CN118160018A

CN118160018A - Intelligent control architecture method for traffic signals

Info

Publication number: CN118160018A
Application number: CN202180103630.XA
Authority: CN
Inventors: 孟卫平
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-10-22
Filing date: 2021-10-22
Publication date: 2024-06-07
Also published as: WO2023065057A1

Abstract

An intelligent control architecture method for traffic signals comprises the following steps: 1) creating a signal pattern library, one signal pattern of which provides an efficient service of traffic pattern features, 2) predicting traffic information features, 3) analyzing traffic patterns, 4) matching optimized signals of signal patterns corresponding to the traffic patterns from the signal pattern library, 5) deciding the optimized signals according to a priority rule, 6) making pattern transitions for converting the current signals into the optimized signals, 7) executing the optimized signals. The method has the advantages that 1) the control architecture of the special superposition signal optimization mode library for matching series intelligent prediction traffic modes is most prominent, each signal mode provides extremely efficient traffic service for the traffic mode matched with the signal mode, the signal mode is accurately constructed on a human-computer function boundary, driving waiting can be greatly reduced, the driving waiting is far more than 30%, and the signal mode cannot be optimized through the existing artificial intelligent algorithm; 2) The traffic flow and the flow direction are controlled in a double-broad-spectrum load mode and the high-efficiency response is realized; 3) Is a live architecture that receives dynamic learning to create a new signal pattern library.

Description

Intelligent control architecture method for traffic signals

Technical Field

The present invention relates to the field of traffic control. In particular to a traffic signal artificial intelligence control architecture method.

Background

In recent years, various methods have been proposed to create a two-dimensional green wave signal pattern that efficiently propagates in two directions across each other, and a green wave signal pattern based on two-dimensional green waves and multiple directions across each other, i.e., a superimposed green wave signal (Superpositioned Signals, SPS); the high-efficiency superimposed green wave signals have an optimal control effect on the set network traffic flow; traffic information predicted by using a prediction method comprising artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) is matched and called with the superimposed green wave signal modes in time, so that traffic efficiency can be greatly improved.

Disclosure of Invention

The invention aims to solve the problem of optimizing the architecture of the response of a signal mode to traffic information.

The present invention proposes a solution to achieve the above object, and proposes a control architecture using traffic information prediction-signal mode including artificial intelligence methods, i.e., AI-SPS architecture. The method comprises the following steps:

An intelligent control architecture method for traffic signals is characterized by comprising the following steps:

S1, obtaining road network parameters; creating a plurality of road network traffic signal modes, namely signal modes for short, forming a signal mode library, wherein each signal mode provides control service of road network traffic characteristics corresponding to the mode and forms an optimized signal matched with the road network traffic characteristics; acquiring or configuring a current running signal mode and parameters thereof, namely current signals and parameters thereof;

The road network parameters comprise the length of each road section in the road network and the traffic time of each road section; the traffic time comprises driving time or/and starting time of a congestion vehicle team; the driving time refers to the time taken by the vehicle to complete a road section at a set vehicle speed, and is equal to the length of the road section divided by the set driving speed, or comprises the braking time of subtracting the set driving speed; the time taken by the congestion fleet to drive from the head-to-the-spot to drive from the tail-to-the-spot is equal to the fleet starting coefficient, the congestion coefficient is equal to the ratio of the fleet length to the road section fleet, and the congestion coefficient is equal to 1, represents serious congestion, or comprises the fleet starting coefficient calculated according to the experimental value range of 0.10 to 0.26, or is 0.18 in units: seconds/meter; and (3) injection: in the present application, "or/and the expressions," and "or the expressions," merely means "expression" immediately after the "or/and the" and "or the" and "do not refer to" expression "listed subsequently to the comma, for example," expression 1 "or/and expression 2, in expression 3," expression 1 "and" expression 3 "are in concurrent relationship, and" expression 2 "is in relationship with other expressions of" or, "or" in relationship with "other expressions;

The signal mode comprises any signal for setting the green light propagation flow direction among the phases of the intersections, which is called a green wave; the characteristic parameter of the flow direction as a signal mode green wave is called a green wave flow direction, and the mode is called a green wave-flow direction; the set green wave flow direction is determined by the phase time difference configured by ratio signals running between the intersections, namely the magnitude order of the phase differences, and flows from the intersection with smaller phase difference to the intersection with larger phase difference; the phase time difference between two adjacent intersections is a relative phase difference and is equal to the traffic time set by the road section between the adjacent intersections; the signal mode without phase difference among ratio signals running among all intersections is standing wave, green light change is not transmitted, namely, the ratio mode and the green wave degradation mode are adopted, and the control service function of equal traffic characteristics of all flow directions is provided; the ratio signal finger port configures each phase time length according to the set period and the set ratio; the green wave characteristic parameters or the green wave characteristic parameters also comprise a function called a green wave function, wherein the function comprises guiding or balancing, or/and dredging, or/and mixing, or/and convection guiding, or counter guiding, wherein the guiding refers to that when the green wave flow direction is the same as the controlled traffic flow direction, the relative phase difference is calculated when the road traffic is used by adopting the set driving; equalization means that green light signals have no flow direction, and 0 phase difference of each intersection is synchronous; the green wave flow direction is opposite to the controlled traffic flow direction, and the relative phase difference is calculated when the traffic on each road section is started by adopting a set congestion vehicle team; mixing means when the green wave flow direction and the controlled traffic flow direction comprise the same part and the opposite part, when the road sections of the same flow direction part are used for driving and the road sections of the opposite flow direction part are used for starting by a congestion vehicle team; the guiding of traffic in two opposite directions is one of guiding; the green wave flow direction or the combination of the green wave function and the green wave function is a green wave optimizing signal, and the modes of the green wave flow direction or the combination of the green wave function and the green wave function are respectively marked as green wave-flow direction-guiding, green wave-flow direction-blocking, green wave-flow direction-mixing and standing wave-uniform direction-balancing; the signal mode parameter also comprises a period, and each phase is distributed for a long time, namely phase timing; the phase includes a direction phase representing a control direction of the intersection, or a shunt phase controlling left/right steering among the direction phases;

The road network traffic characteristics, namely traffic modes for short, and the parameters comprise flow directions, or/and conditions, or/and flow, or/and phase shunt quantities of each phase of the intersection; wherein the condition comprises movement, i.e. non-congestion, or/and mixing; congestion refers to the condition of a fleet that the length of a road segment minus the length of the fleet reaches or is less than a set value, or the congestion coefficient reaches or exceeds a set value, which is simply referred to as a road segment congestion set value; mixing means that part of road sections are congested and part of road sections are not congested; the traffic mode parameter flow direction or the traffic mode combined with the traffic mode parameter condition is recorded as traffic mode-flow direction-movement or traffic mode-flow direction-congestion or traffic mode-flow direction-mixing or traffic mode-all direction-movement;

The matching of the signal mode and the road network traffic characteristics refers to the matching of corresponding parameters of traffic modes, and the matching comprises a green wave flow direction optimizing signal which is matched with the traffic mode flow direction in a consistent way, or a green wave optimizing signal which is matched and combined with the green wave function and the traffic mode condition in a corresponding way, and the green wave optimizing signal comprises a green wave-flow direction-guiding matching traffic mode-flow direction-movement, a standing wave-uniform direction-balanced matching traffic mode-uniform direction-movement, or traffic mode-flow direction-congestion matched with the green wave-flow direction-dredged traffic mode-flow direction, or traffic mode-flow direction-mixed matched with the green wave-flow direction; or/and a period optimization signal corresponding to the signal mode period and traffic mode flow; or/and phase timing optimization signals correspondingly matched with traffic mode phase diversion flow when the signal mode phase timing is performed; the flow direction consistent matching means that the flow direction is the same, the corresponding matching means that the corresponding signal mode parameter values of the traffic mode parameter values in the series of the numerical value sets set between the two mode parameter sets are related to the matching, the selectable numerical value sets comprise traffic mode parameter status and signal mode parameter function numerical value sets, traffic mode parameter flow and signal mode parameter period duration numerical value sets, traffic mode parameter phase shunt flow and signal mode parameter phase timing numerical value sets, and traffic mode parameter fleet leader related values and signal mode setting corresponding parameter numerical value sets;

s2, predicting traffic information: according to the obtained traffic information of the road network, the traffic information of the road network with a plurality of time periods in the future, wherein the time periods are actually measured or/and a plurality of time periods in the past, m > =1 cycle c, and each flow direction traffic flow characteristic or/and a fleet characteristic are predicted; when the predicted future period is not set, the next period is the predicted period;

S3, determining an optimized signal: 1) According to the traffic mode obtained by receiving the command signal mode or analyzing the predicted traffic information, finding a signal mode matched with the traffic mode from the signal mode library to form preliminary judgment of the optimized signal, wherein the preliminary judgment comprises 1.1) preliminary judgment of a green wave optimized signal, 1.2) preliminary judgment of a periodic optimized signal or preliminary judgment of a phase timing optimized signal, and the command signal mode refers to a signal mode which does not need to be matched with the traffic information and is forced to execute a command; 2) Or determining an optimized signal from the preliminary judgment according to a priority rule; 3) Making a corresponding mode transition period according to the determined optimized signal and the current signal;

s4, executing an optimization signal: mode transition period control: firstly, running a mode transition period, and then running a new periodic signal;

The intelligent traffic signal control architecture method comprises the following steps: it is characterized in that the method comprises the steps of,

S11, the signal modes in the signal mode library comprise superposition signals;

The road network parameters comprise road network topology forms: a topological parallelogram or a virtual intersection and a virtual road section;

The superimposed signal refers to a green wave signal running in 2 or more cross flow directions within a set period (including a plurality of n > =1 signal periods c), that is, any two-dimensional green wave signal based on two cross flow directions, and any dimension-reducing form thereof; when one of the two-dimensional green waves flows to the green wave phase difference to be configured as 0, the dimension is reduced to one-dimensional green wave;

The green wave parameter flow direction also comprises two crossed flow directions, the green wave is called a two-dimensional green wave, or is marked as a green wave-double flow direction or a two-dimensional green wave-flow direction, and the dimension reduction form comprises a one-dimensional green wave-flow direction and a 0-dimensional standing wave-uniform direction; the green wave optimization signal comprises two-dimensional green wave-flow direction-guide, one-dimensional green wave-flow direction-guide, 0-dimensional standing wave-uniform direction-equalization, two-dimensional green wave-flow direction-unblocking, one-dimensional green wave-flow direction-unblocking, two-dimensional green wave-flow direction-mixing, one-dimensional green wave-flow direction-mixing or two-dimensional green wave-flow direction-opposite guide, one-dimensional green wave-flow direction-opposite guide:

The traffic mode parameter flow direction also comprises two crossed main flow directions, the traffic mode is called two-dimensional traffic, or is marked as traffic-double flow directions or two-dimensional traffic-flow directions, and the dimension reduction form comprises one main flow direction which is one-dimensional traffic-flow direction and 0-dimensional traffic-uniform direction; the traffic mode comprises two-dimensional traffic-flow direction-movement, one-dimensional traffic-flow direction-movement, 0-dimensional traffic-uniform direction-movement, two-dimensional traffic-flow direction-congestion, one-dimensional traffic-flow direction-congestion, two-dimensional traffic-flow direction-mixing, one-dimensional traffic-flow direction-mixing, or two-dimensional traffic-flow direction-convection, one-dimensional traffic-flow direction-convection;

The green wave optimizing signal also comprises an optimizing signal which is matched with the two-dimensional traffic by the two-dimensional green wave, namely the two-dimensional green wave optimizing signal, optionally comprises two-dimensional green wave-flow direction-guide and two-dimensional traffic-flow direction-motion matching, one-dimensional green wave-flow direction-guide and one-dimensional traffic-flow direction-motion matching, 0-dimensional standing wave-average direction-balance and 0-dimensional traffic-average direction-motion matching, or two-dimensional green wave-flow direction-obstruction and two-dimensional traffic-flow direction-congestion matching, or one-dimensional green wave-flow direction-obstruction and one-dimensional traffic-flow direction-congestion matching, or two-dimensional green wave-flow direction-mixing and two-dimensional traffic-flow direction-mixing, or two-dimensional traffic-flow direction-convection matching, or one-dimensional green wave-flow direction-pair-guide and one-dimensional traffic-flow direction-convection matching;

s21, two or more crossed flow direction traffic information in the predicted traffic information or the state thereof;

S12, the superposition state signal also comprises a step of enabling a set motorcade of one phase of a road junction to obtain a plurality of continuous intersection green light signals, abbreviated as solitary waves, and superposing the continuous intersection green light signals in two-dimensional green waves under the set traffic characteristic condition;

the signal mode parameters also comprise a path temporary timing table of the plurality of continuous intersections, which is called an orphan temporary timing table;

