WO2017166474A1 - 一种基于交叉口群的交通控制方法及系统 - Google Patents
一种基于交叉口群的交通控制方法及系统 Download PDFInfo
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- WO2017166474A1 WO2017166474A1 PCT/CN2016/088548 CN2016088548W WO2017166474A1 WO 2017166474 A1 WO2017166474 A1 WO 2017166474A1 CN 2016088548 W CN2016088548 W CN 2016088548W WO 2017166474 A1 WO2017166474 A1 WO 2017166474A1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/081—Plural intersections under common control
Definitions
- the invention belongs to the technical field of traffic control, and in particular relates to a traffic control method and system based on intersection group.
- Intersection group refers to a collection of intersections in urban road network with geographical proximity and strong correlation, which has significant impact on road network traffic operation status, and is the core node and key point of urban traffic congestion and traffic safety.
- the intersection group exists in the urban road network. The intersection is divided into the intersection of the urban central area, the intersection of the two ends of the urban internal tunnel, the intersection of the adjacent intersection of the overpass, the entrance and exit of the expressway ramp and the urban road and the intersection of the city, and the urban expressway. Signal control intersections at the entrance and exit.
- the intersection group constitutes the key traffic area of the urban road network and is the key to improve the urban traffic control performance. Solving the intersection congestion problem will greatly alleviate the traffic congestion problem of the urban road network.
- intersection group correlation is mainly manifested in the short intersection spacing, the large path traffic, and the small traffic dispersion.
- the traffic distribution at the downstream intersection shows the state of the traffic flow group, while the traffic condition of the upstream intersection will be downstream under certain conditions.
- the concept of intersection group was firstly based on the need of coordinated control at intersection. When Tongji University studied the real-time adaptive control and management system of urban road traffic in China, it proposed the coordinated control and induced management of intersection group as system. A feature.
- the intersection group definitions include:
- Over-saturation of the intersection When the sum of the ratio of the flow in the two directions of the intersection to the saturated flow of the intersection is greater than 1, that is, when the traffic demand exceeds its capacity, the state of the intersection is defined as a supersaturated state.
- intersection group is oversaturated: When the traffic demand in the intersection group is greater than the traffic capacity of the intersection group network, the intersection group is considered to be supersaturated. Use the ratio of the overall traffic demand and capacity (V/C ratio) of the intersection group to determine whether the intersection or intersection group is congested. Similarly, the retention queue can also be used to define the supersaturation state, that is, if the vehicle cannot pass through the intersection in a green light cycle (it is already queued before the green light starts, and still fails to pass the intersection at the end of the green time), it can be defined.
- the state is supersaturated and the relevant factors are extended: the degree of supersaturation (queue length), the rate of change of the supersaturation state (queuing growth rate), the effect of supersaturation state within the intersection group (blocking overflow, green light) Negative effects such as emptying), duration of oversaturation (duration), etc.
- Critical path of the intersection group In the signal control of the intersection group, the path is a sequence of intersections in the intersection group, such that each of its intersections has a road segment that reaches the next intersection of the sequence. Since the intersections in the intersection group are limited, all the paths in the intersection group are finite paths, and each path has a starting intersection and an ending intersection, and the corresponding intersection flow direction is defined as the starting flow direction and the ending flow direction, and the path The passing intersection is defined as the intersection within the path.
- the critical path of the intersection group refers to the path with the largest amount of traffic in the intersection group and determines the overall operational efficiency of the intersection group. In the critical path of the intersection group, the change of the traffic service level of any road segment will affect other paths within the intersection group. It is easy to cause congestion.
- Hierarchical hierarchical control structures such as the British SCOOT (Split Cyele Offset Optimization Technique), the Australian SCATS (Sydney Coordinated Adaptive Traffic System), and the Japanese STREAM (Strategic). Real-time Control for Megalopolis-traffic), MOTION (Method for the Optimization of Traffic Signals In On-Line Controlled Network), and the like.
- the hierarchical hierarchical control structure is generally divided into an organizational layer, a coordination layer, and a control layer, wherein the coordination layer is a regional level control. Both SCOOT in the UK and SCATS in Australia belong to the static partition control strategy.
- the difference between the two is mainly the strategy of merging and separating adjacent sub-areas after partitioning.
- the SCOOT in the UK cannot be merged, and the SCATS in Australia can be merged.
- the disadvantage is the static partition control strategy, which cannot adapt to the dynamic change of the OD distribution of urban road traffic network traffic flow.
- Other models are not completely introduced in China.
- RT/IMPOST Real Time/Internal Metering Policy to Optimize Signal Timing
- the maximum traffic strategy is to maximize the number of open-crossing intersections by adjusting different signal control schemes.
- the main applications of this type of strategy are the Texas Urban Diamond Signal Control, the Arlington Approach, and the Kim Messer Control Strategy.
- phase optimization method for preventing overflow can be applied to the grid state urban road network. This control strategy was applied in the CBD part of Manhattan, New York, USA, and the total travel time was reduced by 20%.
- Intersection group coordination control range does not reflect the real-time dynamic change of its traffic correlation
- intersection groups are not only affected by the intersection spacing, but also related to the traffic behavior characteristics of intersection groups such as traffic flow distribution characteristics and signal control schemes.
- traffic behavior characteristics of intersection groups such as traffic flow distribution characteristics and signal control schemes.
- the range of intersection group and traffic coordination control is dynamic, while the traditional intersection group range determination method is not intelligent, only statically divided according to historical data, and the topology of road network is not considered. The relationship needs to be newly recognized for the correlation characteristics of the intersection group and the judgment of the range of the intersection group.
- intersection group is too saturated to be difficult to identify
- the traffic demand in the supersaturated intersection group is greater than its capacity, and the queues at the intersection are too long or even overflow, so that the conventional traffic detection method can not accurately detect the real-time traffic operation data. Because the over-saturated traffic control strategy and the steady-state traffic control strategy are different, if the supersaturation state start time cannot be accurately identified, it will affect the application effect of the traffic control optimization algorithm.
- intersection group The signal coordination control of the intersection group as a whole has been recognized and paid attention by scholars.
- traffic control strategies are usually based on global optimization or key intersection remediation.
- the collaborative path selected in the optimization process is usually manually specified. It can systematically study and apply the identification and classification of critical paths within the intersection group.
- the traffic coordination control algorithm fails to optimize the traffic characteristics of the intersection group according to the supersaturated state
- intersection group requires that the traffic signal control system must take into account the coordination between adjacent intersections and optimize the signal control scheme of all signalized intersections in the high-density road network; in addition, due to the small spacing of adjacent intersections of the intersection group, adjacent intersections The traffic flow between the ports has a great influence on each other.
- the invention provides a traffic control method and system based on intersection group, and introduces traffic big data and cloud computing technology to establish a traffic state required for optimizing traffic control of an over-saturated intersection group, and establishes a city based intersection group.
- the traffic control intelligent robot thus solves the above problems in the prior art at least to some extent.
- a traffic control method based on an intersection group includes the following steps:
- Step a real-time dynamic acquisition of 360° panoramic video of the intersection through the intelligent robot, establishing an intersection operation model according to the video data, and analyzing the traffic characteristics of the intersection group according to the intersection operation model;
- Step b performing intersection evaluation index and online simulation analysis according to traffic characteristics, and identifying the traffic operation state of the intersection group;
- Step c Perform optimization of the signal timing control scheme of the supersaturated intersection on the critical path of the supersaturated intersection group, and adjust the traffic signal control strategy of the intersection group in the supersaturated state;
- Step d Run the adjusted traffic signal control strategy of the intersection group to realize the steady state operation of the intersection control signal timing optimization scheme and the intelligent robot linkage command.
- the technical solution adopted by the embodiment of the present invention further includes: the step a further comprises: performing an operation situation monitoring on the intersection operation model; the operation situation monitoring method comprises: analyzing the congestion formation and evacuation mechanism of the intersection group and the traffic operation parameter Acquisition and processing; the method for collecting and processing traffic operation parameters specifically includes: video vehicle detection and traffic correlation index modeling.
- the technical solution adopted by the embodiment of the present invention further includes: in the step b, the identifying the traffic operation state of the intersection group includes: defining the intersection group range, identifying the intersection group supersaturation state, and detecting the critical path of the intersection group And short-term prediction modeling and simulation of traffic parameters.
- the technical solution adopted by the embodiment of the present invention further includes: in the step c, the method for optimizing the timing of the over-saturated intersection signal timing of the critical path of the supersaturated intersection group includes: Control optimization scheme static optimization; dynamic coordinated traffic signal control intersection group; hierarchical screening of traffic control strategies for supersaturated intersections; optimization of coordinated timing scheme based on non-dominated sorting genetic algorithm as benchmark time for dynamic control of signal control Scheme; real-time dynamic optimization algorithm for traffic parameters.
- the technical solution adopted by the embodiment of the present invention further includes: in the step d, the intersection signal control optimization scheme and the intelligent robot linkage command method include: urban road over-saturated intersection group dynamic and static coordinated traffic control; intersection group The selection of the critical path coordination control period; the phase difference of the critical path of the supersaturated intersection group is optimized online; the influence of the mixed traffic flow on the green signal ratio optimization is reasonably considered in the maximum minimum green time and the green time interval constraint; establishing a new intersection signal Timing control synergy linkage and command operation mode.
