CN105303833A - Viaduct sudden event discrimination method based on microwave vehicle detector - Google Patents

Abstract

The invention belongs to urban viaduct Information Collecting amp; Processing technical fields, and in particular to a kind of overpass emergency event method of discrimination based on microwave vehicle detector. Steps are as follows: installation microwave vehicle detector is simultaneously debugged; Obtain microwave vehicle detector data; Calculate the equivalent volume of traffic QLj in single lane; Calculate the averag density KLj in single lane; Calculate the averag density KLj in single lane; Calculate overpass road-section average travel speed Predict the road-section average travel speed Vtp in t-th of sampling period; Calculate the road-section average travel speed standard deviation S in past 4 sampling periods; Obtain the road-section average travel speed in t-th of sampling period predicted value and actual value difference and standard deviation ratio Q; Traffic incident differentiates. Faster, measuring and calculating process more succinctly facilitates the responsiveness of data acquisition of the present invention, and the precise effect of online results of measuring is higher, can in time, effectively handle overpass emergency event, the generation of traffic jam is greatly reduced.

Description

Based on the overpass accident method of discrimination of microwave vehicle detecting device

Technical field

The invention belongs to urban viaduct Information Collecting & Processing technical field, be specifically related to a kind of overpass accident method of discrimination based on microwave vehicle detecting device.

Background technology

Overpass in occupation of consequence, is the main artery of urban transportation in the traffic system of large-and-medium size cities.If overpass generation accident, will cause large-scale traffic congestion, affect Urban Residential Trip, therefore overpass accident is distinguished right form wrong and is often necessary.

The traffic information collection of urban road is the basis that overpass accident differentiates.At present, conventional checkout equipment has video detection, Coil Detector, geomagnetism detecting, but all there is drawback miscellaneous in these detection meanss of practical application.As video detects the frequent loss of data of impact etc. that interference is comparatively large, Coil Detector can destroy road surface, geomagnetism detecting is subject to radio communication by light.In addition, for the developing direction of the current urban transportation be showing improvement or progress day by day, judge whether road is in the demand that congestion status also can not meet traffic administration described above merely, calculate more rapidly and efficiently, the higher theme becoming the measuring and calculating of overhead road conditions gradually of response time shorter, accuracy.How to seek the measuring and calculating of the traffic for the overpass accident mode meeting above-mentioned requirements, to possess faster while data response, synchronously guarantee its measuring and calculating high efficiency of process and high precision of results of measuring, thus ensure that traffic administration person can carry out the traffic organization of reasonable science in the time very short under generation event, avoid second accident occurring and blocking up to reach, the impact of minimizing accident and the object of traffic delay, the level of decision-making that final raising traffic administration person event is disposed and intelligent level, by the technical barrier that field of traffic control is urgently to be resolved hurrily nearly ten years.

Summary of the invention

Object of the present invention, for overcoming above-mentioned the deficiencies in the prior art, provides a kind of overpass accident method of discrimination based on microwave vehicle detecting device of more efficient quick; The response of its data acquisition is faster, and measuring and calculating process more succinctly facilitates, and synchronously can realize the high precision effect of online results of measuring, effectively can meet the rapidly and efficiently regulatory requirement of current overpass traffic.

For achieving the above object, present invention employs following technical scheme:

Based on an overpass accident method of discrimination for microwave vehicle detecting device, it is characterized in that comprising the following steps:

1), on overpass section to be detected, microwave vehicle detecting device be installed and debug;

2), obtain microwave vehicle detecting device data measured, these data comprise quantity and the time occupancy of institute's driving vehicle vehicle, each vehicle on each track reference numeral, track;

3), by each motor vehicle on track and Manpower Transportation amount, be converted into the equivalent volume of traffic of Standard of vehicle with reduction coefficient, obtain the equivalent volume of traffic Q in single track _lj, formula is as follows:

Q _Lj＝∑Q _iE _i

Wherein,

Q _ljit is the equivalent volume of traffic in jth track;

Q _iit is the vehicle fleet size absolute number of i-th kind of vehicle in jth track;