The set traffic characteristic conditions comprise instructions, so that a set vehicle team of the flow direction phase of a specified intersection forcibly occupies green light time of other phase vehicle teams of the front intersection, and passes, namely forcible solitary waves; or/and the set motorcade which enables the flow direction phase of the designated intersection to occupy the green light remaining time of motorcades in other phases of the front intersection, namely, the remaining time passes, namely, the remaining time solitary wave; both are commonly referred to as solitary wave traffic;

The signal mode is matched with the optimized signal of the traffic mode, and the optimized signal also comprises an orphan-flow direction-orphan temporary timing table and a set motorcade-flow direction-path intersection table, wherein the orphan temporary timing table comprises a forced orphan temporary timing table or/and a residual orphan temporary timing table;

S22, the predicted traffic information further comprises that the real-time actual measurement and prediction set traffic characteristic conditions comprise instruction solitary waves: including forced solitary waves, or/and time-lapse solitary waves; configuration calculation of a forced solitary wave temporary timing table: the set motorcade of the forced specified intersection flow direction phase and the direction phase or the diversion phase occupies the phase green light time of other motorcades of the front intersection, and the forced solitary wave temporary timing table is built according to the calculation; configuration calculation of a residual time solitary wave temporary timing table: designating the intersection flow direction phase to contain the direction phase or the diversion phase to set the vehicle team to occupy the relative phase of the front intersection, so that the vehicle team can pass the remaining green light time after providing the phase, and the temporary timing table of the remaining time solitary wave is built according to the calculation; the method for calculating the remaining time is called an A-A algorithm for short, and comprises the steps of using special information of the tail q of a directional phase diversion phase queue and a long vehicle queue of the flow direction traffic phase of each set intersection; the Yu Shi orphan is described in China patent 201710897777.6;

S32, the step of determining the matching of the optimized signal 1) predicted traffic mode and the signal mode further comprises the steps of receiving an instruction solitary wave, determining an intersection phase setting motorcade, and preliminarily judging the optimized signal of the solitary wave superimposed on the current signal mode, wherein the step of establishing a solitary wave temporary timing table for obtaining green light signals of a plurality of continuous intersections by using an solitary wave prediction algorithm; the step 2) or the priority rule also comprises the step of forcing the preliminary judgment of the solitary wave to be prior to the preliminary judgment of the solitary wave in the rest time, and the preliminary judgment of the solitary wave to be prior to other preliminary judgment;

s42, the performing optimization signal further includes: and executing the solitary wave temporary timing table.

S13, the superposition state signal also comprises a driving which is closest to one phase of the intersection under the characteristic condition of setting traffic information, namely a phase head driving, a green light signal is obtained by a red light, namely a differential green wave, and the differential green wave is superposed in the two-dimensional green wave; the driving refers to a vehicle which normally runs at a specified speed;

The signal mode parameters also comprise the minimum safe switching passing time between green light and red light between phases, which is called differential green wave time or delta t ^Th0 of phase change quantum time, and the two phases are involved; the minimum safe phase switching passing time refers to the minimum time for enabling the phase head vehicle to safely stop on a front parking line by normal braking when the control phase signal of the phase head vehicle is switched from a green light to a red light, and enabling other phase head vehicles to safely pass through a front intersection after the control phase signal of the phase head vehicle is switched from the red light to the green light; the distance between the phase head car and the front control phase, which is calculated according to the phase minimum safe switching passing time, is the phase minimum safe distance;

The set traffic information characteristic conditions comprise that the phase head vehicle q0 of each set intersection when flowing to a traffic phase red light is at or smaller than the phase minimum safety distance set by the phase, and the phase head vehicle q0 of the intersection ratio signal green light is outside the phase minimum safety distance or has no pedestrians with corresponding pedestrian phases, namely the ratio signal green light phase has no vehicle or no pedestrian, and is jointly called differential traffic of the red light traffic phase head vehicle at a differentiable position, and is also called differential green wave condition; or continuing the differential green wave condition under the following set sequence rule, when the green phase of the green time of the ratio signal is occupied, or the flow direction detects the presence of a car to other diversion phases, or other flow directions detect the presence of a car;

The optimized signal of the signal mode matching with the traffic mode also comprises differential green wave time and two phases thereof, and differential green wave conditions and two phases thereof;

s23, the predicted traffic information further comprises differential green wave conditions of the set traffic characteristic conditions which are actually measured in real time;

S33, the step of determining the matching of the optimized signal 1) and the signal mode further comprises the steps of according to the actual measurement to the differential green wave condition or the command differential green wave signal mode, for the red light phase head vehicle meeting the differential green wave condition in the current signal mode, performing preliminary judgment on the optimized signal matched with the differential time superimposed on the current signal mode, namely, enabling the red light phase head vehicle meeting the differential green wave condition in the current signal mode to obtain the phase change quantum time or the differential time of occupying one of the ratio signal green light phase no vehicle or no pedestrian phase; the 2) or the priority rule further comprises that the preliminary judgment of the differential green wave is superior to other preliminary judgment;

s43, performing the optimization signal further includes: switching or maintaining the green light to the phase at which the differential time is obtained immediately;

S101, the signal mode library comprises operations of adding modes or mode parameters, a new signal mode is set to provide services of setting traffic modes or serve the set traffic modes, the signal mode parameters are matched with the traffic modes served by the new signal mode, and the signal mode library is respectively configured into the signal mode library in S1, the traffic information is predicted in S2, the preliminary judgment priority rule for determining the optimized signal in S3, and the operation for executing the optimized signal in S4;

The intelligent traffic signal control architecture method comprises the following steps: the S2 predicted traffic information thereof is characterized by comprising,

S201, actually measuring or predicting road network traffic information and characteristics thereof include setting a plurality of attention points for assembling traffic sensing devices in a road network, setting positions in road sections or/and intersections, and acquiring traffic flow characteristic data or/and fleet characteristic data of the attention points for setting flow directions so as to analyze and express the road network traffic information characteristics;

S202, the traffic flow characteristic data of the traffic flow set by the attention point comprises a plurality of corresponding traffic flow set values or change set values thereof, or/and flow difference set values of the traffic flow set by the attention point, wherein the flow direction reaching the flow set values or the flow difference set values of the traffic flow set by the attention point is used as the main flow direction of the attention point; or the fleet characteristic data of the flow direction set by the attention point comprises a plurality of corresponding fleet length set values or change set values thereof; or/and the difference set value between the length of the set flow direction motorcade and the length of the road section where the set flow direction motorcade is located, the condition that the difference set value is reached is the set flow direction congestion road section of the concerned point;

the intelligent traffic signal control architecture method comprises the following steps: the S2 acquisition of predicted traffic information is characterized by comprising,

S203, configuring calculation processing units for predicting the point traffic information, namely attention point units for short, wherein each attention point unit predicts traffic information of an attention point set flow direction corresponding to a set prediction method; a plurality of the attention point units form a prediction layer; the prediction method refers to any method for predicting future data according to existing data, and comprises a repeated prediction method, an empirical method, a mean value method, a maximum value method, a statistical optimization method, an artificial intelligence method comprising a neural network method and an expert system method, wherein the repeated prediction method, the empirical method, the mean value method, the maximum value method and the statistical optimization method are directly used for predicting the future data by using real-time detection data.

S204, the traffic information prediction calculation processing unit for setting the flow direction of the attention point intersection, namely an intersection unit for short, wherein each intersection unit is used for predicting the traffic information characteristics of the flow direction phase diversion or relates to the traffic information characteristics and the set value of the traffic information prediction calculation processing unit comprising the vehicle source flowing to the upstream adjacent road section or the intersection unit flowing to the upstream.

The intelligent traffic signal control architecture method comprises the following steps: the S2 predictive traffic information is characterized by comprising

S205, the number, distribution, road segment or intersection type of the points of interest is determined by the flow direction distribution predicted by the set prediction method.

The intelligent traffic signal control architecture method comprises the following steps: the decision of S3 to optimize the signal is characterized in that it comprises,

S301, the preliminary judgment of the green wave optimizing signal comprises green wave flow direction optimization and green wave function optimization, and the steps comprise 1) determining the flow direction of a traffic mode: calculating the sum of the main flow of the attention point reaching the flow set value or/and the flow difference set value, namely the flow of the attention point main flow, wherein the flow with the large sum value is set as the road network traffic main flow, namely the traffic mode flow, the two road network traffic main flows which are intersected are the traffic mode double flow, the two-dimensional traffic-flow is marked, the one road network traffic main flow is the traffic mode single flow, the one-dimensional traffic-flow is marked, the traffic mode flow without the road network traffic main flow is the traffic mode flow, marking as zero-dimensional traffic-average direction; 2) Or with determining traffic pattern conditions: calculating the number of road sections with the length of the motorcade reaching the set value of the motorcade length or/and the length difference of the road sections reaching or smaller than the set value of the road section congestion, namely, the sum of the number of the road sections with the length of the motorcade reaching or/and the length difference of the road sections reaching or smaller than the set value of the road section congestion, wherein the direction with the large sum value is set as the main flow direction of road network traffic congestion, namely, the main flow direction of traffic mode congestion, when two crossed directions have more numbers of the road sections with the congested road sections and reach or exceed the set value of the flow direction, namely, the set value of the flow direction congestion, the two directions are two main flow directions of road network traffic congestion, namely, the two-dimensional traffic-flow direction congestion, when only one flow direction has more numbers of the flow sections with the congestion, and the number of the congestion road sections of the other flow direction is not the number of the congestion road sections of the flow direction, the flow direction is a main flow direction of the traffic jam of the road network, which is marked as one-dimensional traffic-flow direction-congestion, and when the number of the congestion road sections of the other flow direction is not the number of the congestion road sections of the flow direction reaches or exceeds the set value of the congestion road sections of the flow direction, the flow direction is the part of the congestion flow direction, including the congestion flow of a small area or the congestion flow directions of a plurality of road sections; the feature of combining with the traffic pattern flow comprises two-dimensional traffic-flow-movement, or/or with zero-dimensional traffic-all-way-movement, or/and with one-dimensional traffic-flow-movement, or/and with two-dimensional traffic-flow-congestion, or/and with one-dimensional traffic-flow-congestion, or/and with two-dimensional traffic-flow-mixing, or/and with one-dimensional traffic-flow-mixing, or/and with two-dimensional traffic-flow-movement, or/and with one-dimensional traffic-flow-movement; 3) Determining matched green wave optimization parameters and distribution thereof: the two-dimensional traffic-flow direction-motion matches the two-dimensional green wave-flow direction-guide, or/or matches the zero-dimensional traffic-all-direction-motion matches the zero-dimensional standing wave-all-direction-all-guide, or/or matches the one-dimensional traffic-flow direction-motion with the one-dimensional traffic-flow direction-one-dimensional green wave-flow direction-guide, or/or matches the two-dimensional traffic-flow direction-congestion with the two-dimensional traffic-flow direction-flow-block, or matches the one-dimensional traffic-flow direction-flow-congestion with the one-dimensional traffic-flow direction-flow-block, or/or matches the two-dimensional green wave-flow direction-mixture with the one-dimensional traffic-flow direction-flow-mixture, or/or the two-dimensional green wave-flow direction-guiding mixed part is dredged by matching partial congestion with the two-dimensional traffic-flow direction-movement mixed part, or/and the one-dimensional green wave-flow direction-guiding mixed part is dredged by matching partial congestion with the one-dimensional traffic-flow direction-movement mixed part; or the partial blocking with green wave-flow direction-guiding mixing part comprises partial blocking and solitary wave blocking, wherein the partial blocking refers to the partial blocking as a district road network is configured into a corresponding road network blocking signal mode, the two-dimensional green wave-flow direction blocking and one-dimensional green wave-flow direction blocking are also included, the solitary wave blocking refers to the solitary wave blocking of a vehicle team of a blocked road section by using the solitary wave technology, the solitary wave blocking also includes residual time solitary waves, and command solitary waves;

Or/and directly carrying out green wave optimization signal prediction preliminary judgment by using the prediction method: the predicted target data comprise specified traffic characteristic data, the signal parameters of the traffic are adjusted and optimized by the prediction method, and the optimized signal preliminary judgment of the signal parameters of the traffic characteristic data meeting the prediction target is optimized according to the specified traffic characteristic data and the green wave parameter data set, which is called a direct optimized signal prediction method;

S302, preliminary judgment of the periodic optimization signal or preliminary judgment of phase timing optimization is carried out, and the method further comprises the steps of carrying out prediction optimization by using any intersection signal timing algorithm, a Webster timing method, a conflict point method, an estimation method, a critical lane method and a prediction method related to the periodic phase timing optimization signal, which is called a periodic phase timing optimization signal prediction method;