- the intersection signal control optimization scheme and the intelligent robot linkage command method include: urban road over-saturated intersection group dynamic and static coordinated traffic control; intersection group The selection of the critical path coordination control period; the phase difference of the critical path of the supersaturated intersection group is optimized online; the influence of the mixed traffic flow on the green signal ratio optimization is reasonably considered in the maximum minimum green time and the green time interval constraint; establishing a new intersection signal Timing control synergy linkage and command operation mode.
- the technical solution adopted by the embodiment of the present invention further includes: the calculation formula of the period length of the critical path coordinated control period selection of the intersection group is:
- a traffic control system based on an intersection group including an intelligent robot, where the intelligent robot includes a first video camera module, a second video camera module, and a data processor module;
- the first video camera module and the second video camera module are respectively connected to the data processor module;
- the first video camera module and the second video camera module are used for real-time dynamic acquisition of 360° panoramic video of the intersection, and the captured video
- the data is transmitted to the data processor module, and the data processor module is configured to establish an intersection operation model according to the video data, analyze the traffic characteristics of the intersection group according to the intersection operation model, and perform intersection evaluation index and online according to the intersection group traffic characteristics.
- Simulation analysis identifying the traffic operation status of the intersection group, so as to optimize the over-saturated intersection signal timing control scheme for the critical path of the supersaturated intersection group, adjust the over-saturated intersection group traffic signal control strategy, and control the intelligent robot Operation of the adjusted intersection group traffic signal control policy , Optimization and steady-state operation when implementing intelligent robot linkage command control signal intersection with.
- the technical solution adopted by the embodiment of the present invention further includes: the first video camera module is a 360° panoramic HD video camera that is highly scalable, and is disposed above the head of the intelligent robot, and the second video camera module is a high-definition video camera. , located in the eye of the intelligent robot.
- the data processor module includes a model establishing unit, and traffic Characteristic analysis unit, traffic operation state recognition unit, strategy optimization unit, and scheme operation unit;
- the model establishing unit is configured to receive video data transmitted by the first video camera module and the second video camera module, and perform processing such as classification, image recognition and feature extraction on the video data to generate an intersection real-time dynamic information environment, and establish a clear picture. , an open-ended intersection operation model;
- the traffic characteristic analysis unit is configured to monitor the running situation of the intersection running model, and analyze the traffic characteristics of the intersection group according to the intersection running model;
- the traffic operation state identification unit is configured to perform an intersection evaluation index and an online simulation analysis according to the traffic characteristics, and identify the traffic operation state of the intersection group;
- the strategy optimization unit is configured to optimize and induce the over-saturated intersection signal timing control scheme for the critical path of the supersaturated intersection group, and adjust the traffic signal control strategy of the supersaturated intersection group;
- the scheme operation unit is used to run the adjusted traffic signal control strategy of the intersection group to realize the steady state operation of the intersection control signal timing optimization scheme and the intelligent robot linkage command.
- the technical solution adopted by the embodiment of the present invention further includes: the intelligent robot further includes a display module, wherein the display module is a touch display screen, and is located at a body part of the intelligent robot, where the first video camera module and the second video camera module respectively The first video camera module and the second video camera module transmit the captured video data to the display module, and the display module is configured to display the video data captured by the first video camera module and the second video camera module. .
- intersection control group-based traffic control method and system constructs a 360° intersection panoramic video real-time monitoring and modeling, intersection evaluation index and online simulation analysis, supersaturated intersection critical path and control strategy optimization, and crossover
- the “four-step method” method of port signal control optimization and intelligent robot linkage command is to establish a traffic control intelligent robot based on intersection group, solve the problem of single point operation optimization of urban road over-saturation intersection, and form an intelligent command city road.
- FIG. 1 is a flow chart of a traffic control method based on an intersection group according to an embodiment of the present invention
- FIG. 2 is a flowchart of a method for identifying a traffic operation state of an intersection group according to an embodiment of the present invention
- FIG. 3 is a flow chart of optimization of traffic signal control in a supersaturated state according to an embodiment of the present invention
- FIG. 4 is a schematic flow chart of a method for optimizing a critical path and a control strategy of a supersaturated intersection according to an embodiment of the present invention
- FIG. 5 is a schematic diagram of a dynamic optimization method for intersection group traffic control according to an embodiment of the present invention.
- FIG. 6 is a schematic diagram of a method for calculating a period length of an overflow prevention according to an embodiment of the present invention
- FIG. 7 is a schematic structural diagram of a traffic control system based on an intersection group according to an embodiment of the present invention.
- FIG. 8 is a schematic structural diagram of a data processor module according to an embodiment of the present invention.
- Figure 9 is a static model diagram of the road network and related intersection groups in the central city
- Figure 10 is a schematic diagram showing the analysis of the status quo of the dynamic traffic control of the intersection group
- Figure 11 is a schematic diagram of dynamic traffic control optimization of the Lianhua Road signal control intersection
- Figure 12 is a schematic diagram of dynamic traffic control optimization for the signal control intersection of Hongluo Road.
- FIG. 1 is a flowchart of a traffic control method based on an intersection group according to an embodiment of the present invention.
- the traffic control method based on the intersection group of the embodiment of the present invention includes the following steps:
- Step 100 dynamically collect 360° panoramic video of the intersection through the intelligent robot in real time, and establish an intersection operation model according to the video data;
- a 360° panoramic HD video camera with a height and retractability is arranged above the head of the intelligent robot, and the eye of the intelligent robot is a high-definition video camera, and the intersection is dynamically acquired by a 360° panoramic HD video camera and a high-definition video camera.
- the 360° panoramic video is used to classify and filter the captured panoramic video, image recognition, feature extraction and other processes to generate an intersection real-time dynamic information environment, and establish an intersection operation model with clear picture and wide vision.
- Step 200 Perform an operation situation monitoring on the intersection operation model, and analyze the traffic characteristics of the intersection group according to the intersection operation model;
- step 200 the operation model calibration and operation situation monitoring of the traffic big data intersection are carried out, and the geometric topological characteristics of the intersection group, the characteristics of the road space, the discrete characteristics of the traffic flow between the intersections, and the traffic signal control characteristics are analyzed according to the overall model of the intersection.
- the traffic characteristics of the intersection group are analyzed, and the traffic flow characteristics and traffic operation data collection and processing methods in the intersection group are analyzed as the basis of traffic state identification and traffic signal control.
- the method for monitoring the running situation of the intersection running model includes the following steps:
- Step 201 Analyze the congestion formation and evacuation mechanism of the intersection group
- the details include: analyzing the predisposing factors of the intersection group congestion, determining the influence of the adverse effects such as intersection overflow, green light discharge, and detention queue on the traffic congestion of the intersection group, determining the process of supersaturation state formation; judging the traffic flow bottleneck dissipating The traffic flow operation state, the traffic network load balancing theory is applied to describe the traffic flow characteristics of the congestion state evacuation process, which lays a theoretical foundation for analyzing the traffic state of the supersaturated intersection group.
- Step 202 collecting and processing traffic operation parameters
- the specifics include: determining the traffic operation parameters required for analyzing the traffic operation state of urban road intersection groups, comparing and analyzing the advantages and disadvantages of various traffic operation parameter collection methods and the adaptability to the supersaturated state traffic signal control, and optimizing the traffic state of the intersection group group. Identifying and data sources needed for traffic control; establishing traffic operation parameter cleaning and processing methods, determining traffic flow loss data completion, traffic flow error data discrimination, correction, and traffic flow redundancy data reduction algorithm, laying the foundation for traffic state analysis .
- the method for collecting and processing traffic operation parameters specifically includes video vehicle detection and traffic correlation index modeling;
- the specific method of video vehicle detection is:
- Target segmentation separating the target to be identified from the background by recognizing pixels in the image that conform to the characteristics of the vehicle;
- Post-processing calculate traffic operation parameters such as vehicle flow rate and vehicle speed according to the detection requirements.
- Traffic correlation indicators include discrete correlation indicators and retardation correlation indicators
- Discrete correlation indicators are: affected by the discrete factors of traffic flow, if the downstream intersections must ensure that the first and last vehicles of the fleet pass through the intersection during the same green time, it is necessary to design a diffused widened green wave belt. However, this design makes the green light time of the most downstream intersection unacceptably long. It is a control method that does not constrain the discreteness, and is often not desirable in practical engineering applications. For the control method of discrete constraints, the equal-width green wave is often used, but this method will cause some vehicles at the head or tail of the traffic flow to have certain delays at each intersection.
- the discrete correlation index I1 is set as the ratio of the long green time of the vehicle such as the starting and ending points in a signal control period, that is:
- q0(i) represents the number of traffic passing through the i-term of the initial upstream intersection stop line of a certain path
- qd(i+T) represents the number of traffic arrivals at the i+Tth time of the end of the path.
- T represents the travel time from the start to the end of the path
- tg represents the duration of the green wave in one signal period.
- Q0(i) and qd(i+T) can be used for field observations or by Robertson's fleet discrete formula, ie:
- the block correlation index is: for any segment m of an intersection group forming a certain road, if there are N different flow directions at the intersection entrance path along the forward direction of the path, calculate the functional zone length value of each flow direction. the length of queue
- the field observation statistics may be used, or the queuing length calculation formula may be used for estimation.
- the queuing length calculation method of Synchro7 is adopted, and the deceleration distance is used.