E _iit is the reduction coefficient of i-th kind of vehicle in jth track;

4) the average density K in single track, is calculated _lj:

$K_{Lj}=\frac{{\mathrm{occ}}_j}{A}$

Wherein:

K _ljit is jth track average density;

Occ _jit is the time occupancy in jth track;

A is constant;

5) the average overall travel speed V in single track, is calculated _lj:

$V_{Lj}=\frac{Q_{Lj}}{K_{Lj}}$

Wherein:

V _ljit is jth track average overall travel speed;

6) overpass road-section average travel speed, is obtained its computing formula is as follows:

$\stackrel{\‾}{V}=\frac{\underset{j=1}{\overset{n}{\Σ}}{V}_{Lj}}{n}$

Wherein:

N is the track sum that section comprises;

7) the road-section average travel speed V in t sampling period, is predicted _tp;

$V_{tp}=\frac{{\stackrel{\‾}{V}}_{t-1}*4+{\stackrel{\‾}{V}}_{t-2}*3+{\stackrel{\‾}{V}}_{t-3}*2+{\stackrel{\‾}{V}}_{t-4}*1}{10}$

Wherein:

it is the road-section average travel speed in t-1 sampling period; By that analogy,

8) the road-section average travel speed standard deviation S in 4 sampling periods in the past, is calculated:

$S={\left\{\frac{1}{4}\underset{i=1}{\overset{4}{\Σ}}{\[{\stackrel{\‾}{V}}_{t-i}-{\stackrel{\‾}{V}}_t\]}^2\right\}}^{1/2}$

9), set up with the predicted value of the road-section average travel speed in t sampling period and actual value difference and the computing formula of ratio Q of standard deviation, as follows:

$Q=\frac{\left|{\stackrel{\‾}{V}}_t-V_{tp}\right|}{S}$

Wherein: it is the road-section average travel speed actual value in t sampling period;

V _tpit is the road-section average travel speed prediction value in t sampling period;

S is the road-section average travel speed standard deviation in 4 sampling periods in the past;

10), traffic incident judgement is carried out:

Carry out traffic incident judgement:

Compared with setting threshold value M by Q, wherein M=2;

As Q > M, then judge accident occurs;

As Q≤M, then judge without accident.

Described step 1) in, the track scope detected as required adjusts angle and the height of detecting device, ensures that detecting device beam projection can cover all tracks needing to detect, and makes this projection simultaneously and detect link length direction orthogonal.

Described step 3) in, i-th kind of vehicle also namely Standard of vehicle be minibus, reduction coefficient is 1.

Beneficial effect of the present invention is:

1), by such scheme, on the one hand, present invention utilizes dependable performance that microwave vehicle detecting device possesses efficient and possess the advantage of multi-target detection function.For the video of traditional one-point measurement, earth magnetism and coil checker, the fixed point acquisition precision of microwave vehicle detecting device is higher, comprise from motorcycle to multiaxis, the vehicle of high vehicle body all can realize accurately differentiating and information acquisition, microwave vehicle detecting device also can carry out high precision test to trailer, avoid the shortcoming reported by mistake by trailer as many vehicles occurred in like product, the parameter such as vehicle flowrate, car speed, lane occupancy ratio, vehicle classification that on road, each track is passed through can be detected, gather accuracy rate and also can effectively be ensured.And because the construction cost of overpass is high, Maintenance Difficulty, pontic can not be damaged, and possesses that installation and maintenance are easy and not destroy the microwave detector of road surface benefit more applicable.And on the other hand, by the special objective formulae discovery process for overpass, with overpass section to be detected for research object, by carrying out Treatment Analysis to the data of microwave vehicle detector acquisition, whether dependence is greater than predetermined threshold value to the average overall travel speed predicted value in overpass section and the ratio between the difference of actual value and normal state standard deviation judges whether accident occurs to differentiate.If generation event, then and alarm, take measures to reduce the loss, improve the traffic management level of overpass under accident.Computation process of the present invention is succinct, and accuracy is high, and objectivity is strong, judges that the accuracy rate of the traffic behavior in overpass section to be detected is high online, effectively can meet the rapidly and efficiently regulatory requirement of current overpass traffic.