S303, the prediction method further comprises a direct optimized signal prediction method and a periodic phase timing optimized signal prediction method, wherein a new change relation between traffic information characteristic data acquired by traffic information attention points of a road network and corresponding optimized signal parameter data is found through an optimized signal learning method aiming at minimizing vehicle waiting time or/and minimizing vehicle waiting length, the new change relation is created as a new optimized signal, and the new optimized signal is added into a signal mode library;

The intelligent traffic signal control architecture method comprises the following steps: the S3 decision optimizing signal is characterized by comprising

S304, the priority rule decides the priority order of the preliminary judgment of each optimized signal according to the data order including the calculation, prediction/estimation of the reduction of the waiting time of the running of the vehicle, the reduction of the vehicle team and the increase of the flow caused by the preliminary judgment of each optimized signal;

The intelligent traffic signal control architecture method comprises the following steps: the S31 decision optimizing signal is characterized by comprising

S305, the priority rule ranks the former in preference to the latter according to the size of the estimated data: the method comprises the steps of performing a command signal mode, performing preliminary judgment with two-dimensional green wave-flow direction-blocking, performing preliminary judgment with one-dimensional green wave-flow direction-mixing, performing preliminary judgment with two-dimensional green wave-flow direction-opposite guiding, performing preliminary judgment with one-dimensional green wave-flow direction-opposite guiding, performing preliminary judgment with two-dimensional green wave-flow direction-guiding, performing preliminary judgment with one-dimensional green wave-flow direction-guiding, and performing standing wave-uniform direction-balanced;

the intelligent traffic signal control architecture method comprises the following steps: it is characterized in that the forced solitary wave temporary timing comprises,

F201, calculating the time required by passing through the local intersection according to the length of the island wave motorcade obtained by prediction, and the time is used for forcing island waves for short; subtracting the forced solitary wave from the green time of the local phase to obtain a number smaller than 0, and using the time of other phases by corresponding amounts;

Predicting the signal lamp color of the related phase of the front intersection according to the length of the forced solitary wave motorcade and the predicted time reaching the front intersection, subtracting the residual green time after a set time from the green time of the same closing phase of the front intersection, subtracting the forced solitary wave time to obtain the residual green time, and if the absolute value is less than 0, predicting the time of borrowing the corresponding quantity of other phases; wherein the set time is when the phase fleet is assumed to pass;

Setting a plurality of continuous intersections by predictive calculation; making temporary timing tables of the intersections;

The invention has the following advantages: 1) The control architecture of the series prediction traffic mode on the special superposition signal optimization signal library is constructed on the human-machine capability boundary, namely, the artificial intelligence is accurately used in the situation that the human capability is disabled and the human capability is enabled and the situation is disabled, the driving waiting can be greatly reduced by more than 30%, the signal mode and the control architecture cannot be created by the existing artificial intelligence algorithm, and the signal mode and the control architecture cannot be created as if the artificial intelligence cannot find the creation law F=MA, E=MC ² and Maxwell equation set; 2) The structure is provided with a signal mode optimized through intelligent learning expansion; 3) The broad-spectrum traffic flow load control and the broad-spectrum traffic flow direction load control are unified under a signal mode control architecture, so that the efficient control and the efficient response of the traffic flow direction double broad-spectrum loads are realized; 4) The analysis and control traffic pattern distribution and the arrangement of the set attention points are properly and repeatedly applied to generate a plurality of combined optimized control schemes; 5) The control road network is properly selected to set the attention point and set the predicted traffic information characteristics, so that the equipment cost and the running cost can be saved, and the running efficiency can be improved; 6) When all the intersections of the road network are selected as the set attention points and the motorcades are selected as the set traffic information characteristics, the highest control efficiency and control precision can be obtained.

Drawings

FIG. 1 is a flow chart of a traffic signal control architecture method;

FIG. 2 is a graph of 2 set point of interest segments and traffic data versus flow;

FIG. 3 is a block diagram of a road network traffic signal control architecture "predictive decision" for 2 set point of interest segments;

FIG. 4 is a plot of a set point of interest intersection with traffic characteristics versus flow or fleet length;

FIG. 5 is a block diagram of a road network traffic signal control architecture "predictive decision" for a set point of interest intersection of a cell;

Numbered indices in the accompanying drawings:

Fig. 2: 1-the network intersection node code mark starting point (0, 0) is the left lower corner intersection of the road network, the marks { (0, 0), (6, 4) } represent that the origin is (0, 0), the maximum value (6, 4) of the longitudinal and transverse coordinates (i, j) is respectively 6,4, each coordinate (i, j) is an intersection of two roads, 7 roads and 5 roads intersected with the intersection are intersected, and 35 intersections are intersected; 2-2 points of interest, represented by diamond and letter d# flowing along the paragraph, respectively having D1, D2, distributed in 2 different road segments, cross road segments (3, 3), longitudinal road segments (4, 3), the points of interest being equipped with bidirectional traffic information flow collection device and point of interest unit, each road segment point of interest being marked around a group of "east" and "west" or "south" and "north" directions and 2 numbers each drawn out and separated by double brackets ", indicating the direction" actual measured flow ", i.e." south 8- "indicating the actual measured flow of the south flow of the road segment is 8, the predicted flow 8, the direction of the direction being consistent with the traffic flow, the unit being vehicle-vehicle number; 3- -intersection spacing- -driving/congestion team start-up is noted as #/#: units: meter-second/second; note 1: the left upper corner crossing (0, 4) is a virtual crossing, represented by a small dotted square, and the connected road segments (0, 4) are virtual road segments, represented by dotted lines; and (2) injection: triangle marks of the left lower corner crossing (0, 0) of the road network indicate that the crossing is a mode phase difference base point crossing of the current superposition state signal, and two hollow solid arrows point to the current signal green wave flow direction, east and north; and (3) injection: the dashed triangle labels of the upper right corner intersections (6, 4) of the road network represent the mode phase difference base point intersections where the intersection is to be configured to optimize the superimposed signal, and the two open dashed arrows point to the optimized signal green wave flow direction, west and south; general description of drawings in the following figures, unless otherwise stated defined;

Fig. 3: 1-a signal pattern library; 2-setting a attention point road section unit and a traffic information data receiving and predicting module, wherein 2 attention point road section units form a predicting layer, 3-hollow arrows represent layers and layers, the modules are in data connection with each other, the arrows refer to the predicting layer and the analyzing layer, the single-flow direction optimizing signal initial judging unit or the function optimizing signal in the 4-analyzing layer, the arrow refer to the north-flow direction optimizing signal initial judging unit, the double-flow direction optimizing signal initial judging unit or the function optimizing signal in the 5-analyzing layer, the arrow refer to the east-flow direction and north-flow direction optimizing signal initial judging unit, the period and green signal ratio optimizing signal initial judging in the 6-analyzing layer and the signal optimizing decision in the 7-decision layer; the following focus pre-decision structure is marked by a general graph except for the definition of the statement; fig. 4: a set point of interest intersection (3, 1) of one of 2-12 set point of interest intersection cells, indicated by arrows, represented by octagons, the point of interest being equipped with an intersection traffic flow direction phase traffic information flow acquisition device, or a split phase traffic information flow acquisition device, or a fleet head and tail information acquisition device, the "east", "west", "south", "north" azimuth labels around the intersection and 8 numbers # separated by double brackets "# -/#/#/#") each drawn around the intersection representing the azimuth flow and straight#/, left#/, right#, three-phase actual measurements waiting for the length of the fleet passing through the intersection and predicted correlation values, if "north 3-0/0/0" 8-7/0/0 "indicates that the measured flow of the north waiting south line of the intersection is 1, the straight-going phase of the vehicle team is 1, the left turn is 0, the right turn is 0, the predicted flow is 8, the vehicle length is 7/0/0, the azimuth direction is opposite to the traffic flow direction, the unit is the vehicle number, the corresponding seconds of the vehicle length q are converted into meter length by using the standard vehicle length of 6.25 meters and then converted into seconds by using the team scrambling time tqx = (1/v0+a) ×q, the speed of v0 green wave is 12.5 meter seconds, and alpha=0.18 and tqx =0.26 are calculated, for example, 20 meters corresponds to 3 vehicles of 5 seconds; note 1: western black arrows on the crossroad sections (2, 4) and crossroad sections (2, 5) represent western congestion fleets and their captchaetors; and (2) injection: the dotted line inverted triangle in the intersection (3, 2) represents that the intersection is a mode phase difference base point of east flow dredging green waves;

Fig. 5: 2-a traffic information data receiving and predicting module of the intersection unit with the set attention point, wherein 12 intersection unit predicting modules form a predicting layer, and the arrow indicates the intersection unit predicting module with the set attention point (5, 3); 8, primarily judging an solitary wave optimizing signal in an analysis layer, and 9-determining an solitary wave management module in a layer; the method comprises the steps of 10, primarily judging differential green wave optimization signals in an analysis layer, and 11, solving solitary wave conflict in a decision layer;

Detailed Description

3 Embodiments of the present invention will be described in detail with reference to the accompanying drawings:

Example 1, see figures 1 and 2,

E1-S11, acquiring road network parameters including the length of each road section in the road network and the traffic time of each road section, wherein the road network parameters are shown as a mark 3 in FIG. 2; the traffic time comprises the time of starting a congestion vehicle team of a road section; the time for driving refers to the time for the vehicle to run at the set speed to finish a road section, and is equal to the length of the road section divided by the set driving speed or comprises the time for subtracting the braking of the set driving speed; the road network topology comprises a virtual intersection and a virtual road section, wherein the virtual intersection comprises an approximate quasi-parallelogram; creating a plurality of superimposed signal modes for road network traffic shown in fig. 2 to form a signal mode library, wherein each signal mode provides control service of a traffic mode corresponding to the mode, and an optimized signal is formed by matching the signal modes; the current running signal mode and parameters thereof are acquired or configured, namely the current signal and parameters thereof, wherein the current signal comprises a signal period of 68 seconds, and the phase timing of each intersection is as follows: the phase timing ratio of the north-south flow direction to the east-west flow direction is 1:1, 34 seconds each, and the phase timing ratio of the flow direction with the split straight left row is 2:1, 22 seconds each and 12 seconds each;

The current signals are marked as shown in fig. 2, two-dimensional green wave-east and north-guidance is carried out, the mode phase difference base point crossing is at the left lower corner crossing (0, 0) of the road network, 2 cross flow directions are east and north, and the mode period remainder and period complement of each crossing are shown as table 1:

Table 1 current signal two-dimensional green wave-east and north-directed intersection pattern period remainder and period complement, period = 68 seconds

4	42＞42/26	52＞52/16	60＞60/18	72＞4/64	82＞14/54	90＞22/46	102＞34/34
3	30＞30/38	40＞40/28	48＞48/20	60＞60/8	70＞2/66	78＞10/58	90＞22/46
2	20＞20/48	30＞30/38	38＞38/30	50＞50/18	60＞60/8	68＞0/68	80＞12/56
1	12＞12/56	22＞22/46	30＞30/38	42＞42/26	52＞52/16	60＞60/8	72＞4/64
0	0＞0/68	10＞10/58	18＞18/50	30＞30/38	40＞40/28	48＞48/20	60＞60/8
i/j	0	1	2	3	4	5	6

Absolute phase difference # of each intersection mode and period remainder > # period complement/#, as shown in '# > #/#' in table 1;

the signal mode comprises any signal for setting the green light propagation flow direction among the phases of the intersections, which is called a green wave; the characteristic parameter of the flow direction as a signal mode green wave is called a green wave flow direction, and the mode is called a green wave-flow direction; the set green wave flow direction is used for calculating and configuring phase differences of related phases of other intersections according to the phase time of the most upstream intersection called a mode phase difference base point or a green wave source point, and the phase differences are called mode absolute phase differences; the phase time difference between two adjacent intersections is a relative phase difference and is equal to the traffic time set by the road section between the adjacent intersections; the signal mode without phase difference among ratio signals running among all intersections is standing wave, green light change is not transmitted, namely, the ratio mode and the green wave degradation mode are adopted, and the control service function of equal traffic characteristics of all flow directions is provided; the ratio signal finger port configures each phase time length according to the set period and the set ratio; the green wave characteristic parameters also comprise green wave functions, including guiding or balancing or/and dredging or/and mixing or/and convection guiding, namely guiding in opposite directions, wherein guiding means that when the green wave flow direction is the same as the controlled traffic flow direction, the relative phase difference is calculated by adopting the setting of driving when the road sections are used for traffic; equalization means that green light signals have no flow direction, and 0 phase difference of each intersection is synchronous; the green wave flow direction is opposite to the controlled traffic flow direction, and the relative phase difference is calculated when the traffic on each road section is started by adopting a set congestion vehicle team; mixing means when the green wave flow direction and the controlled traffic flow direction comprise the same part and the opposite part, when the road sections of the same flow direction part are used for driving and the road sections of the opposite flow direction part are used for starting by a congestion vehicle team; the guiding of traffic in two opposite directions is one of guiding; the green wave signals are respectively marked as green wave-flow direction-guiding, green wave-flow direction-dredging, green wave-flow direction-mixing and standing wave-uniform direction-balancing; the parameters of the signal mode also comprise periods, and each phase is distributed for a long time, namely phase timing; the phase includes a direction phase representing a control direction of the intersection, or a shunt phase controlling left/right steering among the direction phases; the present embodiment does not include a unblocking function because no fleet length sensing system is configured;