- And perception-reaction distance Calculation method will It is defined as the ratio of the maximum value of the flow direction functional zone to the path length L in the entrance of the intersection of the road segment m along the path of the path, namely:
- the retardation index I2 is:
- Real-time dynamic aggregation and access to traffic big data synchronous online modeling of intersections, integration of structured, semi-structured, unstructured collection of different intersection data, optimization and improvement of intersection operation model, completion of intersection dynamic model, construction
- the information source pool of traffic big data at the intersection of the city is dynamically monitored by the monitoring and model of each year, every quarter, every month, every day to realize the real-time dynamic monitoring modeling robot at the intersection.
- the specific analysis method for analyzing the traffic characteristics of the intersection group in the embodiment of the present invention is: understanding the traffic characteristics of the intersection group from the geometric topological characteristics, the road space characteristics, the traffic flow characteristics, the traffic signal control characteristics, and the like, respectively. Finding the changing characteristics of traffic flow in the intersection group provides a basis for applying the supersaturated traffic control strategy. Among them, the geometrical topological characteristics of the intersection group classify the intersection group according to the number of road paths between the two intersections in the intersection group; the characteristics of the road space design analyze the impact of the road traffic facility design on the traffic flow operation; The description model for the urban road interruption in supersaturated state is given. According to the traffic flow characteristics of the intersection group, the appropriate traffic operation data collection means is selected to establish the data cleaning and processing method. Traffic signal control characteristics analysis basic control principle and control structure, laid the foundation for the establishment of traffic control methods.
- Step 300 Perform intersection evaluation index and online simulation analysis according to traffic characteristics, and identify intersection group transportation Line status
- the traffic state identification of the intersection group used for the supersaturated traffic signal control mainly includes the intersection group range definition, the intersection group supersaturation state recognition, and the intersection.
- the critical path detection of the mouth group and the prediction of the characteristics of short-term traffic flow parameters are predicted.
- the traffic operation parameters required for the evaluation of the operational status of the intersection mainly include: vehicle speed, traffic flow, occupancy rate, etc.
- the automatic judgment algorithms for traffic congestion state mainly include exponential smoothing method, California algorithm, McMaster algorithm, SND method, cross-correlation method. , Kalman filtering method, etc.
- FIG. 2 is a flowchart of a method for identifying a traffic state of an intersection group according to an embodiment of the present invention.
- the method for identifying the traffic operation state of the intersection group in the embodiment of the present invention includes the following steps:
- Step 301 Define an intersection group range
- intersection group In the definition of the intersection group scope is a prerequisite for the traffic state identification and traffic control optimization of the intersection group.
- the coordinated control of the intersections at the intersection group level can achieve significant improvement in the traffic operation within the intersection group.
- the intersection network group determination algorithm is used to divide the entire road network into several intersections. It is a feasible way to conduct coordinated traffic control by optimizing the traffic control strategy.
- the coordinated control of the intersection group is between the single point control and the regional control.
- the scope should be in line with the hardware requirements of the traffic signal, and the optimal traffic control strategy can be selected in a short time.
- intersections with strong correlations should be divided into an intersection group, and intersections with weak correlation should be divided into different intersection groups;
- the method for defining the range of the intersection group specifically includes: analyzing the traffic characteristics of the intersections in the intersection group based on the spatial characteristics of the intersection group and the internal correlation mechanism, and establishing a feature matrix based on the feature matrix.
- Intersection group scoping method and intersection method based on self-organizing neural network.
- the correlation between the queue length of the vehicle and the spatial distance of the intersection and the effective utilization of the green time are respectively used to describe the association characteristics of the intersection group.
- the former combines the flow factor and the distance factor, and the latter takes into account the flow factor and the timing factor.
- a feature analysis method that defines the extent of the intersection group.
- Step 302 Identify and evaluate the supersaturation state of the intersection group
- the method for identifying the over-saturation state identification and evaluation index of the intersection group is: based on the method of analyzing the degree of supersaturation of the intersection group, the ratio of the invalid green time and the total green time caused by the negative effect is applied. Define the supersaturation index and use this to measure the degree of supersaturation of the intersection group. Based on the characteristics of the negative effects produced by the supersaturated state intersection group in the spatial dimension and the time dimension, the supersaturation index of the intersection group is calculated in the spatial and temporal dimensions respectively.
- the shock wave model and the space-time map are used to calculate the maximum queuing length of the intersection from the shock wave generated when the queuing starts to dissipate and the departure shock wave generated when the green wave starts.
- the shock wave generated by the queuing starts to dissipate and the lower period red light starts.
- the parking shock wave generated at the time calculates the tributary length of the intersection, and calculates the supersaturation coefficient of the spatial dimension.
- the supersaturation degree coefficient of the intersection is calculated mainly by the long-time occupancy phenomenon of the upstream detector generated by the overflow of the intersection.
- the supersaturation degree of the intersection group is identified by the supersaturation degree coefficient of the spatial dimension and the time dimension.
- the supersaturation state cannot be directly identified by traffic parameter measurement or calculation, and can only be obtained indirectly through negative effects such as overflow caused by supersaturation.
- the definition of the over-saturation state of the intersection group is extended, and the supersaturation coefficient is calculated by the negative effect caused by the super-saturation state, thereby determining the over-saturation of the intersection group.
- the supersaturation state refers to the situation when a traffic facility controlled by a traffic signal has a traffic demand greater than its traffic capacity state (the maximum number of green time passes), which may be negatively affected by the retention queue of a certain cycle or the upstream traffic.
- the facility is defined by the negative effects of the overflow in one cycle, and the ratio of the ineffective green time to the total green time (supersaturation coefficient) is used to measure the degree of supersaturation.
- the over-saturation state of the intersection group is evaluated by using the induction coil traffic detection data, and the typical arrangement manner of the induction coil includes a parking line detector and an advanced detector (layed upstream of the parking line).
- the intersection group is queued long. No matter whether the parking line detector or the advanced detector can accurately detect the traffic organization that identifies the supersaturated intersection, the parameter estimation method is needed to identify the supersaturation state of the intersection group.
- the negative effects of traffic control in the supersonic state are used to replace the traditional estimation method to evaluate the state of the traffic facilities.
- the negative effects identified by the algorithm mainly include the length of the stagnation queue at the end of the signal period and the overflow phenomenon at the upstream intersection.
- Shockwave shockwave
- QOD Queue Over Detector
- the wave velocity (u2, u3, u4) is also used to calculate the maximum queue length in one cycle. Because the variance of traffic arrival flow rate is large, the queuing shock wave (u1) is not suitable for estimating the queue length.
- the queuing length is estimated by using the shock wave (u2) and the back shock wave (u3).
- the calculation formula is:
- qm and km represent the flow rate and density at the maximum flow rate, respectively, and kj represents the plugging density.
- High-resolution traffic data is used to estimate including Various traffic variables including qm, km, where traffic flow rate data, such as And qm can be obtained directly by the detector, but The density data of km and so on must be estimated.
- Event-based traffic data can provide a separate occupancy time, assuming that the effective vehicle length is known, the spatial average speed can be obtained; at this point, the average flow rate can be divided by the space average vehicle speed to estimate the density data.
- the methods for estimating individual velocity ui, spatial average velocity us, flow rate q and density k are:
- t0, i and tg, i represents the detector occupancy time and time interval of vehicle i
- ui and hi represent the speed and head spacing of vehicle i
- q, us and k represent respectively Average flow rate, space average speed and density
- Le represents the effective length of the car
- n represents the number of vehicles in a fleet in the same traffic state.
- Ld represents the distance between the stop line and the detector.
- Step 303 detecting and classifying the critical path of the intersection group
- the critical path of the intersection group is the high-incidence section of traffic congestion, and also the bottleneck section of the intersection group.
- the path level of the intersection group is analyzed, and the critical path of the intersection group is identified, so that the intersection group traffic control can be
- the traffic flow of the intersection group is optimized more efficiently.
- the intersection path group identification method based on wavelet transform and spectrum analysis is used to analyze and extract the intersection group traffic flow.
- the short-term variation characteristic is used to detect the critical path of the intersection group by means of data mining analysis, and to classify the intersection group path.
- the wavelet transform technology is used to decompose the traffic signal according to different frequencies, and the high-frequency signal reflecting the short-term variation characteristics of the traffic flow and the low-frequency signal reflecting the change characteristics of the traffic flow are retained.
- the filtered traffic signal is reconstructed into a new traffic signal that highlights the short-term variation characteristics of the traffic flow as input data for critical path identification and classification. Calculate the power spectral density and the cross-spectral density between the flow directions of each of the intersections of the intersections reconstructed by the wavelet transform.
- the correlation degree of the two traffic signals is determined, and the critical degree index corresponding to all the paths of the designated import is obtained, and then the phase between the two signals is calculated, and the travel time verification calculation of the two points is effective.
- Sexuality comprehensive analysis of the importance of all import critical paths.
- the traffic correlation of intersections in the intersection group is mainly reflected in the degree of dispersion of traffic flow between intersections, that is, the similarity of arrival traffic characteristics and upstream traffic characteristics of downstream intersections.
- the similarity is more obvious on the critical path.
- the wavelet transform method is used to decompose the traffic signal according to different frequencies, and the high-frequency signal reflecting the short-term variation characteristics of the traffic flow and the low-frequency signal reflecting the change characteristics of the traffic flow are retained.
- the filtered traffic signal is reconstructed into a new traffic signal that highlights the short-term change characteristics of the traffic as input data for critical path identification and classification.
- Wavelet transformation (Wavelet Transformation) is a localized analysis of time (space) frequency.
- Wavelet transform is a time-frequency resolution in which the window size is fixed and its shape is variable, and both the time window and the frequency window can be changed, while the high frequency portion has higher time resolution and lower frequency resolution.
