}{(g_{i-1,j}^1+g_{i-1,j}^2)},\frac{\left|M_{i,j}^{42k}\right|}{(g_{i+1,j}^1+g_{i+1,j}^2)})i\&NotEqual;1,M\end{array}\right.$

$\begin{array}{c}{q}_{\mathrm{1,2}}^7=u_{\mathrm{1,2}}^7\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^7\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^8=u_{\mathrm{1,2}}^8\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^8\&CenterDot;(q_{\mathrm{1,1}}^4+u_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ q_{\mathrm{1,2}}^9=u_{\mathrm{1,2}}^9\&CenterDot;z_{\mathrm{1,1}}^1=u_{\mathrm{1,2}}^9\&CenterDot;(q_{\mathrm{1,1}}^4+q_{\mathrm{1,1}}^8+q_{\mathrm{1,1}}^{12})\\ \&CenterDot;\\ \&CenterDot;\\ \&CenterDot;\\ q_{M,N}^7=u_{M,N}^7\&CenterDot;z_{M,N-1}^1=u_{M,N}^7\&CenterDot;\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^8=u_{M,N}^8\&CenterDot;Z_{M,N-1}^1=u_{M,N}^8(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\\ q_{M,N}^9=u_{M,N}^9\&CenterDot;z_{M,N-1}^1=u_{m,n}^9\&CenterDot;(q_{M,N-1}^4+q_{M,N-1}^8+q_{M,N-1}^{12})\end{array}$

C _cri-M＜C _i,j＜C _cri+M；

Described step 4) comprises the following steps:

4.1) algorithm search strategy

The timing parameter of subarea multi-intersection group decision control model comprises common signal cycle, split, phase differential, wherein split can be according to the magnitude of traffic flow ratio in crossing inlet road, solve according to key flow saturation degree principle, common signal cycle and phase differential can, according to subarea multi-intersection group decision control model, utilize intelligent algorithm to be optimized and solve; Select Global Genetic Simulated Annealing Algorithm to common signal cycle C _i,jwith phase differential O _i,jbe optimized, lead maximum or vehicle average latency minimum to realize subarea multi-intersection chief coordinator; Therefore still adoption rate distributes coding/decoding method, chooses proportionality factors lambda _ifor decision variable, i=1 ...., n, λ ₀=0, n is crossing, subarea number, supposes that a crossing green light initial time in n crossing is given, λ so ₁-λ _n-1be used for calculating the green light initial time of all the other crossings, λ _nbe used for calculating common signal cycle duration; λ after every generation is evolved ₁-λ _nsubstitution following formula is asked its corresponding signal timing dial parameter respectively; Signal timing dial parameter substitution subarea multi-intersection group decision model formation after every generation optimization is tried to achieve to target function value and the fitness value that each decision variable is corresponding, genetic algorithm is carried out follow-on selection according to fitness value, until algorithm finishes while meeting end condition:

T _i,j＝(C _i,j-1)·λ _l,i＝1,...,M,j＝1,...,N,l＝1,...,n-1

C _i,j＝C _min+int[(C _max-C _min)·λ _n]

4.2) Algorithm for Solving step

The Global Genetic Simulated Annealing Algorithm that solves subarea multi-intersection group decision control model, comprises the following steps:

4.2.1) initialization: the crossover probability p that determines genetic algorithm _c, variation Probability p _m, individuality sum N and the maximum evolutionary generation M of every generation population, each individuality shows one group of signal time distributing conception by e fragment gene string list, determines the interior cycle index H of simulated annealing, the initial value T of temperature ₀, make T=T ₀;

4.2.2), from multiple individualities of random generation and calculate fitness value, the probability distribution determining by fitness function is therefrom selected good N the individual initial population P of composition (0);

4.2.3) the target function value F (C, T) of calculating population, according to target function value, calculates each individual fitness value

evaluate the fitness value of colony;

4.2.4) carry out genetic manipulation, comprise selection, crossover and mutation operator;

4.2.5) population P (gen) is carried out to simulated annealing operation, makes i=1:

If 1. i=N, goes to step 4.2.6); Otherwise make circulation round counting k=1;

2. utilize state to produce function and produce the new state of individual P (gen), and calculate its fitness;

3. accepting formula with Metropolis probability accepts new individual;

If 4. k=H, makes i=i+1, go to step 1.; Otherwise make k=k+1, go to step 2.;

4.2.6) output new population, moves back temperature, makes T=0.5T, goes to step 4.2.7);

4.2.7) judge whether genetic algebra reaches maximum, is to stop calculating output optimum solution, otherwise go to step 4.2.3).

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