The superimposed signal refers to a green wave signal running in 2 or more cross flow directions within a set period (including a plurality of n > =1 signal periods c), that is, any two-dimensional green wave signal based on two cross flow directions, and any dimension-reducing form thereof; when the phase difference of one of the two-dimensional green waves flowing to the green wave is configured to be 0, the dimension of the one-dimensional green wave is reduced to be one-dimensional green wave, and similarly, the dimension of the one-dimensional green wave is reduced to be zero-dimensional standing wave; the green wave flow direction also comprises two crossed flow directions, the green wave is called a two-dimensional green wave, or is marked as a green wave-double flow direction or a two-dimensional green wave-flow direction, and the dimension reduction form comprises a one-dimensional green wave-flow direction and a 0-dimensional standing wave-uniform direction; the green wave signal comprises two-dimensional green wave-flow direction-guide, one-dimensional green wave-flow direction-guide, 0-dimensional standing wave-uniform direction-equalization or two-dimensional green wave-flow direction-opposite guide and one-dimensional green wave-flow direction-opposite guide; in this embodiment, the two-dimensional green wave-flow direction, wherein the flow direction comprises east and north or north and east, east and south or south and east, west and north or north and west, west and south or south and west, wherein the flow direction comprises east, south, west, north, and zero-dimensional standing wave-both directions; the two-dimensional green wave flow direction is combined with the green wave function, and in this embodiment, the two-dimensional green wave flow direction is guided, or the two-dimensional green wave flow direction is guided, the one-dimensional green wave flow direction is guided, and the zero-dimensional standing wave is guided under the signal mode column of the signal mode library in table 2, as shown by mode numbers 4 to 8: the serial number is also used as a priority number, a smaller number is prioritized over a larger number, and serial numbers 2 and 3 are not listed in the column;

Table 2 example 1 table of signal pattern and traffic pattern matches in signal pattern library

Note [1]: the opposite guidance needs to meet the set road network structure requirement and the set value thereof;

Setting the intersection point at the most upstream of the 2 cross flow directions as the mode phase difference base point intersection, namely a two-dimensional green wave base point intersection, and vice versa, wherein the position of one two-dimensional green wave base point intersection also determines the 2 cross flow direction parameters; setting the position of a mode phase difference base point intersection of one-dimensional green waves at an intersection on the same intersection non-green wave flow direction of the most upstream of each green wave channel, namely a one-dimensional green wave base point intersection; any intersection can be set at the intersection of the phase difference base point of the zero-dimensional standing wave mode;

The traffic mode parameters comprise flow direction, or/and state, or/and flow, or/and phase shunt quantity of each phase of the crossing; wherein the traffic pattern flow direction comprises two main directions intersecting, the traffic pattern is called two-dimensional traffic, or is denoted traffic-double flow direction or two-dimensional traffic-flow direction, the dimension reduction form comprises one main flow direction which is one-dimensional traffic-flow direction and 0-dimensional traffic-both direction, the two-dimensional traffic-flow direction comprises east and north or north and east, east and south or south and east, west and north or north and west, west and south or south and west, the degradation form comprises one main flow direction which is characterized by one-dimensional traffic-flow direction comprising east, south, west, north and 0-dimensional both direction; the traffic conditions of the embodiment do not comprise congestion, and the traffic mode conditions comprise movement, namely non-congestion; congestion refers to the condition of a fleet that the length of a road segment minus the length of the fleet reaches or is less than a set value, or the congestion coefficient reaches or exceeds a set value, which is simply referred to as a road segment congestion set value; the traffic pattern flow direction or the traffic pattern combined with the traffic pattern condition of the embodiment comprises two-dimensional traffic-flow direction-movement, one-dimensional traffic-flow direction-movement, zero-dimensional traffic-all-direction-movement, or two-dimensional traffic-flow direction-convection, or one-dimensional traffic-flow direction-convection, which are shown by pattern numbers 4 to 8 under the condition that the signal pattern library is matched with the traffic pattern column in the table 2;

The signal mode and traffic mode matching means the matching of all corresponding parameters, and the signal mode and traffic mode matching means the matching of all corresponding parameters, including a green wave flow direction optimizing signal for matching the signal mode flow direction with the traffic mode flow direction; a green wave optimizing signal combined with the green wave function optimizing signal matched with the traffic pattern condition, in this embodiment, under the signal pattern library signal pattern column and the matched traffic pattern column in table 2, as shown by pattern sequence numbers 4 to 8, two-dimensional green wave-flow direction-guide is matched with two-dimensional traffic-flow direction-motion, one-dimensional green wave-flow direction-guide is matched with one-dimensional traffic-flow direction-motion, zero-dimensional standing wave-uniform direction-equalization is matched with zero-dimensional traffic-uniform direction-motion, or is matched with two-dimensional green wave-flow direction-pair guide is matched with two-dimensional traffic-flow direction-convection, or is matched with one-dimensional green wave-flow direction-pair guide is matched with one-dimensional traffic-flow direction-convection; or/and a period optimization signal matched with the signal mode period and the traffic mode flow; or/and phase timing optimization signals matched with traffic phase diversion characteristics when the signal mode phase timing is matched with the traffic phase diversion characteristics;

E1-S21, predicting traffic information:

E1-S201-S205, selecting a road network attention point: predicting the long-term easy occurrence of peak flow in four directions of the longitudinal and transverse directions of the road network of the figure 2 and the positions of the road network in the transverse road segments (3, 3) and the longitudinal road segments (4, 3) according to flow distribution and past experience data, determining the two road segments as the midpoint positions of attention point road segments in the road network, configuring a bidirectional traffic flow sensor at the set positions, and acquiring the traffic flow of 4 flow directions of east, west, south and north by using road coils or vehicle positioning data so as to express the traffic information and the characteristics of the road network; s203, a traffic information prediction calculation processing unit, namely a road section unit for short, configured at the road section position of the attention point predicts each traffic flow direction and traffic flow of the attention point by using a repeated prediction method; s202, determining traffic flow characteristics, wherein the absolute value of the difference between the traffic flow of the set flow direction of the road section unit and the traffic flow of the opposite flow reaches or exceeds a set value of 2, and the flow direction of the larger flow is a main flow direction of a concerned point of the concerned point; in this embodiment, at most one focus may have a focus main flow direction; calculating the periodic phase timing of the reconfiguration signal mode by using a Weber intersection signal timing method according to the selected peak flow or/and the predicted peak flow of the set attention point road section, wherein the period is 68 seconds, the direction phase ratio is 34 seconds to 34 seconds, and the shunt phase is directly rotated left for 22 seconds to 12 seconds;

According to the configured attention points, the traffic sensor and the traffic data set by the traffic sensor are predicted by a set prediction method to obtain: in fig. 2, the absolute value of the south-north flow difference of the attention point D2 is larger than the set difference value 2 from |8-2|=6 of the previous period, the south flow direction is the main flow direction of the attention point, the unit is the number of vehicles-vehicles, the prediction remains the same as before, the south flow direction is continuously set as the main flow direction of the attention point, no other flow direction is the main flow direction of the attention point, the predicted main flow direction and flow information of the attention point D2 are respectively sent to a single flow direction-south-optimizing signal initial judging unit, a double flow direction-south and west-optimizing signal initial judging unit, a double flow direction-south and east-optimizing signal initial judging unit of green wave optimization in an analysis layer, and a single flow direction optimizing signal initial judging unit and a double flow direction optimizing signal initial judging unit of 3-5 shown as 3-4 in fig. 3; the absolute value of the east-west flow difference of the attention point D1 is larger than a set difference value of 2 from |1-9|=8 of a previous period, the west flow direction is the main flow direction of the attention point, prediction remains the same as before, the west flow direction is continuously set to be the main flow direction of the attention point, no other flow direction is the main flow direction of the attention point, and the predicted main flow direction and flow information of the attention point D2 are respectively sent to a green wave optimized single flow direction-west-optimized signal preliminary judgment, a double flow direction-south and west-optimized signal preliminary judgment, a double flow direction-west and north-optimized signal preliminary judgment in an analysis layer;

E1-S31, determining an optimization signal: 1) According to the traffic mode obtained by receiving the command signal mode or analyzing the predicted traffic information, the preliminary judgment of matching the corresponding superposition signal mode from the signal mode library to form the optimized signal further comprises: 1.1 The green wave optimizing signal preliminary judging step comprises the following steps: 1.1.1 Determining traffic pattern flow direction: calculating the sum of the main flow of the attention point in each same flow direction reaching a flow set value or/and the flow difference set value, namely the flow of the attention point main flow, wherein the flow with a large sum value is set as a road network traffic main flow, namely a traffic mode flow, the two road network traffic main flows which are intersected are two traffic mode flow directions, the traffic flow direction is marked as a two-dimensional traffic flow direction, the traffic mode flow direction is marked as a one-dimensional traffic flow direction, the traffic mode flow direction is marked as a zero-dimensional traffic flow direction, and the traffic mode flow direction is marked as a non-road network traffic flow direction; in this embodiment, according to the calculation that the sum of the flows of all the southbound flow differences reaching the set value 2 is the predicted value 8 of the flow of the attention point longitudinal section (4, 3) and the sum of the flows of all the western flow differences reaching the set value 2 is the predicted value 9 of the flow of the attention point transverse section (3, 3), two main road network traffic flows are obtained, and southbound and western are used as the predicted traffic mode double flows, namely two-dimensional traffic-southbound and western; other road network traffic flow characteristics can be predicted according to other traffic information data, wherein the traffic flow characteristics comprise two-dimensional traffic-other flow, zero-dimensional traffic-uniform flow and one-dimensional traffic-other flow; 1.1.2 In this embodiment, no vehicle length sensing device and data thereof are used, and no condition congestion and default condition movement are concerned, so that the combination characteristic of road network traffic flow direction and condition prediction in this embodiment is two-dimensional traffic-south and west-movement; other road network traffic flow direction and condition combination characteristics can be predicted, including two-dimensional traffic-other set flow direction-movement, one-dimensional traffic-other flow direction-movement, and zero-dimensional traffic-homography-movement; 1.1.3 Determining matched green wave optimized signal parameters: in this embodiment, two-dimensional traffic-south and west-motion matches two-dimensional green wave-south and west-guidance; the focus configuration of this embodiment may also determine that the matched green wave optimization signal includes two-dimensional traffic-other set flow direction-motion matching two-dimensional green wave-corresponding to other flow direction-guide, one-dimensional traffic-flow direction-motion matching one-dimensional green wave-corresponding to flow direction-guide, zero-dimensional traffic-uniform direction-motion matching zero-dimensional standing wave-uniform direction-balance; or matching the two-dimensional traffic-flow-convection with the two-dimensional green wave-corresponding flow-convection; or one-dimensional green wave-corresponding flow direction-opposite direction is matched with one-dimensional traffic-flow direction-opposite flow; 1.2 Primary judgment of the period optimization signal and primary judgment of the phase timing optimization signal; the traffic mode flow or/and the characteristic parameters of the length of the vehicle are a plurality of set values or a change set value thereof, and the period of the superimposed signal mode for predicting and matching the corresponding flow is optimized for a plurality of periods corresponding to the plurality of set values; the traffic pattern phase flow or/and the length of the characteristic car length is a plurality of set values or a set value is changed with the characteristic car length, predicting the phase timing of the superposition signal mode matched with the corresponding phase flow to be a plurality of optimized phase timing corresponding to the plurality of set values, wherein the prediction matching or the periodic phase timing optimized signal prediction method is used;

2) Or determining an optimization signal from said preliminary decisions according to a priority order, ordered in preference to the former in preference to the latter: a command signal mode, a two-dimensional green wave-flow direction-guiding preliminary judgment, a one-dimensional green wave-flow direction-guiding step judgment, or a one-dimensional green wave-flow direction-guiding preliminary judgment, or a one-dimensional green wave-flow direction-guiding step judgment, or a periodic optimization signal preliminary judgment and/or a phase timing optimization signal preliminary judgment, a standing wave optimization signal preliminary judgment, wherein the or and optimization signal preliminary judgment only refers to the or and preliminary judgment, and the preliminary judgment listed later is not involved; in this embodiment, only one traffic pattern is predicted, and an optimization signal is generated; the determined optimization signal: two-dimensional green wave-south and west-guide;