- the wavelet transform inherits and carries forward the idea of localization of short-time Fourier transform, and at the same time overcomes the shortcomings of window size without frequency variation, etc. It can provide a time-frequency window with frequency change, and analyze and process the signal time-frequency.
- the ideal tool Its main feature is that it can successfully highlight some aspects of the problem through transformation, and has been successfully applied in many fields.
- the wavelet transform is the weighted sum of the signals to be analyzed into a family of wavelet machines, and its meaning is the mother wavelet function.
- the inner product is compared with the signal f(t) to be analyzed at different scales ⁇ :
- the spectrum analysis method is used to take the traffic flow change as the input signal, and analyze the spectrum variation characteristics at different frequencies.
- the consistency coefficient of the signals is analyzed to determine the correlation between the two traffic signals, and the phase difference between the two signals is applied to judge the effectiveness of the algorithm.
- the spectrum refers to the representation of a time domain signal in the frequency domain, which can be obtained by Fourier transform of the signal.
- the obtained conclusions are that the amplitude or phase is the vertical axis and the frequency is the horizontal axis.
- the amplitude spectrum shows the amplitude as a function of frequency
- the phase spectrum shows the phase as a function of frequency.
- the spectrum can represent the frequency of a string of sine waves, as well as the size and phase of each frequency sine wave.
- Spectral analysis is a technique for decomposing complex signals into simpler signals. Finding the information of a signal at different frequencies (such as amplitude, power, intensity, phase, etc.) is a bit-spectrum analysis.
- the power spectrum is a characterization of the energy distribution characteristics of digital time series at different frequencies, if the time series self-covariance function ⁇ k satisfies the condition Then there is the following correspondence between the power spectral density f( ⁇ ) and ⁇ k: Where: f( ⁇ ) is defined on [- ⁇ , ⁇ ] and is a real-valued non-negative function.
- Step 304 Modeling and simulating short-term prediction of traffic parameters
- the traditional traffic flow model cannot directly calculate the future traffic state through the model.
- the improved exponential smoothing method, state space neural network, extended Kalman filtering method and data fusion method are used to predict the variation characteristics of short-term traffic parameters of intersection groups.
- the traffic data of the current time period and the historical time period By using the traffic data of the current time period and the historical time period, the traffic data of the next time period is predicted, and the model is not limited by the supersaturation state.
- Short-term prediction of traffic parameters plays an important role in the design of dynamic traffic control algorithms. The accuracy of prediction has a significant impact on the effectiveness of traffic control algorithms.
- the short-term traffic flow prediction model is divided into two types: data-driven and model-based.
- Data-driven methods are processed by mathematical statistics or artificial intelligence methods, such as traffic flow, traffic speed, travel time and other historical traffic data, and predict changes in traffic flow in the future; model-based methods mainly apply traffic flow propagation model to Xue Ding
- the traffic flow state on the path is estimated and predicted.
- the model can be divided into three types: macroscopic model, mesoscopic model and microscopic model.
- the method applied to short-term prediction of traffic parameters has various forms and effects.
- SSNN State Space Neural Network
- extended Kalman filter is adopted.
- the state space neural network adds a state layer that stores the state of the previous neuron as a short-term memory layer, so that the neural network can determine the predicted output value according to the current state and the state of the previous moment. Efficiently learn complex time and space states.
- the hidden layer vector s(t) is the input vector and the deviation weighted sum, which can be calculated from the input layer vector x(t) by the transfer function:
- sm represents the value of the mth hidden layer neuron
- bm represents the deviation value of the mth hidden layer neuron
- its value is fixed at 1
- h( ⁇ ) represents the transfer function.
- Step 400 Perform optimization and induction of a signal timing matching scheme of the supersaturated intersection on a critical path of the supersaturated intersection group, and adjust a traffic signal control strategy of the intersection group in the supersaturated state;
- step 400 the intersection group facility optimization, control structure, traffic control strategy and model determine the optimization idea and control effect of the signal control scheme in the supersaturated state. Since the relatively mature supersaturated traffic control target has not yet been formed, when the goal of conventional traffic control can make the traffic run smoothly, the more mature signal optimization strategy should be adopted instead of the new control strategy.
- the control structure refers to the system structure adopted to implement the control strategy, which mainly includes centralized, decentralized, and distributed. Because the traffic control system has the characteristics of typical information dispersion (the subsystems are distributed in a wide range of urban space), it is difficult to achieve centralized control with the expansion of the road network scale. According to the discrimination of the traffic state of the road network, the control parameters and The grading and combination of control structures is the core solution to the control problem.
- intersection group traffic management layer manages the overall traffic demand at the intersection group level to ensure that the traffic pressure is shared to the surrounding road network in the supersaturated state;
- the critical path coordination control layer mainly optimizes the coordinated traffic signal control scheme of the critical path.
- the optimization layer of the single-point intersection optimizes the signal timing scheme of each intersection according to the implementation of dynamic traffic conditions.
- the critical path passes through the most vehicles and the average queue length is the smallest, avoiding negative effects.
- the traffic control strategy in the super-saturated state is divided into a single-point optimization layer, a critical path optimization layer, and a network optimization layer.
- the single-point optimization layer mainly focuses on the calculation of the timing scheme of a single intersection, and optimizes the initial timing scheme after the critical path optimization layer feeds back the initial signal timing scheme (green letter ratio, period length, etc.), and the final signal timing
- the scheme is sent to the control unit of the intersection, and each control unit needs to be able to exchange information with each other, perform short-term traffic flow prediction, and complete the rolling optimization of the control scheme.
- the critical path optimization layer is based on real-time dynamic traffic detection data and critical paths, taking into account traffic control optimization strategies and optimization target constraints to form a critical path coordination control scheme.
- This scheme reflects the decision-making idea of the traffic controller to ease the bottleneck section within the intersection group, is the basis for the network layer signal control scheme optimization, and is also the core to alleviate the over-saturation state of the intersection group.
- the supersaturation control strategy should be combined with the operation characteristics of the traffic network of the intersection group road network.
- the critical path is Using a common signal cycle wake-up control, and limiting the dispersion of the inter-intersection fleet to a harmonizable threshold, making full use of the spatial storage capacity of the dry branch, so that the overall optimized control output scheme can better adapt to the intersection group Real-time changes in traffic demand conditions within the scope.
- the evaluation criteria of traffic operation status of urban road intersections under supersaturation state are different from those of steady state traffic operation state, and their optimization objectives are also different.
- the traffic control strategy of the supersaturated intersection group needs to be based on the intersection
- the group real-time traffic operation state, the design characteristics of the intersection group, and the optimization targets in the supersaturation state (such as the number of intersections, the length of the queue, etc.) are comprehensively determined.
- the data collected by the detection device should be processed and calculated to meet the needs of traffic control and management.
- the decision support system is the core part of the entire traffic control loop. The system determines the traffic control strategy in real time based on the real-time traffic operation data and short-term prediction information obtained by the traffic information processing system, so as to implement the preset in different interference situations.
- the control objectives (such as the maximum number of intersections, the shortest queue length, etc.) for reference by traffic decision makers.
- Traffic decision makers determine the final traffic control strategy through field traffic conditions and intersection traffic characteristics.
- the effectiveness of the intersection group traffic control system is determined by the effectiveness of the control strategy and the correlation with the actual situation. Therefore, when determining the traffic control strategy, the system optimization method should be improved as much as possible and the automatic control theory algorithm should be selected. It is not simple to apply some specific algorithms to solve the problem.
- the status of traffic operation in urban road intersections can be described by various evaluation indicators.
- the total time Ts in the road network is: The total consumption time of the urban road intersection group is the least equivalent to the maximum output flow under the time weight, that is, under the appropriate traffic control measures, the faster the vehicle can leave the intersection group, the shorter the overall consumption time.
- FIG. 3 is a flowchart of traffic signal control optimization in a supersaturated state according to an embodiment of the present invention.
- the key path and control strategy optimization method of the supersaturated intersection is as follows: under the premise of the intersection group range, supersaturation state, critical path, and short-term traffic flow parameter change information, firstly optimize the optimization target of the supersaturated state traffic signal control, The traffic control structure and different levels of traffic control strategies are used to control the traffic signals of the supersaturated intersection group.
- the critical path is selected by the maximum number of vehicles and the minimum queue is the optimization target.
- the intersection group, the critical path layer and the single point intersection are applied.
- the three-level optimization mode of the mouth layer discusses the traffic control optimization strategy respectively; to prevent the negative effects such as overflow and green light release of the intersection group as the boundary conditions, determine the optimization range of the traffic control parameters of the intersection group, and propose the traffic control parameters.
- the optimization method is adopted to make the traffic flow of the intersection group in the supersaturated state run smoothly, and the state of the steady state traffic control optimization method can be applied to the rapid recovery road.
- the traffic signal timing scheme is dynamically updated according to the real-time dynamic traffic flow and short-term traffic flow prediction information.
- the method for optimizing and adjusting the critical path and control strategy of the supersaturated intersection in the embodiment of the present invention includes the following steps:
- Step 401 Static optimization of the intersection signal timing optimization scheme; in the supersaturated state, the steady-state traffic control is not applicable to the smooth optimization of the traffic flow.
- This paper analyzes the applicability of optimization targets with the largest number of critical routes and the minimum queue length in over-saturated state traffic control, and determines the traffic control optimization objectives, which lays a foundation for the optimization of traffic control parameters. Combining the supersaturated intersection group needs to optimize the control target of traffic flow in the bottleneck section, and select the hierarchical traffic control structure in traffic control, and divide it into intersection group layer, key path layer and single point intersection layer.