Accompanying drawing explanation

Fig. 1 is method flow diagram of the present invention;

Fig. 2 is the time shaft distribution plan in each sampling period;

Fig. 3 is that laying design sketch installed by microwave vehicle detecting device.

Embodiment

For ease of understanding, 1-3 does following description to specific embodiment of the invention structure and workflow by reference to the accompanying drawings herein:

As shown in Figure 1, the overpass accident method of discrimination based on microwave vehicle detecting device disclosed in this invention, comprises the following steps:

1), on overpass section to be detected, microwave vehicle detecting device be installed and debug;

2), microwave vehicle detector data is obtained;

3) the equivalent volume of traffic Q in single track, is calculated _lj;

4) the average density K in single track, is calculated _lj;

5) the average density K in single track, is calculated _lj;

6) overpass road-section average travel speed, is calculated

7) the road-section average travel speed V in t sampling period, is predicted _tp;

8) the road-section average travel speed standard deviation S in 4 sampling periods in the past, is calculated;

9), obtain the predicted value of the road-section average travel speed in t sampling period and actual value difference and the ratio Q of standard deviation;

10), traffic incident differentiates.

Describedly on overpass section to be detected, microwave vehicle detecting device be installed and debug, angle and the height of the track scope adjustment detecting device detected as required, ensure that detecting device beam projection can cover all tracks needing to detect, ensure that projection is orthogonal with detection road simultaneously.Obtain meagre detector data and then comprise lane number, vehicle, the quantity of each vehicle, time occupancy.

Calculate the equivalent volume of traffic Q in single track _ljrefer to and the various motor vehicle of reality and Manpower Transportation amount are converted into the equivalent volume of traffic of certain Standard of vehicle by certain reduction coefficient.Because the path space that different automobile types takies is different, in traffic specialty, in order to the statistic flow of science, the replacing vehicle of different automobile types must be counted as standard vehicle calculated flow rate.Its computing formula is as follows:

Q _Lj＝∑Q _iE _i

Wherein,

Q _ljit is the equivalent volume of traffic in jth track;

Q _iit is the vehicle fleet size absolute number of i-th kind of vehicle in jth track;

E _iit is the reduction coefficient of i-th kind of vehicle in jth track.

Reduction coefficient E _ivalue all have regulation at " highway technical standard " and " urban road design criterion " of China.Reduction coefficient in urban road and the reduction coefficient in highway have little bit different crossing and section also variant.China take minibus as Standard of vehicle, specifically can see " highway technical standard " and " urban road design criterion ".At this for overpass, according to 4.1.2 regulation in CJJ37-2012 " urban road engineering design specifications ": the volume of traffic converts and minibus should be adopted to be Standard of vehicle, and the conversion system of various vehicle should meet the regulation of table 1.

Table 1 vehicle conversion factor

Type of vehicle	Minibus	Motorbus	High capacity waggon	Articulator
					Reduction coefficient	1.0	2.0	2.5	3.0

Calculate the average density K in single track _lj, its computing formula is as follows:

$K_{Lj}=\frac{{\mathrm{occ}}_j}{A}$

Wherein:

K _ljit is jth track average density;

Occ _jit is the time occupancy in jth track;

A is constant, and concrete value needs to carry out demarcation according to real data and learns.The method that current routine adopts is by the traffic flow parameter typing of emulation platform by overpass reality, can learn one group of average density and time occupancy, by the linear fit to this data, can obtain the value of A.

The average overall travel speed V in the single track of described calculating _lj:

$V_{Lj}=\frac{Q_{Lj}}{K_{Lj}}$

Wherein:

V _ljit is jth track average overall travel speed

Calculate the road-section average travel speed of overpass its computing formula is as follows:

$\stackrel{\‾}{V}=\frac{\underset{j=1}{\overset{n}{\Σ}}{V}_{Lj}}{n}$

Wherein:

N is the track sum that section comprises.

it is overpass road-section average travel speed.