3) And (3) making corresponding mode transition periods according to the determined optimized signals and the current signals: the determined optimization signal:

Two-dimensional green wave-south and west-guidance and current signals, two-dimensional green wave-north and east-guidance, and corresponding mode transition periods of the two are manufactured, 3.0) the current signal period 68 seconds is an optimization period 68 seconds before each intersection is kept; 3.1 Calculating the transition time length of the two signal modes of each intersection: 3.1.1 Optimized signal pattern period remainder calculation: the mode phase difference base points of the two-dimensional green wave-south and west-guidance are selected at the intersection (6, 4) which is the most upstream intersection of the two-dimensional traffic flow direction and is marked by a dotted triangle at the upper right corner in fig. 2, the green wave flow direction is selected as the mode main flow direction, the green wave flow direction south passing through the mode phase difference base point intersection (6, 4) becomes the mode auxiliary flow direction, the north-south channels become the channel phase difference base points of all the mode main flow direction channels, and the optimized signal mode absolute phase difference and the period remainder of each intersection are shown in the following table 3: in the table, # > # represents the absolute phase difference '#' of the signal pattern and the periodic remainder '> #' thereof, and the following symbols are synonymous;

table 3 optimizing signal two-dimensional green wave-south and west-guided intersection mode absolute phase difference and period remainder, period = 68 seconds

4	60＞60	50＞50	42＞42	30＞30	20＞20	12＞12	0＞0
3	72＞4	62＞62	54＞54	42＞42	32＞32	24＞24	12＞12
2	82＞14	72＞4	64＞64	52＞52	42＞42	34＞34	22＞22
1	90＞22	80＞12	72＞4	60＞60	50＞50	42＞42	30＞30
0	102＞34	92＞24	84＞16	72＞4	62＞62	54＞54	42＞42
i/j	0	1	2	3	4	5	6

3.1.2 Current signal pattern period complement calculation: two-dimensional green wave-north and east-guidance, the mode phase difference base point crossing is shown as the left lower corner crossing (0, 0) of the road network in fig. 2, the period complement of the absolute phase difference period remainder of the current signal mode of each crossing is shown as the '/#' value of # > #/# in the table 1, and the current period = 68 seconds;

3.1.3 Calculating the mode transition period: the mode transition duration of each intersection is equal to the period remainder of the absolute phase difference of the optimized signal mode of each intersection plus the period complement of the period remainder of the absolute phase difference of the current signal mode of each intersection, and the period remainder of the sum is taken to obtain the mode transition duration of each intersection as shown in the following table 4: in the table/# > # represents the period complement '/#' of the previous current signal pattern absolute phase difference period remainder plus the period remainder '> #' of the optimized signal pattern absolute phase difference, period = 68 seconds,

Table 4 calculation of transition time length of each intersection mode, period=68 seconds;

3.2 A mode transition period corresponding to the mode transition period of each intersection is manufactured: dividing the mode transition period into the sum of two flow direction phase periods, or with subdividing each flow direction into the sum of the shunt phase periods, as shown in table 5 below (shunt phase periods not labeled):

table 5 period = 68 seconds at each intersection mode transition phase timing

4	＞18＝9+9	＞66＝33+33	＞60＝30+30	＞26＝13+13	> 6 = Red light	＞58＝29+29	＞34＝17+17
3	＞42＝21+21	＞22＝11+11	> 6 = Red light	＞50＝25+25	＞30＝15+15	> 14 = Red light	＞58＝29+29
2	＞62＝31+31	＞42＝21+21	＞26＝13+13	> 2 = Red light	＞50＝25+25	＞34＝17+17	> 10 = Red light
1	> 10 = Red light	＞58＝29+29	＞42＝21+21	＞18＝9+9	＞66＝33+33	＞50＝25+25	＞26＝13+13
0	＞34＝17+17	> 14 = Red light	＞66＝33+33	＞42＝21+21	＞22＝11+11	> 6 = Red light	＞50＝25+25
i/j	0	1	2	3	4	5	6

In the table, the pattern transition time length '> #' is formed by adding the phase 1 time length# and the phase 2 time length#;

E1-S41, performing an optimization signal: mode transition period control: firstly, running a mode transition period, and then running a new periodic signal;

example 2, referring to FIG. 4, updating and adding on the basis of the parameters, structures and methods of example 1 includes

E2-S11, acquiring road network parameters including the length of each road section in the road network and the traffic time of each road section, as shown by a mark 3 in fig. 4; the traffic time also comprises the time of starting a congestion vehicle team of a road section; the time taken by the congestion fleet to drive from the head-of-fleet to the tail-of-fleet to the place is equal to the length of the road section of the fleet starting coefficient, wherein the range of the congestion coefficient is a number less than or equal to 1, and the congestion coefficient is a number less than or equal to 1, or the congestion coefficient is calculated according to the experimental value range of 0.10 to 0.26, or the unit is 0.18: seconds/meter;

The signal mode function also comprises dredging, mixing and dredging of a mixed part; the mixing means that one flow direction green wave is guided and the other flow direction green wave is dredged; the mixed partial blocking is used for guiding one flow to the green wave and guiding the other flow to the green wave to perform partial road section blocking or solitary wave, and is especially used for two-dimensional green wave-flow to-mixed partial blocking below, or used for guiding one flow to the green wave to perform partial road section blocking or solitary wave and is especially used for one-dimensional green wave-flow to-mixed or partially blocking below; the signal modes of the green wave flow direction or the combination of the green wave functions are shown in the signal mode columns of the signal mode library in the table 6, and as shown in the mode serial numbers 4 to 17, the signal modes comprise two-dimensional green wave-flow direction-blocking, two-dimensional green wave-flow direction-mixing part blocking, one-dimensional green wave-flow direction-blocking and one-dimensional green wave-flow direction-mixing;

The traffic mode conditions also comprise congestion, mixing, and mixing partial congestion; the mixing refers to the situation that one flow direction is congested and the other flow direction is not congested, namely movement; the mixed partial congestion refers to that one flow direction traffic condition moves and the other flow direction traffic condition is partial road section movement and partial road section congestion; the traffic flow direction or the combination of the traffic flow direction and the traffic condition is included in the signal pattern list of the signal pattern library in the table 6, and the signal pattern list is shown as pattern serial numbers 4 to 17, and the signal pattern list comprises two-dimensional traffic-flow direction-congestion, two-dimensional traffic-flow direction-mixing and partial congestion; the degradation comprises one-dimensional traffic-flow direction-congestion, one-dimensional traffic-flow direction-mixing and one-dimensional traffic-flow direction-mixing containing partial congestion; parameters and values listed in the traffic pattern as in table 6:

The signal mode green wave function and traffic mode condition matching function optimization signal also comprises a green wave function, traffic mode condition jam matching, green wave function, traffic mode condition mixing, traffic mode jam matching; the optimized signal of matching the green wave mode with the traffic mode further comprises a combination optimization of matching the two-dimensional green wave flow direction and the functional combination with the two-dimensional traffic flow direction and the condition combination, and in the embodiment, the signal mode library signal mode column and the matched traffic mode column in the table 6 comprise two-dimensional green wave-flow direction-dredging and two-dimensional traffic-flow direction-congestion matching, two-dimensional green wave-flow direction-mixing and two-dimensional traffic-flow direction-mixing matching, and two-dimensional green wave-flow direction-mixing partial dredging and two-dimensional traffic-flow direction-mixing contain partial congestion as shown by mode serial numbers 4 to 17; one-dimensional green wave-flow direction-dredging and one-dimensional traffic-flow direction-congestion matching, one-dimensional green wave-flow direction-mixing and one-dimensional traffic-flow direction-mixing matching; the one-dimensional green wave-flow direction-mixed partial dredging is matched with the one-dimensional traffic-flow direction-mixed partial congestion;

TABLE 6 example 2 Signal Pattern and traffic Pattern matching Table in Signal Pattern library

Note [2]: green wave parameter fluctuations in parentheses will be used and described in "signal pattern library update" example 3;

the remainder and the complement of the absolute phase difference period of the mode of the two-dimensional green wave-east and north-leading mode of the current signal of the present embodiment are shown in table 1 in embodiment 1;

E2-S21, predicting traffic information:

S201, selecting a road network attention point: according to the distribution of the flow and the fleet and past experience data, as the peak flow and the peak fleet captain frequently appear in 12 crossing cells { (2, 1), (5, 3) } in the road network of fig. 4, determining to set the 12 crossing cells as the crossing cells of interest, wherein each crossing in the region is configured with an incoming direction traffic flow representation reaching flow sensor and a fleet sensor at a set position, and acquiring the traffic flow of incoming vehicle flows in the east-west 4 directions of the crossing and the head-of-fleet and tail-of-fleet captain information to express the traffic information characteristics of the road network; s203, the traffic information prediction calculation processing unit of the attention point crossing, which is called an intersection unit for short, predicts the traffic flow and the length of a vehicle queue of each traffic flow of the attention point crossing by using a three-layer BP neural network taking a wavelet function as an excitation function, namely a wavelet neural network prediction method and traffic data of 25 signal periods; the traffic flow direction characteristic judging rule is that the difference value between the traffic flow of the set flow direction of the intersection unit and the traffic flow of the opposite flow reaches or exceeds a set value 2, the flow direction of the larger flow is a main flow direction of a concerned point of the concerned point, and in the embodiment, at most, two main flow directions of the concerned point can be provided for one concerned point; the traffic condition feature judging rule is that the difference between the length of the road section and the team leader of the vehicle in the set flow direction of the intersection unit reaches or is smaller than a set value 2, the flow direction of the larger flow is a main flow direction condition of one attention point of the attention point, and in the embodiment, the main flow direction condition of the attention point can be at most two;

According to the configured attention points, the sensors and the traffic data set by the sensors are predicted by a set prediction method to obtain: the predicted traffic characteristic data of 12 points of interest in fig. 4, as shown in table 7, are the flow rates of the east and west directions of each point of interest and their differences, the fleet length of the east and west directions of each point of interest and their directions that meet or exceed the main flow direction set point; the main flow direction and flow condition information of the predicted attention points are respectively sent to a single flow direction-east/west/south/north-optimizing signal initial judging unit of green wave optimization in an analysis layer, and a double flow direction-east and south/south and west and north/north and east-optimizing signal initial judging unit;

Table 7 predicted traffic information characteristic data for 12 points of interest intersections in cell

Note that: in the table, F represents flow characteristics, Q represents fleet characteristics: the # - = # main flow// # - = # main flow represents the difference #, obtained by subtracting east flow (i.e., intersection west direction) data # from traffic information west flow (i.e., intersection east direction) data # and @ main flow/status, the difference #, obtained by subtracting south flow data # from north flow data # of the same theory, and @ main flow/status, e.g., intersection (4, 2) data, "F: 8-1=7@west// 1-7= -6@south "and" Q: 16-1=15@west/congestion// 0-0=0@indicates that the main flow direction is obtained by predicting the difference 7 between east and west flows of the intersection to be west, the main flow direction is obtained by predicting the difference 6 between north and south flows to be south, the main flow direction is obtained by predicting the difference 15 between east and west fleet lengths to be west, and the main flow direction is obtained by predicting the difference 0 between north and south fleet lengths to be none;

E2-S31, 1) obtaining a traffic mode according to the traffic information predicted by analysis in the decision optimization signal, and matching the traffic mode to form preliminary judgment of the optimization signal, wherein the preliminary judgment comprises the following steps: 1.1 The green wave optimizing signal preliminary judging step comprises the following steps: 1.1.1 Determining the main traffic flow direction of the road network: calculating the attention point that the main flow direction flow of each same main flow direction reaches a flow set value or/and a flow total value of a flow difference set value, wherein the main flow direction with a large value is set as a main flow direction of district traffic, namely a traffic mode flow direction, and the main flow direction comprises two-dimensional traffic-flow direction, one-dimensional traffic-flow direction and zero-dimensional traffic-average direction, and calculating to obtain a table 8:

Table 8 calculation of 12 Point-of-interest cells traffic pattern information

In the table, "(i, j) @ flow #", represents the main flow # "of the intersection (i, j) of the abscissa i, j, e.g., (2, 1) @ east 5 represents the main flow 5 of the intersection (2, 1), and" + "represents addition; the sum of the east flow is 19, the sum of the south flow is 58, the sum of the west flow is 64, the sum of the north flow is 24, the larger two total flows are the south flow 58 and the west flow 64, and the traffic mode flow is two-dimensional traffic-south and west;