- the internal traffic flow of the intersection group is quickly evacuated by means of current limiting and adaptive control, and the external traffic flow is appropriately restricted; the key path layer pays attention to the coordination signal of the most prominent path of the intersection group traffic problem.
- the time plan is adopted; the single-point intersection layer optimizes the timing parameters according to the real-time traffic parameters and the coordinated control scheme of the critical path layer through the signal at the intersection, and finally determines the optimization scheme of the intersection timing signal timing control.
- Step 402 Dynamically coordinate traffic signal control intersection group
- Step 403 hierarchically screen the traffic control strategy of the supersaturated intersection group; according to the three-layer hierarchical optimization control model of the intersection group, screen the traffic control strategy applicable to the supersaturated state in the existing control strategy.
- the traffic control strategies of the single-point intersection layer include green light delay, early termination phase, phase re-service, dynamic left turn, left turn phase advance/shift, and short-circuit intersection with the same timing scheme; key path layer Including reverse coordination control, synchronous traffic control, green flash and prevent overflow, green light empty phase difference design, etc.; intersection group layer control strategy is mainly limited flow, adaptive control.
- Step 404 Optimize the coordinated timing scheme based on the non-dominated sorting genetic algorithm, as a reference timing scheme for signal control dynamic optimization; based on the offline data of the intersection group operation, select the critical path according to the traffic control target in the supersaturated state The maximum number of weighted vehicles and the minimum number of critical routes are optimized. The green time of each intersection is used as the input variable.
- the second generation multi-objective non-dominated sorting genetic algorithm is used to optimize the coordination timing scheme as the dynamic optimization of signal control. Benchmark timing plan.
- Step 405 Real-time dynamic optimization algorithm for traffic parameters
- FIG. 5 is a frame diagram of a dynamic optimization method for intersection group traffic control according to an embodiment of the present invention. Based on the traffic state information, short-term traffic flow prediction results, and the value range of key control parameters, based on the baseline control scheme, the values of traffic control parameters are dynamically adjusted based on real-time traffic data, and the time-consuming analysis of each step is performed. .
- the cycle length can be adjusted to avoid the intersection of the discrete shock wave and the queuing dissipative shock wave before the upstream intersection, thereby avoiding the purpose of avoiding the queue;
- the phase difference between the two intersections also avoids the occurrence of overflow and green light.
- Step 500 Run the adjusted traffic signal control strategy of the intersection group to realize the steady state operation of the intersection control signal timing optimization scheme and the intelligent robot linkage command;
- the existing intelligent robot is already capable of accurate and repetitive work, but in many cases it is not flexible enough to adapt itself to new tasks, nor can it cope with an unfamiliar or uncertain situation.
- the urban road traffic intelligent robot linkage command intersection operation, etc. the invention realizes the intersection signal control optimization and the intelligent robot linkage command through the sensing, cognition and behavior control of the intelligent robot.
- the intelligent robot senses and recognizes the intersection, enters the steady-state intersection signal timing control optimization scheme, and runs the intersection signal timing optimization scheme for three cycles, and at the same time, the intersection signal is matched.
- the time control optimization scheme and the intelligent robot linkage command intersection are in normal operation, and the intersection signal control optimization and the intelligent robot linkage command are realized.
- the method for controlling the intersection signal control optimization scheme and the intelligent robot linkage command according to the embodiment of the invention comprises the following steps:
- the traffic control of the supersaturated intersection group should be combined with the intersection group state recognition algorithm to identify the supersaturation state of the intersection group.
- the cause of the over-saturation state of the intersection group should be determined first. If the intersection group is over-saturated due to the individual crossover Because of the traffic design, the negative effects such as overflow or green light release should be adopted.
- Corresponding traffic management control measures should be adopted to eliminate traffic congestion as soon as possible. If the traffic volume is too large, interception or current limit should be carried out at the intersection boundary.
- optimizing the traffic timing scheme of each intersection it is necessary to make full use of the traffic flow capacity of the road network to ensure smooth running of the traffic, so that the congestion can be dissipated as soon as possible. If the formation of the supersaturated state of the intersection group has been regularized, it is necessary to analyze the traffic demand within the overall scope of the city, reduce the traffic of the bottleneck section by improving the supply of traffic facilities and traffic management measures, and combined with traffic guidance. flow.
- the selection of the coordinated control period of the critical path of the intersection group is the key task of the coordinated control of the supersaturated state signal. Selecting the length of the non-optimal signal period will increase the probability of the queue overflow and blocking. In the state of steady traffic flow, the period length can be determined by parameters such as traffic volume and road capacity; while in supersaturation state, the main influencing factors of coordinated control cycle length are road segment storage capacity and red light time and green time vehicle. Arrival rate.
- the main goal of the selection of the period of the super-saturated state traffic coordination control is to avoid the phenomenon of queuing overflow at the key intersections of the intersection group, and apply the upstream interception strategy to avoid the intersection overflow phenomenon by coordinating the period length of the upstream intersection.
- the recommended period length generated by applying this strategy is the maximum period length that ensures that the shock wave formed by the queue dissipates before reaching the upstream intersection.
- FIG. 6 is a schematic diagram of a method for calculating a period length of overflow prevention according to an embodiment of the present invention.
- the present invention draws a calculation formula for calculating a maximum signal control period for preventing a queue overflow by a space-time diagram as follows:
- the length of the coordinated traffic control cycle under supersaturation should also consider the free drive rate and the length of the link under the critical path [5]. Therefore, the calculation cycle length should be:
- the period length of each intersection of the intersection group should be based on the range of the critical path coordination control period, and the signal period length is searched according to the traffic control optimization strategy and signal control constraints of the single-point intersection layer combined with the actual traffic arrival rate.
- the traffic volume of the intersection or short-connection intersection is large, short-cycle should be avoided; to avoid the queue overflow phenomenon at the short-circuit intersection, when the short-cycle cannot be used, the method of adjusting the phase difference can be used to reduce the red-light time. Arrival rate. Also extending the green time of the downstream intersection to create a shut-off effect at the upstream intersection also avoids the problem of queue overflow.
- the short-term intersection has a limitation on the length of the cycle when the traffic volume is high as follows.
- Equation (18) j- phase difference of one cycle; yj, y' j - flow ratio of j -th phase to design flow ratio; qd-design traffic volume, unit pcu/h; sd-design saturation flow, unit Pcu/h.
- intersection group coordinated traffic control reference period length takes the minimum of the above condition period:
- the phase difference optimization can be regarded as the optimization problem with the phase difference as the optimization parameter.
- the goal is that the value of a complex function is the largest or the smallest.
- the phase difference of the critical path should be optimized.
- each road segment in the intersection group is divided into several paths and optimized according to the importance of the critical path.
- the number of phase differences that may exist is (C/r)n-1, C is the period length (s), and r is the search step size (s). Therefore, the computational complexity of solving the phase difference is exponentially increasing in n, and an efficient optimization method is needed [6].
- the Link-Pivoting Combination Method (LPCM) is used to optimize the critical path of urban road intersections. The phase difference.
- the line-axis combination method uses a series of search and combination steps to make the road network equivalent to a road segment. Each combination is equivalent to converting an additional road segment into the same road segment as the previous road segment, so as to directly utilize the road segment optimized by the previous road segment.
- the flow rate is more suitable for the trunk line group in the central city. It optimizes the phase difference of the traffic signal control network in the form of a combination of "series" and "parallel".
- Step 1 Define the actual intersection Jo at the starting point of the optimized trunk road
- Step 2 sequentially combine the intersections on the dry line network according to the following process
- Step 3 For an isolated system, the adjustment set ⁇ j ⁇ of the phase difference can be specified to a specific value in order to specify that the phase difference of the intersection reaches the requirement.
- Optimizing the phase difference of the supersaturated intersection group requires, in particular, the limitation of the capacity of the downstream intersection and the intersection of other re-steering traffic flows that flow into the critical path.
- the optimization of the phase difference of the intersection group in the supersaturated state requires consideration of two constraints on the basis of the original scheme: that is, the phase difference is designed to prevent the overflow phenomenon and the green light floating phenomenon at the intersection.
- the optimization of the green letter ratio is the most active and frequent parameter in the adjustment of the four parameters (cycle, phase phase sequence, green signal ratio, phase difference) of the traffic signal control system.
- the key content of the single-point intersection green letter ratio optimization real-time adaptive control is as follows:
- the ratio of the effective green time of the signal phase to the period duration is defined as the filtering ratio of the signal phase, ie
- ⁇ is the green signal ratio
- C is the signal period duration
- ge is the effective green time
- ge g (green time) + A (yellow time)-L (start loss time)
- start loss time after the signal period C is determined, the green
- the optimization of the signal ratio ⁇ is to optimize the effective green time ge, and after determining the green time g, the ge is determined at the same time. In this paper, the optimization ge is to determine the optimization g.
- Vehicle detectors are buried in the upstream and downstream of each entrance line of the intersection;
- the green time of the phase can be determined by offline optimization, or the scheme of the previous time period can be called.
- the online optimization and adjustment can be continuously performed, and the optimization algorithm gradually conforms to the actual running state of the traffic flow.