The road-section average travel speed V in described t sampling period of prediction _tp.According to the road-section average travel speed V in the road-section average travel speed weighted average calculation next sampling period in 4 sampling periods in past _tp.Concrete symbol logo See Figure 2.

V _tpcomputing formula is as follows:

$V_{tp}=\frac{{\stackrel{\‾}{V}}_{t-1}*4+{\stackrel{\‾}{V}}_{t-2}*3+{\stackrel{\‾}{V}}_{t-3}*2+{\stackrel{\‾}{V}}_{t-4}*1}{10}$

it is the road-section average travel speed in t-1 sampling period; By that analogy,

The road-section average travel speed standard deviation S in 4 sampling periods in described calculating past, computing formula is as follows:

$S={\left\{\frac{1}{4}\underset{i=1}{\overset{4}{\Σ}}{\[{\stackrel{\‾}{V}}_{t-i}-{\stackrel{\‾}{V}}_t\]}^2\right\}}^{1/2}$

Obtain the predicted value of the road-section average travel speed in t sampling period and actual value difference and the ratio K formula of standard deviation as follows:

$Q=\frac{\left|{\stackrel{\‾}{V}}_t-T_{tp}\right|}{S}$

Wherein: it is the road-section average travel speed actual value in t sampling period;

V _tpit is the road-section average travel speed prediction value in t sampling period;

S is the road-section average travel speed standard deviation in 4 sampling periods in the past.

Compared with setting threshold value M by Q, judge whether it accident occurs:

As Q > M, then there is accident; Otherwise, then judge without accident.

The value of M is 2, is namely no more than the standard deviation (more than the standard deviation of 2 times, just meaning this shifts samples) of 2 times.In other words, numeral 2 is exactly the matter of common sense of mathematical statistics, and it is alpha value when degree of confidence is 95%, and 95% is then the setting value of degree of confidence (confidence level) under normal circumstances.

Embodiment 1:

1), on overhead selection one section, north and south, Hefei City, microwave vehicle detecting device be installed and debug;

2), a certain period microwave vehicle detecting device data measured is obtained:

Track 1: the vehicle fleet size 98 of vehicle 1; The vehicle fleet size 2 of vehicle 2; The vehicle fleet size 0 of vehicle 3; The vehicle fleet size 0 of vehicle 4; Time occupancy is 31%.

Track 2: the vehicle fleet size 63 of vehicle 1; The vehicle fleet size 0 of vehicle 2; The vehicle fleet size 0 of vehicle 3; The vehicle fleet size 0 of vehicle 4; Time occupancy is 19%.

Track 3: the vehicle fleet size 76 of vehicle 1; The vehicle fleet size 0 of vehicle 2; The vehicle fleet size 0 of vehicle 3; The vehicle fleet size 0 of vehicle 4; Time occupancy is 23%.

3) the equivalent volume of traffic in single track, is calculated:

Track 1: equivalent volume of traffic Q _l1=∑ Q _ie _i=98*1+2*2+0+0=102,

Track 2: equivalent volume of traffic Q _l2=∑ Q _ie _i=63*1+0+0+0=63,

Track 3: equivalent volume of traffic Q _l3=∑ Q _ie _i=76*1+0+0+0=76.

4) the average density K in single track, is calculated _lj:

A is that one group of density being obtained by emulation platform and time occupancy matching are obtained, A value 0.15.

Track 1:K _l1=0.31 ÷ 0.15=2.067;

Track 2:K _l2=0.19 ÷ 0.15=1.267;

Track 3:K _l3=0.23 ÷ 0.15=1.533.

5) the average overall travel speed V in single track, is calculated _lj:

Track 1:V _l1=102 ÷ 2.067=49.35;

Track 2:V _l2=63 ÷ 1.267=49.72;

Track 3:V _l1=76 ÷ 1.533=49.57.