1.1.2 Determining road network main traffic conditions and partial congestion distribution: calculating the number of road sections of which the length of the motorcade reaches the set value of the motorcade length or/and the length of the road section reaches or is smaller than the set value of the road section congestion, namely the number of the road sections with the flow direction congestion, when two crossed flow directions have more road sections with the flow direction congestion, and both reach or exceed the set value of the flow direction, namely the set value of the flow direction congestion, the set value is set to 90 percent of the total number of the road sections with the flow direction, the two flow directions are set to be the two-dimensional traffic congestion main flow directions, when only one flow direction has more road sections with the flow direction congestion, and both reach or exceed the set value of the flow direction congestion, the flow direction is set to be the one-dimensional traffic congestion main flow direction, when no flow has the number of flow congestion road sections reaching or exceeding the flow congestion set value, the flow is set as the traffic partial congestion flow, when no flow has the number of flow congestion road sections, the flow characteristic combination comprises two-dimensional traffic-flow-movement, or with zero-dimensional traffic-all-direction-movement, or with one-dimensional traffic-flow-movement, or with two-dimensional traffic-flow-congestion, or with one-dimensional traffic-flow-congestion, or with two-dimensional traffic-flow-mixing, or with one-dimensional traffic-flow-mixing, or with two-dimensional traffic-flow-movement partial congestion, or with one-dimensional traffic-flow-movement partial congestion; according to the calculated and determined set values, the embodiment obtains the traffic mode situation part which is analyzed and calculated as shown in the table 7, wherein the traffic mode flow direction is two-dimensional traffic-south and west-movement mixed and contains partial congestion, and two road sections are congested: the cross sections (2, 3) and (2, 4);

1.1.3 Determining matching green wave optimization parameters and distribution thereof: the method comprises the steps of two-dimensional traffic-flow direction-motion matching two-dimensional green wave-flow direction-guiding, or/or zero-dimensional traffic-all direction-motion matching zero-dimensional standing wave-all direction-all guiding, or/or one-dimensional traffic-flow direction-motion matching one-dimensional green wave-flow direction-guiding, or/or two-dimensional traffic-flow direction-congestion matching two-dimensional green wave-flow direction-guiding, or one-dimensional traffic-flow direction-congestion matching one-dimensional green wave-flow direction-guiding, or two-dimensional traffic-flow direction-mixing, or one-dimensional traffic-flow direction-mixing matching one-dimensional green wave-flow direction-mixing, or two-dimensional traffic-flow direction-motion mixing containing partial congestion matching one-dimensional green wave-flow direction-guiding mixing partial congestion, or one-dimensional traffic-flow direction-motion mixing containing partial congestion matching one-dimensional green wave-flow direction-guiding mixing partial congestion; or the partial blocking with green wave-flow direction-guiding mixing part blocking comprises partial blocking and solitary wave blocking, wherein the partial blocking refers to configuring a blocked district crossing part into a corresponding district blocking signal mode, the two-dimensional green wave-flow direction blocking and one-dimensional green wave-flow direction blocking are also included, the solitary wave blocking refers to using the solitary wave technology to unblank a motorcade of a blocked road section, the solitary wave blocking also includes residual time solitary waves, and command solitary waves; in this embodiment, for two-dimensional traffic-south and west-motion mix, there is partial congestion, two road segments are congested: the cross sections (3, 2) and (4, 2) are matched with two-dimensional green wave-south and west-guiding mixed part dredging/solitary wave dredging;

2) Or the priority rule also comprises the steps that the two-dimensional green wave-flow direction-blocking-out preliminary judgment is prior to the two-dimensional green wave-flow direction-mixing preliminary judgment, the two-dimensional green wave-flow direction-mixing preliminary judgment is prior to the one-dimensional green wave-flow direction-blocking-out preliminary judgment, the one-dimensional green wave-flow direction-blocking-out preliminary judgment is prior to the two-dimensional green wave-flow direction-mixing part blocking-out preliminary judgment, and the two-dimensional green wave-flow direction-mixing part blocking-out preliminary judgment is prior to the two-dimensional green wave-flow direction-blocking-in preliminary judgment; the determined optimization signal: two-dimensional green wave-south and west-guide mixed part dredging/solitary wave;

3) And (3) making corresponding mode transition periods according to the determined optimized signals and the current signals: a determined optimization signal;

Two-dimensional green wave-south and west-guiding mixed part blocking/solitary wave, and current signal, two-dimensional green wave-north and east-guiding, making corresponding mode transition period of the two, 3.0) current signal period 68 seconds and phase timing before each intersection is kept; 3.1 Calculating the transition time length of the two signal modes of each intersection: 3.1.1 Two-dimensional green wave-south and west-guide mixed part of optimized signal dredging/solitary wave, ??? Other mode reference fast mode methods, the mode phase difference base point of which is selected at the intersection (6, 4) which is the intersection of the most upstream of the two-dimensional traffic flow direction, as the intersection marked by the dotted triangle at the upper right corner in fig. 2, the green wave flow is selected to be the mode main flow direction, the south of the green wave flow passing through the mode phase difference base point intersection (6, 4) becomes the mode auxiliary flow direction, the north-south channel becomes the channel phase difference base point of all the mode main flow direction channels, ???; (1) First, two-dimensional green wave-south and west-guide mode phase difference timing is carried out on each intersection of the whole road network according to the embodiment 1, the processes are shown in tables 2 to 4, and the results are shown in table 5; (2) Performing solitary wave phase timing-solitary wave temporary timing table on the crossing (3, 2) Western congestion fleet 16 and the crossing (4, 2) Western congestion fleet 12; the channel where two congested road segments are located is the 2 nd cross channel, which is shown in table 9 when the phase of each intersection under the guidance of the two-dimensional green wave-south and west-of the instruction mode,

TABLE 9 original phase timing table for each intersection of 2 nd horizontal channel

Note that: in the table, "flow direction #/#/#" represents the phase timing of the intersection represented by the table coordinates, for example, "coordinates (0, 1) are 22/12/" represents the straight-going phases of the east and west directions of the intersection (0, 1) for 22 seconds, the left-hand phase 12, and no right-hand phase; the phase difference is the remainder of the mode phase difference period of the intersection;

-calculating the time (seconds) t _x required by the congestion fleet at the congested intersection (3, 2), equal to the empirical value of the congestion fleet length (standard number of small cars) q times the intersection passing rate (seconds per standard number of small cars) v _x,v _x, from 2 to 2.6, taking v _x＝2,t _x =16×2=32 seconds; letting intersection (3, 2) west flow to original phase time 20 seconds borrow other phase time 10, get temporary phase timing 32 seconds, as shown in the (3, 2) table of corresponding intersection of table 9;

Calculating the time and temporary timing needed by the congestion fleet to pass through each intersection of the downstream path, wherein the calculation consists of two sections,

1. Congestion intersections (3, 2) to intersections (2, 2) with fleet sensors at the most downstream in the west flow direction are formed by the steps of: calculating the sum of the downstream intersection western flow direction motorcade and the time when the congestion intersection western flow direction motorcade passes through the intersection, wherein the intersection (2, 2) western flow direction motorcade 8+ intersection (2, 2) western flow direction motorcade 16=24, and the sum tq=24×2=48 seconds when the intersection passes through the intersection;

Calculating the time loss trq of the congestion fleet reaching the intersection (2, 2), which trq is the time loss when trq > 0, when trq is counted into said passing intersection, when trq < = 0, indicating no time loss: trq=d/v0- (1/v0+a) ×q, where d is the length-meter of the road segment between adjacent intersections, v0 is the designed green wave hour rate-meter/second at the specified limit hour rate for that road segment, q is the length-meter of the queuing of the (2, 2) west-flow vehicles at the intersection, a is the fleet initiation factor, and its estimated range is 0.10 to 0.26, taken in 0.18, units: second/meter, the value can be dynamically adjusted, a is that the time when a motorcade starts = 0.18 x 8 x 7 = 10.08 = 10 seconds, (d-q)/v0= (150-8 x 7)/12.5 = 7.5, trq = 7.5-10.08 < 0; and (3) injection: the number 7 in the calculation is the standard passenger train length and the train distance;

letting intersection (2, 2) west flow to original phase time 20 seconds borrow other phase time 28, get temporary phase timing 48 seconds, as shown in the (2, 2) table of corresponding intersection of table 9;

2. Then the vehicle is flowed to the crossing (1, 2) without the motorcade sensor until the most downstream crossing (0, 2); the timing is correspondingly divided into residual time solitary wave and instruction solitary wave, and the timing is carried out according to an instruction solitary wave algorithm: forcing each intersection of the downstream sensorless intersection to use temporary phase timing of the intersection of the adjacent motorcade sensors, as shown in the (1, 2) and (0, 2) tables of the corresponding intersections of table 9, to obtain a temporary phase timing table of the instruction solitary wave part; the synthesis with the upstream, residual, orphan section yields a temporary phase timing table for the congested fleet path, as shown in table 10,

Table 10 Cross-2. Cross-channel individual crossing solitary wave temporary timing Table

Because the crossroad (4, 2) western flow direction congestion fleet is slightly smaller than the former crossroad (3, 2) western flow direction congestion fleet, the solitary wave temporary timing table of the untwisted crossroad (3, 2) western flow direction congestion fleet can be suitable for untwisting the crossroad (4, 2) western flow direction congestion fleet, so the solitary wave temporary timing table executes 2 periods to untwist the congestion fleet of the crossroad (4, 2);

E2-S42, performing an optimization signal: mode transition period control: firstly, running a mode transition period, and then running a new periodic signal; and executing the solitary wave temporary timing table.

Example 3: s101, adding green wave parameters-phase difference fluctuation of a new signal mode; the road network as in embodiment 2, signal and point of interest and traffic data configuration and setting; the following are added in S12, S22, S32,

E3-S101-S1, creating a new parameter in the green wave parameters of the signal mode library, namely phase difference fluctuation, and setting flow direction phase difference change at a road opening; the values are road team phase difference and its variation trq, trq=d/v 0- (1/v0+a) Q, Δtrq= - (1/v0+a) Δq, ("traffic signal green wave control method" china invention, 201710224791.X and "traffic signal chord control method and system" china invention, 201710897777.6); row 15 as in table 6;

the traffic mode creates a new parameter crossing to set the length Q of a flow direction motorcade, the variable delta Q of the flow direction motorcade and the set values of the flow direction motorcade and the variable delta Q;

The signal mode is matched with the traffic mode, and green wave-intersection flow direction-phase difference fluctuation and traffic-intersection flow direction-phase motorcade change are added;

E3-S101-S2, predicting traffic information, wherein the attention point crossing unit is added with a new processing function: the characteristic data that the length of the motorcade reaches a set value and the change of the motorcade reaches the set value, which are obtained by a sensing system of the motorcade in the specified flow direction, namely the fluctuation of the motorcade in the row flow direction of the intersection, or the fluctuation of the motorcade in the row flow direction of the intersection, are found and sent to an analysis layer; in this embodiment, the direction of the flow direction of the train of lines at the intersection means the horizontal direction, the east or west direction, and the direction of the flow direction of the train of lines at the intersection means the longitudinal direction, the south or north direction, and the direction;

E3-S101-S3, determining an optimized signal, 1) adding a new optimized signal preliminary judgment unit to an analysis layer: 4 column fluctuation initial judgment units for respectively analyzing 4 columns of intersections of the vehicle team sensing system in the embodiment, and 3 column fluctuation initial judgment units for respectively analyzing 3 rows of intersections of the vehicle team sensing system in the embodiment; the initial judging unit of the rise and fall analyzes whether the number of the intersections of the row intersection, the column direction and the vehicle queue rise and fall of all the intersections of the same column reach a set value or not so as to determine the change of traffic mode, the row direction and the vehicle queue of the row intersection, and match the initial judgment of the green wave, the row direction and the phase difference rise and fall of the row intersection; the primary line fluctuation judging unit analyzes whether the number of line intersections of all the specified intersections of the same line reach a set value or not so as to determine the traffic mode, the line intersection flow direction and the vehicle team change, and the primary green wave, the line intersection flow direction and the phase difference fluctuation judgment are matched; 2) The preliminary judgment of the rise and fall of the priority rule increase is only prior to the zero-dimensional standing wave; 3) The method comprises the steps of manufacturing a mode transition period, adding and recalculating the absolute phase difference of the mode of the current signal intersection and the period remainder thereof, and using the corresponding road phase difference trq as the relative phase difference of the intersection in the intersection flow direction of the vehicle sensing system;

E3-S101-S4, performing an optimization signal: adding phase difference fluctuation control: firstly, the current phase difference period is completed, and then the phase difference fluctuation, namely a new phase difference period signal, is operated;

Claims

An intelligent control architecture method for traffic signals is characterized by comprising the following steps:

S1, obtaining road network parameters; creating a plurality of road network traffic signal modes, namely signal modes for short, forming a signal mode library, wherein each signal mode provides control service of road network traffic characteristics corresponding to the mode and forms an optimized signal matched with the road network traffic characteristics; acquiring or configuring a current running signal mode and parameters thereof, namely current signals and parameters thereof;