- the ratio of the optimal green signal ratio of each phase of different signal periods is roughly proportional to the ratio of phase saturation flow ratio:
- gi, gj represent the optimal green signal ratio of phase i, j; yi, yj represent the saturation flow ratio of phase i, j; qi, qj represent the flow of phase i, j, si, sj represent The saturation flow of phase i, j. Therefore, in the case that the signal period has been optimized and determined, the initial value of the green signal ratio under the single-point real-time adaptive control can be determined according to the principle of equal saturation distribution and the ratio of the saturation flow ratio of each phase.
- the constraints of the green letter ratio optimization are mainly signal period constraints, maximum and minimum green time constraints, and traffic capacity constraints:
- the green letter ratio is a multi-dimensional vector whose dimension is equal to the number of phases. Therefore, in the green letter ratio optimization, we must consider how to simplify the complexity and memory overhead of multidimensional space optimization while ensuring the optimization accuracy.
- the allocation of green signal ratio usually has the following methods:
- a.Saturation time-matching method based on the principle of fairness, according to the saturation flow ratio as the basis for optimization of green-tone ratio, it has the characteristics of simple, fast and approximate optimal, but the traffic efficiency and service level are not as good as the total delay. .
- Total delay minimization timing method Based on the principle of efficiency, the green letter ratio distribution is the best, and the traffic efficiency and service level are the best, but the calculation time is long and the model requirements are complex.
- the average delay time of the car is delayed: the delays of the cars in each phase are equal.
- the queuing rate is equal to the time method: the queuing rate of each phase traffic is equal.
- the optimization method based on the total delay minimization of equal saturation allocation is selected, and the green letter ratio of the equal saturation distribution is used as the initial green signal ratio of the system optimization, and then the optimal green signal ratio is gradually approached.
- the green letter ratio optimization operation process can be divided into three stages:
- the signal period duration is initially allocated according to the ratio of the saturated flow ratio of each phase, and the sum of the green signal ratios of each phase obeys the signal period constraint.
- maximum and minimum green light duration, maximum critical saturation constraint :
- m represents the number of phases of the intersection
- qi represents the traffic volume of the i-th phase
- Si represents the saturation flow rate of the i-th phase.
- the green light timing should be increased; otherwise, the green time should be reduced.
- the optimization of the green letter ratio starts from the extended phase green signal ratio on the main road of the intersection, and uses the hill climbing method to compare the green letter ratio performed in the previous cycle before the green light is turned on, searching for + ⁇ gs, 0, - ⁇ gs In the case of the change of the delay size of the intersection, find the green-tone ratio fine-tuning scheme with the smallest delay.
- the detector Since the detector is installed upstream and downstream of the system, it is possible to save the green light time according to the induction control, and redistribute the green time of the surplus to obtain better benefits and further reduce the delay value of the system.
- Three types of phases are established: extended phase, inductive phase, and basic phase; the purpose is mainly to facilitate the proper adjustment of the green light time of each phase in the induction control, and to preferentially allocate the green time of the non-extended phase to the extended phase with a large traffic volume.
- the extended phase is usually set in the main road with large traffic volume or large saturation flow ratio.
- the final green time can only be determined after the green signal ratio of other phases is determined, which is equal to the period time minus the remaining time after all other phases.
- the total number of extended phases should typically be less than the total number of set sensing phases.
- the extended phase After the extended phase is introduced, it is necessary to set the extended phase immediately after the inductive phase. When the inductive phase is skipped or there is excess green light savings, the extended phase can obtain the full green time of the induced phase. Conversely, setting the extended phase before the inductive phase is completed is not desirable because when the induced phase has not reached the maximum green light, the residual green time cannot be adjusted to extend the phase to ensure that the optimized cycle time is performed.
- a main path direction can usually be set to at most one extended phase, and it is not necessary to set an extended phase for each coordination direction, especially in the case of two phases.
- the basic phase is only the phase introduced to specify the direction in which the adjustment is performed, and it is not necessary to set the basic phase for each intersection, especially in the case of two phases. If the sensing control phase is skipped in the previous cycle, the minimum green time when the general phase is set is assigned to the initial optimized inductive phase green signal ratio at the green signal ratio optimization of the next cycle.
- the above content is mainly to describe the green letter ratio optimization in the case of single extended phase, but there will be cases where the extended phase is not unique. For example, there is a typical four-phase situation at a large intersection where two main roads intersect. At this time, there are two extended phases, and the two-way hill climbing method can be used for optimal search, and the optimal green signal ratio with the minimum delay is obtained. At this time, the green light distribution is performed according to equal saturation for all non-extended phases, and the green light distribution is performed according to equal saturation for all extended phases, but it is not equivalent to the completion of saturation between all phases in the case of calculating the initial green signal ratio, but the same phase. Relatively equal saturation.
- g1 and g3 be the green-to-signal ratios of non-extended phase 1 and 3
- g2 and g4 be the green-to-signal ratios of extended phase 2 and 4.
- the optimized search for the green-tone ratio uses the bidirectional mountain climbing method. Then there are:
- the double-extended phase green-tone ratio optimization uses the two-way hill climbing method, and its optimization objective function is:
- d(g1), d(g3), and d(g4) represent respective non-extended phase delay values obtained by the hill climbing method in the extended phase g2 direction; d(g11), d(g33), d (g44) represents each non-extended phase delay value obtained by the hill climbing method along the extended phase g4 direction; ⁇ g2 represents a search step length of the extended phase 2; ⁇ g4 represents a search step length of the extended phase 4; Representing the extended green signal ratio of the previous signal of phase 2; Represents the green signal ratio that is performed by a signal on the phase 4 extension.
- the adjustment interval of the green letter ratio In order to minimize the delay in the final determination of the signal period, it must be matched in real time to the changing traffic conditions of the various incoming connections.
- the adjustment interval of the green letter ratio When the adjustment interval of the green letter ratio is too long, the real-time performance is poor, and the system should be too lagging behind the change in traffic demand of each phase.
- the green letter ratio adjustment interval is too short, frequent adjustment will bring instability to the system operation. Since the optimal interval of the signal period as the main parameter of the strategy is two cycles, and the green-tone ratio is a pure tactical parameter, the adjustment interval should be lower than the signal period, so the optimization of the green-tone ratio is once per cycle.
- the optimization time of the green signal ratio generally optimizes the green signal ratio of the next cycle before the end of the signal of the cycle.
- the advance time T is composed of the following two parts: The first is system optimization. The time T1 required for the operation depends on the performance of the algorithm, the calculation scale, and the hardware configuration. The second is the time T2 required for the execution of the system scheme: determined by the communication transmission time and the signal decoding time.
- FIG. 7 is a schematic structural diagram of a traffic control system based on an intersection group according to an embodiment of the present invention.
- the traffic control system based on the intersection group of the embodiment of the present invention includes an intelligent robot including a first video camera module 1, a second video camera module 2, a data processor module (not shown), and a display module 3;
- the video camera module 1 and the second video camera module 2 are respectively connected to the data processor module and the display module 3; the first video camera module 1 and the second video camera module 2 are used for real-time dynamic acquisition of the 360° panoramic video of the intersection, and
- the captured video data is transmitted to the data processor module and the display module 3.
- the data processor module is configured to establish an intersection operation model according to the video data, perform an operation situation monitoring on the intersection operation model, and analyze the intersection group according to the intersection operation model. According to the traffic characteristics, the intersection evaluation index and online simulation analysis are carried out according to the traffic characteristics of the intersection group, and the traffic operation state of the intersection group is identified, so that the signal path timing control scheme of the supersaturated intersection is optimized for the critical path of the supersaturated intersection group.
- Adjust the traffic signal control strategy of the supersaturated intersection group and control the intelligent machine People running adjusted intersection group traffic signals The control strategy realizes the steady-state operation of the intersection control signal timing optimization scheme and the intelligent robot linkage command to solve the single-point operation optimization problem of the urban road over-saturation intersection; the display module 3 is used to display the first video camera module 1 and the second Video data captured by the video camera module 2.
- the first video camera module 1 is a 360° panoramic HD video camera that is highly scalable, and is disposed above the head of the intelligent robot.
- the second video camera module 2 is a high-definition video camera and is disposed on the intelligent robot.
- the display module 3 is a touch display screen, which is located in the body part of the intelligent robot, and is convenient for manual touch operation.
- FIG. 8 is a schematic structural diagram of a data processor module according to an embodiment of the present invention.
- the data processor module of the embodiment of the present invention includes a model establishing unit, a traffic characteristic analyzing unit, a traffic running state identifying unit, a strategy optimizing unit, and a solution running unit; specifically:
- the model establishing unit is configured to receive video data transmitted by the first video camera module and the second video camera module, and perform processing such as classification, image recognition and feature extraction on the video data to generate an intersection real-time dynamic information environment, and establish a clear picture. , an open-ended intersection operation model;
- the traffic characteristic analysis unit is used to monitor the operation situation of the intersection operation model, and analyze the traffic characteristics of the intersection group according to the intersection operation model; wherein the method for monitoring the operation situation of the intersection operation model includes: analyzing the congestion formation of the intersection group And evacuation mechanism and collection and processing of traffic operating parameters;
- the analysis of the congestion formation and evacuation mechanism of the intersection group includes: analyzing the induced factors of the intersection group congestion, determining the influence of the intersection overflow, the green light release, the detention queue and other adverse effects on the traffic congestion of the intersection group, and determining the supersaturation state formation.