6) overpass road-section average travel speed, is calculated

$\stackrel{\‾}{V}=\left(49.35+49.72+49.57\right)/3=\mathrm{49.55.}$

7) the road-section average travel speed V in t sampling period, is predicted _tp:

Repeat 6 steps above to calculate respectively ${\stackrel{\‾}{V}}_{t-1}=48.55,{\stackrel{\‾}{V}}_{t-2}=50.01,{\stackrel{\‾}{V}}_{t-3}=49.33,$ ${\stackrel{\‾}{V}}_{t-1}=49.60;$

V _tp＝(48.55*4+50.01*3+49.33*2+49.60*1)/10＝49.28。

8) the road-section average travel speed standard deviation S in 4 sampling periods in the past, is calculated:

$S=\sqrt{\[{(49.37-48.55)}^2+{(49.37-50.01)}^2+{(49.37-49.33)}^2+{(49.37-49.60)}^2\]/4}=0.53$

9), obtain the predicted value of the road-section average travel speed in t sampling period and actual value difference and the ratio Q of standard deviation:

Q＝|49.55-49.28|/0.53＝0.51。

10), traffic incident differentiates:

Due to Q < 2, therefore not there is traffic events.

Embodiment 2:.

1), on overhead selection one section, north and south, Hefei City, microwave vehicle detecting device be installed and debug;

2), a certain period microwave vehicle detecting device data measured is obtained:

Track 1: the vehicle fleet size 150 of vehicle 1; The vehicle fleet size 4 of vehicle 2; The vehicle fleet size 0 of vehicle 3; The vehicle fleet size 0 of vehicle 4; Time occupancy is 71%.

Track 2: the vehicle fleet size 122 of vehicle 1; The vehicle fleet size 1 of vehicle 2; The vehicle fleet size 0 of vehicle 3; The vehicle fleet size 0 of vehicle 4; Time occupancy is 58%.

Track 3: the vehicle fleet size 90 of vehicle 1; The vehicle fleet size 0 of vehicle 2; The vehicle fleet size 0 of vehicle 3; The vehicle fleet size 0 of vehicle 4; Time occupancy is 33%.

3) the equivalent volume of traffic in single track, is calculated:

Track 1: equivalent volume of traffic Q _l1=∑ Q _ie _i=150*1+4*2+0+0=158;

Track 2: equivalent volume of traffic Q _l2=∑ Q _ie _i=122*1+1*2+0+0=124;

Track 3: equivalent volume of traffic Q _l3=∑ Q _ie _i=90+0+0+0=90.

4) the average density K in single track, is calculated _lj:

A is that one group of density being obtained by emulation platform and time occupancy matching are obtained, A value 0.15.

Track 1:K _l1=0.71 ÷ 0.15=4.71;

Track 2:K _l2=0.58 ÷ 0.15=3.87;

Track 3:K _l3=0.33 ÷ 0.15=2.2.

5) the average overall travel speed V in single track, is calculated _lj:

Track 1:V _l1=158 ÷ 4.71=33.54;

Track 2:V _l2=124 ÷ 3.87=32.04;

Track 3:V _l1=90 ÷ 2.2=40.91.

6) overpass road-section average travel speed, is calculated

$\stackrel{\&OverBar;}{V}=\left(33.54+32.04+40.91\right)/3=\mathrm{35.49.}$

7) the road-section average travel speed V in t sampling period, is predicted _tp:

Repeat 6 steps above to calculate respectively ${\stackrel{\&OverBar;}{V}}_{t-1}=48.55,{\stackrel{\&OverBar;}{V}}_{t-2}=50.01,{\stackrel{\&OverBar;}{V}}_{t-3}=49.33,$ ${\stackrel{\&OverBar;}{V}}_{t-1}=49.60;$

V _tp＝(48.55*4+50.01*3+49.33*2+49.60*1)/10＝49.28。

8) the road-section average travel speed standard deviation S in 4 sampling periods in the past, is calculated:

$S=\sqrt{\&lsqb;{(49.37-48.55)}^2+{(49.37-50.01)}^2+{(49.37-49.33)}^2+{(49.37-49.60)}^2\&rsqb;/4}=0.53$

9), obtain the predicted value of the road-section average travel speed in t sampling period and actual value difference and the ratio Q of standard deviation:

Q＝|35.49-49.28|/0.53＝26.01。

10), traffic incident differentiates:

Due to Q > 2, judge traffic incident occurs; Overpass traffic control center receives system alarm, takes measures to reduce the loss.