The road network parameters comprise the length of each road section in the road network and the traffic time of each road section; the traffic time comprises driving time or/and starting time of a congestion vehicle team; the driving time refers to the time taken by the vehicle to complete a road section at a set vehicle speed, and is equal to the length of the road section divided by the set driving speed, or comprises the braking time of subtracting the set driving speed; the time taken by the congestion fleet to drive from the head-to-the-spot to drive from the tail-to-the-spot is equal to the fleet starting coefficient, the congestion coefficient is equal to the ratio of the fleet length to the road section fleet, and the congestion coefficient is equal to 1, represents serious congestion, or comprises the fleet starting coefficient calculated according to the experimental value range of 0.10 to 0.26, or is 0.18 in units: seconds/meter; and (3) injection: the "and" or "and" expressions "herein mean" expressions "immediately following the" and "or" following the "or/and, and do not refer to" expressions "listed after comma, for example," expression 1, or/and "co-existence with expression 2," expression 1 "and" expression 3 "in expression 3," expression 2 "is in" or "existence relation with" other expressions, or "existence relation with" existence relation;

The signal mode comprises any signal for setting the green light propagation flow direction among the phases of the intersections, which is called a green wave; the characteristic parameter of the flow direction as a signal mode green wave is called a green wave flow direction, and the mode is called a green wave-flow direction; the set green wave flow direction is determined by the phase time difference configured by ratio signals running between the intersections, namely the magnitude order of the phase differences, and flows from the intersection with smaller phase difference to the intersection with larger phase difference; the phase time difference between two adjacent intersections is a relative phase difference and is equal to the traffic time set by the road section between the adjacent intersections; the signal mode without phase difference among ratio signals running among all intersections is standing wave, green light change is not transmitted, namely, the ratio mode and the green wave degradation mode are adopted, and the control service function of equal traffic characteristics of all flow directions is provided; the ratio signal finger port configures each phase time length according to the set period and the set ratio; the green wave characteristic parameters or the green wave characteristic parameters also comprise a function called a green wave function, wherein the function comprises guiding or balancing, or/and dredging, or/and mixing, or/and convection guiding, or counter guiding, wherein the guiding refers to that when the green wave flow direction is the same as the controlled traffic flow direction, the relative phase difference is calculated when the road traffic is used by adopting the set driving; equalization means that green light signals have no flow direction, and 0 phase difference of each intersection is synchronous; the green wave flow direction is opposite to the controlled traffic flow direction, and the relative phase difference is calculated when the traffic on each road section is started by adopting a set congestion vehicle team; mixing means when the green wave flow direction and the controlled traffic flow direction comprise the same part and the opposite part, when the road sections of the same flow direction part are used for driving and the road sections of the opposite flow direction part are used for starting by a congestion vehicle team; the guiding of traffic in two opposite directions is one of guiding; the green wave flow direction or the combination of the green wave function and the green wave function is a green wave optimizing signal, and the modes of the green wave flow direction or the combination of the green wave function and the green wave function are respectively marked as green wave-flow direction-guiding, green wave-flow direction-blocking, green wave-flow direction-mixing and standing wave-uniform direction-balancing; the signal mode parameter also comprises a period, and each phase is distributed for a long time, namely phase timing; the phase includes a direction phase representing a control direction of the intersection, or a shunt phase controlling left/right steering among the direction phases;

The road network traffic characteristics, namely traffic modes for short, and the parameters comprise flow directions, or/and conditions, or/and flow, or/and phase shunt quantities of each phase of the intersection; wherein the condition comprises movement, i.e. non-congestion, or/and mixing; congestion refers to the condition of a fleet that the length of a road segment minus the length of the fleet reaches or is less than a set value, or the congestion coefficient reaches or exceeds a set value, which is simply referred to as a road segment congestion set value; mixing means that part of road sections are congested and part of road sections are not congested; the traffic pattern flow direction or the traffic pattern combined with the traffic pattern condition is recorded as traffic pattern-flow direction-movement, or traffic pattern-flow direction-congestion, or traffic pattern-flow direction-mixing, or traffic pattern-all direction-movement;

The matching of the signal mode and the road network traffic characteristics refers to the matching of corresponding parameters of traffic modes, and the matching comprises a green wave flow direction optimizing signal which is matched with the traffic mode flow direction in a consistent way, or a green wave optimizing signal which is matched and combined with the green wave function and the traffic mode condition in a corresponding way, and the green wave optimizing signal comprises a green wave-flow direction-guiding matching traffic mode-flow direction-movement, a standing wave-uniform direction-balanced matching traffic mode-uniform direction-movement, or traffic mode-flow direction-congestion matched with the green wave-flow direction-dredged traffic mode-flow direction, or traffic mode-flow direction-mixed matched with the green wave-flow direction; or/and a period optimization signal corresponding to the signal mode period and traffic mode flow; or/and phase timing optimization signals correspondingly matched with traffic mode phase diversion flow when the signal mode phase timing is performed; the flow direction consistent matching means that the flow direction is the same, the corresponding matching means that the corresponding signal mode parameter values of the traffic mode parameter values in the series of the numerical value sets set between the two mode parameter sets are related to the matching, the selectable numerical value sets comprise traffic mode parameter status and signal mode parameter function numerical value sets, traffic mode parameter flow and signal mode parameter period duration numerical value sets, traffic mode parameter phase shunt flow and signal mode parameter phase timing numerical value sets, and traffic mode parameter fleet leader related values and signal mode setting corresponding parameter numerical value sets;

s2, predicting traffic information: according to the obtained traffic information of the road network, the traffic information of the road network with a plurality of time periods in the future, wherein the time periods are actually measured or/and a plurality of time periods in the past, m > =1 cycle c, and each flow direction traffic flow characteristic or/and a fleet characteristic are predicted; when the predicted future period is not set, the next period is the predicted period;

S3, determining an optimized signal: 1) According to the traffic mode obtained by receiving the command signal mode or analyzing the predicted traffic information, finding a signal mode matched with the traffic mode from the signal mode library to form preliminary judgment of the optimized signal, wherein the preliminary judgment comprises 1.1) preliminary judgment of a green wave optimized signal, 1.2) preliminary judgment of a periodic optimized signal or preliminary judgment of a phase timing optimized signal, and the command signal mode refers to a signal mode which does not need to be matched with the traffic information and is forced to execute a command; 2) Or determining an optimized signal from the preliminary judgment according to a priority rule; 3) Making a corresponding mode transition period according to the determined optimized signal and the current signal;

s4, executing an optimization signal: mode transition period control: the mode transition period is completed by running first, and then the new periodic signal is run.
The traffic signal intelligent control architecture method of claim 1, wherein,

S11, the signal modes in the signal mode library comprise superposition signals;

The road network parameters comprise road network topology forms: a topological parallelogram or a virtual intersection and a virtual road section;

The superimposed signal refers to a green wave signal running in 2 or more cross flow directions within a set period (including a plurality of n > =1 signal periods c), that is, any two-dimensional green wave signal based on two cross flow directions, and any dimension-reducing form thereof; when one of the two-dimensional green waves flows to the green wave phase difference to be configured as 0, the dimension is reduced to one-dimensional green wave;

The green wave parameter flow direction also comprises two crossed flow directions, the green wave is called a two-dimensional green wave, or is marked as a green wave-double flow direction or a two-dimensional green wave-flow direction, and the dimension reduction form comprises a one-dimensional green wave-flow direction and a 0-dimensional standing wave-uniform direction; the green wave optimization signal comprises two-dimensional green wave-flow direction-guide, one-dimensional green wave-flow direction-guide, 0-dimensional standing wave-uniform direction-equalization, two-dimensional green wave-flow direction-unblocking, one-dimensional green wave-flow direction-unblocking, two-dimensional green wave-flow direction-mixing, one-dimensional green wave-flow direction-mixing or two-dimensional green wave-flow direction-opposite guide, one-dimensional green wave-flow direction-opposite guide:

The traffic mode parameter flow direction also comprises two crossed main flow directions, the traffic mode is called two-dimensional traffic, or is marked as traffic-double flow directions or two-dimensional traffic-flow directions, and the dimension reduction form comprises one main flow direction which is one-dimensional traffic-flow direction and 0-dimensional traffic-uniform direction; the traffic mode comprises two-dimensional traffic-flow direction-movement, one-dimensional traffic-flow direction-movement, 0-dimensional traffic-uniform direction-movement, two-dimensional traffic-flow direction-congestion, one-dimensional traffic-flow direction-congestion, two-dimensional traffic-flow direction-mixing, one-dimensional traffic-flow direction-mixing, or two-dimensional traffic-flow direction-convection, one-dimensional traffic-flow direction-convection;

The green wave optimizing signal also comprises an optimizing signal which is matched with the two-dimensional traffic by the two-dimensional green wave, namely the two-dimensional green wave optimizing signal, optionally comprises two-dimensional green wave-flow direction-guide and two-dimensional traffic-flow direction-motion matching, one-dimensional green wave-flow direction-guide and one-dimensional traffic-flow direction-motion matching, 0-dimensional standing wave-average direction-balance and 0-dimensional traffic-average direction-motion matching, or two-dimensional green wave-flow direction-obstruction and two-dimensional traffic-flow direction-congestion matching, or one-dimensional green wave-flow direction-obstruction and one-dimensional traffic-flow direction-congestion matching, or two-dimensional green wave-flow direction-mixing and two-dimensional traffic-flow direction-mixing, or two-dimensional traffic-flow direction-convection matching, or one-dimensional green wave-flow direction-pair-guide and one-dimensional traffic-flow direction-convection matching;

And S21, two or more crossed flow direction traffic information in the predicted traffic information or the state thereof.
The traffic signal intelligent control architecture method of claim 2, wherein,

S12, the superposition state signal also comprises a step of enabling a set motorcade of one phase of a road junction to obtain a plurality of continuous intersection green light signals, abbreviated as solitary waves, and superposing the continuous intersection green light signals in two-dimensional green waves under the set traffic characteristic condition;

the signal mode parameters also comprise a path temporary timing table of the plurality of continuous intersections, which is called an orphan temporary timing table;

The set traffic characteristic conditions comprise instructions, so that a set vehicle team of the flow direction phase of a specified intersection forcibly occupies green light time of other phase vehicle teams of the front intersection, and passes, namely forcible solitary waves; or/and the set motorcade which enables the flow direction phase of the designated intersection to occupy the green light remaining time of motorcades in other phases of the front intersection, namely, the remaining time passes, namely, the remaining time solitary wave; both are commonly referred to as solitary wave traffic;

The signal mode is matched with the optimized signal of the traffic mode, and the optimized signal also comprises an orphan-flow direction-orphan temporary timing table and a set motorcade-flow direction-path intersection table, wherein the orphan temporary timing table comprises a forced orphan temporary timing table or/and a residual orphan temporary timing table;

S22, the predicted traffic information further comprises that the real-time actual measurement and prediction set traffic characteristic conditions comprise instruction solitary waves: including forced solitary waves, or/and time-lapse solitary waves; configuration calculation of a forced solitary wave temporary timing table: the set motorcade of the forced specified intersection flow direction phase and the direction phase or the diversion phase occupies the phase green light time of other motorcades of the front intersection, and the forced solitary wave temporary timing table is built according to the calculation; configuration calculation of a residual time solitary wave temporary timing table: designating the intersection flow direction phase to contain the direction phase or the diversion phase to set the vehicle team to occupy the relative phase of the front intersection, so that the vehicle team can pass the remaining green light time after providing the phase, and the temporary timing table of the remaining time solitary wave is built according to the calculation; the method for calculating the remaining time is called an A-A algorithm for short, and comprises the steps of using special information of the tail q of a directional phase diversion phase queue and a long vehicle queue of the flow direction traffic phase of each set intersection;

S32, the step of determining the matching of the optimized signal 1) predicted traffic mode and the signal mode further comprises the steps of receiving an instruction solitary wave, determining an intersection phase setting motorcade, and preliminarily judging the optimized signal of the solitary wave superimposed on the current signal mode, wherein the step of establishing a solitary wave temporary timing table for obtaining green light signals of a plurality of continuous intersections by using an solitary wave prediction algorithm; the step 2) or the priority rule also comprises the step of forcing the preliminary judgment of the solitary wave to be prior to the preliminary judgment of the solitary wave in the rest time, and the preliminary judgment of the solitary wave to be prior to other preliminary judgment;

s42, the performing optimization signal further includes: and executing the solitary wave temporary timing table.
The traffic signal intelligent control architecture method of claim 2, wherein,

S13, the superposition state signal also comprises a driving which is closest to one phase of the intersection under the characteristic condition of setting traffic information, namely a phase head driving, a green light signal is obtained by a red light, namely a differential green wave, and the differential green wave is superposed in the two-dimensional green wave; the driving refers to a vehicle which normally runs at a specified speed;