- the collection and processing of traffic operation parameters include: determining the traffic operation parameters needed to analyze the traffic operation state of urban road intersections, and comparing the advantages and disadvantages of various traffic operation parameters collection methods and the adaptability to supersaturated traffic signal control. Optimize the data sources needed for traffic status identification and traffic control at intersections; establish traffic operation parameter cleaning and processing methods, determine traffic flow loss data completion, traffic flow error data identification, correction, and traffic flow redundancy data reduction algorithm To lay the foundation for traffic state analysis.
- the method for collecting and processing traffic operation parameters according to the embodiment of the present invention specifically includes video vehicle detection and traffic correlation index modeling;
- the specific method of video vehicle detection is:
- Target segmentation separating the target to be identified from the background by recognizing pixels in the image that conform to the characteristics of the vehicle;
- Post-processing calculate traffic operation parameters such as vehicle flow rate and vehicle speed according to the detection requirements.
- Traffic correlation indicators include discrete correlation indicators and retardation correlation indicators
- Discrete correlation indicators are: affected by the discrete factors of traffic flow, if the downstream intersections must ensure that the first and last vehicles of the fleet pass through the intersection during the same green time, it is necessary to design a diffused widened green wave belt. However, this design makes the green light time of the most downstream intersection unacceptably long. It is a control method that does not constrain the discreteness, and is often not desirable in practical engineering applications. For the control method of discrete constraints, the equal-width green wave is often used, but this method will cause some vehicles at the head or tail of the traffic flow to have certain delays at each intersection.
- the discrete correlation index I1 is set as the ratio of the long green time of the vehicle such as the starting and ending points in a signal control period, that is:
- q0(i) represents the number of traffic passing through the i-term of the initial upstream intersection stop line of a certain path
- qd(i+T) represents the number of traffic arrivals at the i+Tth time of the end of the path.
- T represents the journey from the beginning to the end of the route Time
- tg represents the duration of the green wave in a signal period.
- Q0(i) and qd(i+T) can be used for field observations or by Robertson's fleet discrete formula, ie:
- the block correlation index is: for any segment m of an intersection group forming a certain road, if there are N different flow directions at the intersection entrance path along the forward direction of the path, calculate the functional zone length value of each flow direction. the length of queue
- the field observation statistics may be used, or the queuing length calculation formula may be used for estimation.
- the queuing length calculation method of Synchro7 is adopted, and the deceleration distance is used.
- And perception-reaction distance Calculation method will It is defined as the ratio of the maximum value of the flow direction functional zone to the path length L in the entrance of the intersection of the road segment m along the path of the path, namely:
- the retardation index I2 is:
- the way to analyze the traffic characteristics of the intersection group is to understand the traffic characteristics of the intersection group from the geometric topological characteristics, road space characteristics, traffic flow characteristics and traffic signal control characteristics of the intersection group, and to find the change of traffic flow in the intersection group.
- the geometrical topological characteristics of the intersection group classify the intersection group according to the number of road paths between the two intersections in the intersection group; the characteristics of the road space design analyze the impact of the road traffic facility design on the traffic flow operation; The description model for the urban road interruption in supersaturated state is given.
- the appropriate traffic operation data collection means is selected to establish the data cleaning and processing method. Traffic signal control characteristics analysis basic control principle and control structure, laid the foundation for the establishment of traffic control methods.
- the traffic operation state identification unit is configured to perform an intersection evaluation index and an online simulation analysis according to the traffic characteristics, and identify the traffic operation state of the intersection group; wherein the traffic operation state recognition unit identifies the intersection traffic state of the intersection group includes: the intersection group range Definition, intersection group over-saturation recognition and evaluation, intersection group critical path detection and classification, and short-term prediction modeling and simulation of traffic parameters;
- intersection groups are as follows:
- intersections with strong correlations should be divided into an intersection group, and intersections with weak correlation should be divided into different intersection groups;
- the method for defining the range of the intersection group specifically includes: analyzing the traffic characteristics of the intersections in the intersection group based on the spatial characteristics of the intersection group and the internal correlation mechanism, and establishing a feature matrix based on the feature matrix.
- Intersection group scoping method and intersection method based on self-organizing neural network.
- the correlation between the queue length of the vehicle and the spatial distance of the intersection and the effective utilization of the green time are respectively used to describe the association characteristics of the intersection group.
- the former combines the flow factor and the distance factor, and the latter takes into account the flow factor and the timing factor.
- a feature analysis method that defines the extent of the intersection group.
- the method of identifying and evaluating the over-saturation state of the intersection group is as follows: based on the method of analyzing the degree of supersaturation of the intersection group, the ratio of the invalid green time and the total green time caused by the negative effect is proposed to define the supersaturation index, and Measure the degree of supersaturation of the intersection group. Based on the characteristics of the negative effects produced by the supersaturated state intersection group in the spatial dimension and the time dimension, the supersaturation index of the intersection group is calculated in the spatial and temporal dimensions respectively. In the spatial dimension, the shock wave model and the space-time map are used to calculate the maximum queuing length of the intersection from the shock wave generated when the queuing starts to dissipate and the departure shock wave generated when the green wave starts.
- the shock wave generated by the queuing starts to dissipate and the lower period red light starts.
- the parking shock wave generated at the time calculates the tributary length of the intersection, and calculates the supersaturation coefficient of the spatial dimension.
- the supersaturation degree coefficient of the intersection is calculated mainly by the long-time occupancy phenomenon of the upstream detector generated by the overflow of the intersection.
- the supersaturation degree of the intersection group is identified by the supersaturation degree coefficient of the spatial dimension and the time dimension.
- the supersaturation state cannot be directly identified by traffic parameter measurement or calculation, and can only be obtained indirectly through negative effects such as overflow caused by supersaturation.
- the definition of the supersaturation state of the intersection group is extended, and the supersaturation coefficient is calculated by the negative effect caused by the supersaturation state, thereby determining the supersaturation state of the intersection group.
- the supersaturation state refers to the situation when a traffic facility controlled by a traffic signal has a traffic demand greater than its traffic capacity state (the maximum number of green time passes), which may be negatively affected by the retention queue of a certain cycle or the upstream traffic.
- the facility is defined by the negative effects of the overflow in one cycle, and the ratio of the ineffective green time to the total green time (supersaturation coefficient) is used to measure the degree of supersaturation.
- the over-saturation state of the intersection group is evaluated by using the induction coil traffic detection data, and the typical arrangement manner of the induction coil includes a parking line detector and an advanced detector (layed upstream of the parking line).
- the intersection group is queued long. No matter whether the parking line detector or the advanced detector can accurately detect the traffic organization that identifies the supersaturated intersection, the parameter estimation method is needed to identify the supersaturation state of the intersection group.
- the negative effects of traffic control in the supersonic state are used to replace the traditional estimation method to evaluate the state of the traffic facilities.
- the negative effects identified by the algorithm mainly include the length of the stagnation queue at the end of the signal period and the overflow phenomenon at the upstream intersection.
- Shockwave shockwave
- QOD Queue Over Detector
- the wave velocity (u2, u3, u4) is also used to calculate the maximum queue length in one cycle. Because the variance of traffic arrival flow rate is large, the queuing shock wave (u1) is not suitable for estimating the queue length.
- the queuing length is estimated by using the shock wave (u2) and the back shock wave (u3).
- the calculation formula is:
- qm and km represent the flow rate and density at the maximum flow rate, respectively, and kj represents the plugging density.
- High-resolution traffic data is used to estimate including Various traffic variables including qm, km, where traffic flow rate data, such as And qm can be obtained directly by the detector, but The density data of km and so on must be estimated.
- Event-based traffic data can provide a separate occupancy time, assuming that the effective vehicle length is known, the spatial average speed can be obtained; at this point, the average flow rate can be divided by the space average vehicle speed to estimate the density data.
- the methods for estimating individual velocity ui, spatial average velocity us, flow rate q and density k are:
- t0, i and tg, i represents the detector occupancy time and time interval of vehicle i
- ui and hi represent the speed and head spacing of vehicle i
- q, us and k represent respectively Average flow rate, space average speed and density
- Le represents the effective length of the car
- n represents the number of vehicles in a fleet in the same traffic state.
- Ld represents the distance between the stop line and the detector.
- the method of detecting and classifying the critical path of the intersection group is as follows: based on the characteristics of the strong traffic correlation of the fleet in the intersection group, the intersection path group identification method based on wavelet transform and spectrum analysis is used to analyze and extract the intersection group traffic flow.
- the short-term variation characteristic is used to detect the critical path of the intersection group by means of data mining analysis, and to classify the intersection group path.
- the wavelet transform technology is used to decompose the traffic signal according to different frequencies, and the high-frequency signal reflecting the short-term variation characteristics of the traffic flow and the low-frequency signal reflecting the change characteristics of the traffic flow are retained.
- the filtered traffic signal is reconstructed into a new traffic signal that highlights the short-term variation characteristics of the traffic flow as input data for critical path identification and classification.
- the correlation degree of the two traffic signals is determined, and the critical degree index corresponding to all the paths of the designated import is obtained, and then the phase between the two signals is calculated, and the travel time verification calculation of the two points is effective.
- Sexuality comprehensive analysis of the importance of all import critical paths.
- the traffic correlation of intersections in the intersection group is mainly reflected in the degree of dispersion of traffic flow between intersections, that is, the similarity of arrival traffic characteristics and upstream traffic characteristics of downstream intersections.
- the similarity is more obvious on the critical path.
- the wavelet transform method is used to decompose the traffic signal according to different frequencies, and the high-frequency signal reflecting the short-term variation characteristics of the traffic flow and the low-frequency signal reflecting the change characteristics of the traffic flow are retained.