Claims (3)

1., based on an overpass accident method of discrimination for microwave vehicle detecting device, it is characterized in that comprising the following steps:

1), on overpass section to be detected, microwave vehicle detecting device be installed and debug;

2), obtain microwave vehicle detecting device data measured, these data comprise quantity and the time occupancy of institute's driving vehicle vehicle, each vehicle on each track reference numeral, track;

3), by each motor vehicle on track and Manpower Transportation amount, be converted into the equivalent volume of traffic of Standard of vehicle with reduction coefficient, obtain the equivalent volume of traffic Q in single track _lj, formula is as follows:

Q _Lj＝∑Q _iE _i

Wherein,

Q _ljit is the equivalent volume of traffic in jth track;

Q _iit is the vehicle fleet size absolute number of i-th kind of vehicle in jth track;

E _iit is the reduction coefficient of i-th kind of vehicle in jth track;

4) the average density K in single track, is calculated _lj:

$K_{Lj}=\frac{{\mathrm{occ}}_j}{A}$

Wherein:

K _ljit is jth track average density;

Occ _jit is the time occupancy in jth track;

A is constant;

5) the average overall travel speed V in single track, is calculated _lj:

$V_{Lj}=\frac{Q_{Lj}}{K_{Lj}}$

Wherein:

V _ljit is jth track average overall travel speed;

6) overpass road-section average travel speed, is obtained its computing formula is as follows:

$\stackrel{\&OverBar;}{V}=\frac{\underset{j=1}{\overset{n}{\&Sigma;}}{V}_{Lj}}{n}$

Wherein:

N is the track sum that section comprises;

7) the road-section average travel speed V in t sampling period, is predicted _tp:

$V_{tp}=\frac{{\stackrel{\&OverBar;}{V}}_{t-1}*4+{\stackrel{\&OverBar;}{V}}_{t-2}*3+{\stackrel{\&OverBar;}{V}}_{t-3}*2+{\stackrel{\&OverBar;}{V}}_{t-4}*1}{10}$

Wherein:

it is the road-section average travel speed in t-1 sampling period; By that analogy,

8) the road-section average travel speed standard deviation S in 4 sampling periods in the past, is calculated:

$S={\left\{\frac{1}{4}\underset{i=1}{\overset{4}{\&Sigma;}}{\&lsqb;{\stackrel{\&OverBar;}{V}}_{t-i}-{\stackrel{\&OverBar;}{V}}_t\&rsqb;}^2\right\}}^{1/2}$

9), set up with the predicted value of the road-section average travel speed in t sampling period and actual value difference and the computing formula of ratio Q of standard deviation, as follows:

$Q=\frac{|{\stackrel{\&OverBar;}{V}}_t-V_{tp}|}{S}$

Wherein: it is the road-section average travel speed actual value in t sampling period;

V _tpit is the road-section average travel speed prediction value in t sampling period;

S is the road-section average travel speed standard deviation in 4 sampling periods in the past;

10), traffic incident judgement is carried out:

Compared with setting threshold value M by Q, wherein M=2;

As Q > M, then judge accident occurs;

As Q≤M, then judge without accident.

2. the overpass accident method of discrimination based on microwave vehicle detecting device according to claim 1, it is characterized in that: described step 1) in, the angle of the track scope adjustment detecting device detected as required and height, ensure that detecting device beam projection can cover all tracks needing to detect, make this projection orthogonal with detection link length direction simultaneously.

3. the overpass accident method of discrimination based on microwave vehicle detecting device according to claim 1 and 2, is characterized in that: described step 3) in, i-th kind of vehicle also namely Standard of vehicle be minibus, reduction coefficient is 1.