The signal mode parameters also comprise the minimum safe switching passing time between green light and red light between phases, which is called differential green wave time or delta t ^Th0 of phase change quantum time, and the two phases are involved; the minimum safe phase switching passing time refers to the minimum time for enabling the phase head vehicle to safely stop on a front parking line by normal braking when the control phase signal of the phase head vehicle is switched from a green light to a red light, and enabling other phase head vehicles to safely pass through a front intersection after the control phase signal of the phase head vehicle is switched from the red light to the green light; the distance between the phase head car and the front control phase, which is calculated according to the phase minimum safe switching passing time, is the phase minimum safe distance;

The set traffic information characteristic conditions comprise that the phase head vehicle q0 of each set intersection when flowing to a traffic phase red light is at or smaller than the minimum safety distance set by the phase, and the phase head vehicle q0 of the intersection ratio signal green light is outside the minimum safety distance of the phase or has no pedestrians with the corresponding pedestrian phase, namely the ratio signal green light phase has no vehicle or no pedestrian, and is jointly called differential traffic of the red light traffic phase head vehicle at a differentiable position, and is also called differential green wave condition; or continuing the differential green wave condition under the following set sequence rule, when the green phase of the green time of the ratio signal is occupied, or the flow direction detects the presence of a car to other diversion phases, or other flow directions detect the presence of a car;

The optimized signal of the signal mode matching with the traffic mode also comprises differential green wave time and two phases thereof, and differential green wave conditions and two phases thereof;

s23, the predicted traffic information further comprises differential green wave conditions of the set traffic characteristic conditions which are actually measured in real time;

S33, the step of determining the matching of the optimized signal 1) and the signal mode further comprises the steps of according to the actual measurement to the differential green wave condition or the command differential green wave signal mode, for the red light phase head vehicle meeting the differential green wave condition in the current signal mode, performing preliminary judgment on the optimized signal matched with the differential time superimposed on the current signal mode, namely, enabling the red light phase head vehicle meeting the differential green wave condition in the current signal mode to obtain the phase change quantum time or the differential time of occupying one of the ratio signal green light phase no vehicle or no pedestrian phase; the 2) or the priority rule further comprises that the preliminary judgment of the differential green wave is superior to other preliminary judgment;

s43, performing the optimization signal further includes: the green light is immediately switched to or held to the phase where the differential time is obtained.
The traffic signal intelligent control architecture method of claim 1, comprising

S101, the signal mode library comprises operations of adding modes or mode parameters, a new signal mode is set to provide services of setting traffic modes or serve the set traffic modes, the signal mode parameters are matched with the traffic modes served by the signal mode, the signal mode library is respectively configured into the signal mode library in S1, the traffic information is predicted in S2, the preliminary judgment priority rule for determining the optimized signal in S3, and the signal optimizing operation is executed in S4.
The traffic signal intelligent control architecture method according to claim 1, wherein the S2 predicted traffic information is characterized in that,

S201, actually measuring or predicting road network traffic information and the characteristics thereof include setting a plurality of attention points for assembling traffic sensing devices in a road network, setting positions in road sections or/and intersections, and acquiring traffic flow characteristic data or/and fleet characteristic data of the attention points for setting flow directions so as to analyze and express the road network traffic information characteristics.
The traffic signal intelligent control architecture method according to claim 6, wherein the S2 predicted traffic information is characterized in that,

S202, the traffic flow characteristic data of the traffic flow set by the attention point comprises a plurality of corresponding traffic flow set values or change set values thereof, or/and flow difference set values of the traffic flow set by the attention point, wherein the flow direction reaching the flow set values or the flow difference set values of the traffic flow set by the attention point is used as the main flow direction of the attention point; or the fleet characteristic data of the flow direction set by the attention point comprises a plurality of corresponding fleet length set values or change set values thereof; or/and the difference between the length of the set flow direction motorcade and the length of the road section where the set flow direction motorcade is located, the condition that the difference reaches the difference set value is the set flow direction congestion road section of the concerned point.
The traffic signal intelligent control architecture method according to claim 6, wherein S2 is characterized in that,

S203, configuring calculation processing units for predicting the point traffic information, namely attention point units for short, wherein each attention point unit predicts traffic information of an attention point set flow direction corresponding to a set prediction method; a plurality of the attention point units form a prediction layer; the prediction method refers to any method for predicting future data according to existing data, and comprises a repeated prediction method, an empirical method, a mean value method, a maximum value method, a statistical optimization method, an artificial intelligence method comprising a neural network method and an expert system method, wherein the repeated prediction method, the empirical method, the mean value method, the maximum value method and the statistical optimization method are directly used for predicting the future data by using real-time detection data.
The traffic signal intelligent control architecture method according to claim 8, wherein the S2-acquisition predicted traffic information is characterized in that,

S204, the traffic information prediction calculation processing unit for setting the flow direction of the attention point intersection, namely an intersection unit for short, wherein each intersection unit is used for predicting the traffic information characteristics of the flow direction phase diversion or relates to the traffic information characteristics and the set value of the traffic information prediction calculation processing unit comprising the vehicle source flowing to the upstream adjacent road section or the intersection unit flowing to the upstream.
The traffic signal intelligent control architecture method according to claim 6, wherein the S2-obtained predicted traffic information is characterized in that

S205, the number, distribution, road segment or intersection type of the points of interest is determined by the flow direction distribution predicted by the set prediction method.
The traffic signal intelligent control architecture method according to claim 1, wherein the determining of the optimized signal at S3 comprises,

S301, the preliminary judgment of the green wave optimizing signal comprises green wave flow direction optimization and green wave function optimization, and the steps comprise 1) determining the flow direction of a traffic mode: calculating the sum of the main flow of the attention point reaching the flow set value or/and the flow difference set value, namely the flow of the attention point main flow, wherein the flow with the large sum value is set as the road network traffic main flow, namely the traffic mode flow, the two road network traffic main flows which are intersected are the traffic mode double flow, the two-dimensional traffic-flow is marked, the one road network traffic main flow is the traffic mode single flow, the one-dimensional traffic-flow is marked, the traffic mode flow without the road network traffic main flow is the traffic mode flow, marking as zero-dimensional traffic-average direction; 2) Or with determining traffic pattern conditions: calculating the number of road sections with the length of the motorcade reaching the set value of the motorcade length or/and the length difference of the road sections reaching or smaller than the set value of the road section congestion, namely, the sum of the number of the road sections with the length of the motorcade reaching or/and the length difference of the road sections reaching or smaller than the set value of the road section congestion, wherein the direction with the large sum value is set as the main flow direction of road network traffic congestion, namely, the main flow direction of traffic mode congestion, when two crossed directions have more numbers of the road sections with the congested road sections and reach or exceed the set value of the flow direction, namely, the set value of the flow direction congestion, the two directions are two main flow directions of road network traffic congestion, namely, the two-dimensional traffic-flow direction congestion, when only one flow direction has more numbers of the flow sections with the congestion, and the number of the congestion road sections of the other flow direction is not the number of the congestion road sections of the flow direction, the flow direction is a main flow direction of the traffic jam of the road network, which is marked as one-dimensional traffic-flow direction-congestion, and when the number of the congestion road sections of the other flow direction is not the number of the congestion road sections of the flow direction reaches or exceeds the set value of the congestion road sections of the flow direction, the flow direction is the part of the congestion flow direction, including the congestion flow of a small area or the congestion flow directions of a plurality of road sections; the feature of combining with the traffic pattern flow comprises two-dimensional traffic-flow-movement, or/or with zero-dimensional traffic-all-way-movement, or/and with one-dimensional traffic-flow-movement, or/and with two-dimensional traffic-flow-congestion, or/and with one-dimensional traffic-flow-congestion, or/and with two-dimensional traffic-flow-mixing, or/and with one-dimensional traffic-flow-mixing, or/and with two-dimensional traffic-flow-movement, or/and with one-dimensional traffic-flow-movement; 3) Determining matched green wave optimization parameters and distribution thereof: the two-dimensional traffic-flow direction-motion matches the two-dimensional green wave-flow direction-guide, or/or matches the zero-dimensional traffic-all-direction-motion matches the zero-dimensional standing wave-all-direction-all-guide, or/or matches the one-dimensional traffic-flow direction-motion with the one-dimensional traffic-flow direction-one-dimensional green wave-flow direction-guide, or/or matches the two-dimensional traffic-flow direction-congestion with the two-dimensional traffic-flow direction-flow-block, or matches the one-dimensional traffic-flow direction-flow-congestion with the one-dimensional traffic-flow direction-flow-block, or/or matches the two-dimensional green wave-flow direction-mixture with the one-dimensional traffic-flow direction-flow-mixture, or/or the two-dimensional green wave-flow direction-guiding mixed part is dredged by matching partial congestion with the two-dimensional traffic-flow direction-movement mixed part, or/and the one-dimensional green wave-flow direction-guiding mixed part is dredged by matching partial congestion with the one-dimensional traffic-flow direction-movement mixed part; or the partial blocking with green wave-flow direction-guiding mixing part comprises partial blocking and solitary wave blocking, wherein the partial blocking refers to the partial blocking as a district road network is configured into a corresponding road network blocking signal mode, the two-dimensional green wave-flow direction blocking and one-dimensional green wave-flow direction blocking are also included, the solitary wave blocking refers to the solitary wave blocking of a vehicle team of a blocked road section by using the solitary wave technology, the solitary wave blocking also includes residual time solitary waves, and command solitary waves;

Or/and directly carrying out green wave optimization signal prediction preliminary judgment by using the prediction method: the predicted target data comprise specified traffic characteristic data, the signal parameters of the traffic are adjusted and optimized by the prediction method, and the optimized signal preliminary judgment of the signal parameters of the traffic characteristic data meeting the prediction target is optimized according to the specified traffic characteristic data and the green wave parameter data set, so that the method is called a direct optimized signal prediction method.
The traffic signal intelligent control architecture method according to claim 1, wherein the determining of the optimized signal at S3 comprises,

S302, preliminary judgment of the periodic optimization signal or preliminary judgment of phase timing optimization is carried out, and the method further comprises the steps of carrying out prediction optimization by using any intersection signal timing algorithm, a Webster timing method, a conflict point method, an estimation method, a critical lane method and a prediction method related to the periodic phase timing optimization signal, which is called a periodic phase timing optimization signal prediction method.
The traffic signal intelligent control architecture method according to claim 1, wherein the determining of the optimized signal at S3 comprises,

S303, the prediction method further comprises a direct optimized signal prediction method and a periodic phase timing optimized signal prediction method, and a new change relation between traffic information characteristic data acquired by traffic information attention points of a road network and corresponding optimized signal parameter data is found through an optimized signal learning method aiming at minimizing vehicle waiting time or/and minimizing vehicle waiting length, and the new change relation is created as a new optimized signal and is added into a signal mode library.
The traffic signal intelligent control architecture method according to claim 1, wherein the determining of the optimized signal at S3 comprises,

S304, the priority rule decides the priority of the preliminary judgment of each optimized signal according to the data sequence including the calculation of the reduction of the waiting time of the driving, the reduction of the fleet, and the increase of the flow caused by the preliminary judgment of each optimized signal.
The traffic signal intelligent control architecture method according to claim 2, wherein the determining of the optimized signal at S3 comprises,

S305, the priority rule ranks the former in preference to the latter according to the size of the estimated data: the method comprises the steps of carrying out a command signal mode, carrying out preliminary judgment with two-dimensional green wave-flow direction-blocking, carrying out preliminary judgment with one-dimensional green wave-flow direction-mixing, carrying out preliminary judgment with two-dimensional green wave-flow direction-opposite guiding, carrying out preliminary judgment with one-dimensional green wave-flow direction-opposite guiding, carrying out preliminary judgment with two-dimensional green wave-flow direction-guiding, carrying out preliminary judgment with one-dimensional green wave-flow direction-guiding, and carrying out standing wave-uniform direction-balanced preliminary judgment.
The traffic signal intelligent control architecture method of claim 3, wherein the forced solitary wave temporary phase timing feature comprises

F201, calculating the time required by passing through the local intersection according to the length of the island wave motorcade obtained by prediction, and the time is used for forcing island waves for short; subtracting the forced solitary wave from the green time of the local phase to obtain a number smaller than 0, and using the time of other phases by corresponding amounts;

Predicting the signal lamp color of the related phase of the front intersection according to the length of the forced solitary wave motorcade and the predicted time reaching the front intersection, subtracting the residual green time after a set time from the green time of the same closing phase of the front intersection, subtracting the forced solitary wave time to obtain the residual green time, and if the absolute value is less than 0, predicting the time of borrowing the corresponding quantity of other phases; wherein the set time is when the phase fleet is assumed to pass;

setting a plurality of continuous intersections by predictive calculation; and making temporary timing tables of the intersections.