- the filtered traffic signal is reconstructed into a new traffic signal that highlights the short-term change characteristics of the traffic as input data for critical path identification and classification.
- Wavelet transformation (Wavelet Transformation) is a localized analysis of time (space) frequency.
- Wavelet transform is a time-frequency resolution in which the window size is fixed and its shape is variable, and both the time window and the frequency window can be changed, while the high frequency portion has higher time resolution and lower frequency resolution.
- the wavelet transform inherits and carries forward the idea of localization of short-time Fourier transform, and at the same time overcomes the shortcomings of window size without frequency variation, etc. It can provide a time-frequency window with frequency change, and analyze and process the signal time-frequency.
- the ideal tool Its main feature is that it can successfully highlight some aspects of the problem through transformation, and has been successfully applied in many fields.
- the wavelet transform is the weighted sum of the signals to be analyzed into a family of wavelet machines, and its meaning is the mother wavelet function.
- the inner product is compared with the signal f(t) to be analyzed at different scales ⁇ :
- the spectrum analysis method is used to take the traffic flow change as the input signal, and analyze the spectrum variation characteristics at different frequencies.
- the consistency coefficient of the signals is analyzed to determine the correlation between the two traffic signals, and the phase difference between the two signals is applied to judge the effectiveness of the algorithm.
- the spectrum refers to the representation of a time domain signal in the frequency domain, which can be obtained by Fourier transform of the signal.
- the obtained conclusions are that the amplitude or phase is the vertical axis and the frequency is the horizontal axis.
- the amplitude spectrum shows the amplitude as a function of frequency
- the phase spectrum shows the phase as a function of frequency.
- the spectrum can represent the frequency of a string of sine waves, as well as the size and phase of each frequency sine wave.
- Spectral analysis is a technique for decomposing complex signals into simpler signals. Finding the information of a signal at different frequencies (such as amplitude, power, intensity, phase, etc.) is a bit-spectrum analysis.
- the power spectrum is a characterization of the energy distribution characteristics of digital time series at different frequencies, if the time series self-covariance function ⁇ k satisfies the condition Then there is the following correspondence between the power spectral density f( ⁇ ) and ⁇ k: Where: f( ⁇ ) is defined on [- ⁇ , ⁇ ] and is a real-valued non-negative function.
- the specific methods of short-term prediction modeling and simulation of traffic parameters are: applying improved exponential smoothing method, state space neural network, extended Kalman filtering method and data fusion method to predict the changing characteristics of short-term traffic parameters of intersection group.
- the traffic data of the current time period and the historical time period By using the traffic data of the current time period and the historical time period, the traffic data of the next time period is predicted, and the model is not limited by the supersaturation state.
- Short-term prediction of traffic parameters plays an important role in the design of dynamic traffic control algorithms. The accuracy of prediction has a significant impact on the effectiveness of traffic control algorithms. According to the different basic methods of prediction, the short-term traffic flow prediction model is divided into two types: data-driven and model-based.
- Data-driven methods are processed by mathematical statistics or artificial intelligence methods, such as traffic flow, traffic speed, travel time and other historical traffic data, and predict changes in traffic flow in the future; model-based methods mainly apply traffic flow propagation model to Xue Ding
- the traffic flow state on the path is estimated and predicted.
- the model can be divided into three types: macroscopic model, mesoscopic model and microscopic model.
- the method applied to short-term prediction of traffic parameters has various forms and effects.
- SSNN State Space Neural Network
- extended Kalman filter is adopted.
- the state space neural network adds a state layer that stores the state of the previous neuron as a short-term memory layer, so that the neural network can determine the predicted output value according to the current state and the state of the previous moment. Efficiently learn complex time and space states.
- the vector s(t) of the hidden layer is known.
- sm represents the value of the mth hidden layer neuron
- bm represents the deviation value of the mth hidden layer neuron
- its value is fixed at 1
- h( ⁇ ) represents the transfer function.
- the strategy optimization unit is configured to perform optimization and induction of the oversaturated intersection signal timing control scheme for the critical path of the supersaturated intersection group, and adjust the supersaturated intersection intersection group traffic signal control strategy; wherein the supersaturation of the embodiment of the present invention
- the intersection critical path and control strategy optimization methods include: static optimization of intersection signal timing optimization scheme, dynamic coordinated traffic signal control intersection group, stratified screening of traffic control strategy of supersaturated intersection group, inheritance based on non-dominated sorting Algorithm optimization coordination timing scheme, real-time dynamic optimization algorithm of traffic parameters;
- intersection signal timing optimization scheme is statically optimized; in the supersaturated state, the steady-state traffic control makes the traffic flow smooth and the optimization target is no longer applicable.
- This paper analyzes the applicability of optimization targets with the largest number of critical routes and the minimum queue length in over-saturated state traffic control, and determines the traffic control optimization objectives, which lays a foundation for the optimization of traffic control parameters.
- Combining the supersaturated intersection group needs to optimize the control target of traffic flow in the bottleneck section, and select the hierarchical traffic control structure in traffic control, and divide it into intersection group layer, key path layer and single point intersection layer.
- the internal traffic flow of the intersection group is quickly evacuated by means of current limiting and adaptive control, and the external traffic flow is appropriately restricted.
- the key path layer pays attention to the coordination signal timing of the most prominent path of the intersection group traffic problem.
- the scheme; the single-point intersection layer optimizes the timing parameters according to the real-time traffic parameters and the coordinated control scheme of the critical path layer through the signal at the intersection, and finally determines the optimization scheme of the intersection timing signal timing control.
- the traffic control strategy of the supersaturated intersection group is hierarchically screened; according to the three-layer hierarchical optimization control model of the intersection group, the traffic control strategy suitable for supersaturation state is selected in the existing control strategy.
- the traffic control strategies of the single-point intersection layer include green light delay, early termination phase, phase re-service, dynamic left turn, left turn phase advance/shift, and short-circuit intersection with the same timing scheme; key path layer Including reverse coordination control, synchronous traffic control, green flash and prevent overflow, green light empty phase difference design, etc.; intersection group layer control strategy is mainly limited flow, adaptive control.
- the non-dominated sorting genetic algorithm optimizes the coordinated timing scheme; as the benchmark timing scheme for signal control dynamic optimization, based on the offline data of the intersection group operation, according to the traffic control target of the supersaturated state, the weighted passage of the critical path is selected. The maximum number of vehicles and the minimum number of critical routes are optimized. The green time of each intersection is used as the input variable.
- the second generation multi-objective non-dominated sorting genetic algorithm is used to optimize the coordination timing scheme as the reference timing for signal control dynamic optimization. Program.
- Real-time dynamic optimization algorithm for traffic parameters based on traffic state information, short-term traffic flow prediction results, and value range of key control parameters, based on the reference control scheme, dynamically adjust the value of traffic control parameters based on real-time traffic data, and Perform a time-consuming analysis of each step.
- the cycle length can be adjusted to avoid the intersection of the discrete shock wave and the queuing dissipative shock wave before the upstream intersection, thereby avoiding the purpose of avoiding the queue;
- the phase difference between the two intersections also avoids the occurrence of overflow and green light. Apply this method to obtain the range of values of each traffic parameter, which can be used as The range of values that are dynamically optimized by parameters.
- the solution operation unit is configured to run the adjusted intersection group traffic signal control strategy, and realize the intersection operation of the intersection control signal timing optimization scheme and the intelligent robot linkage command; specifically, the intersection signal control optimization scheme of the embodiment of the present invention
- the methods of intelligent robot linkage command include:
- the traffic control of the supersaturated intersection group should be combined with the intersection group state recognition algorithm to identify the supersaturation state of the intersection group.
- the cause of the over-saturation state of the intersection group should be determined first. If the intersection group is over-saturated due to the individual crossover Because of the traffic design, the negative effects such as overflow or green light release should be adopted.
- Corresponding traffic management control measures should be adopted to eliminate traffic congestion as soon as possible. If the traffic volume is too large, interception or current limit should be carried out at the intersection boundary.
- optimizing the traffic timing scheme of each intersection it is necessary to make full use of the traffic flow capacity of the road network to ensure smooth running of the traffic, so that the congestion can be dissipated as soon as possible. If the formation of the supersaturated state of the intersection group has been regularized, it is necessary to analyze the traffic demand within the overall scope of the city, reduce the traffic of the bottleneck section by improving the supply of traffic facilities and traffic management measures, and combined with traffic guidance. flow.
- the selection of the coordinated control period of the critical path of the intersection group is the key task of the coordinated control of the supersaturated state signal. Selecting the length of the non-optimal signal period will increase the probability of the queue overflow and blocking. In the state of steady traffic flow, the period length can be determined by parameters such as traffic volume and road capacity; while in supersaturation state, the main influencing factors of coordinated control cycle length are road segment storage capacity and red light time and green time vehicle. Arrival rate.
- the main goal of the selection of the period of the super-saturated state traffic coordination control is to avoid the phenomenon of queuing overflow at the key intersections of the intersection group, and apply the upstream interception strategy to avoid the intersection overflow phenomenon by coordinating the period length of the upstream intersection.
- the recommended period length generated by applying this strategy is the maximum period length that ensures that the shock wave formed by the queue dissipates before reaching the upstream intersection.
- the length of the coordinated traffic control cycle under supersaturation should also consider the free drive rate and the length of the link under the critical path [5]. Therefore, the calculation cycle length should be:
- the period length of each intersection of the intersection group should be based on the range of the critical path coordination control period, and the signal period length is searched according to the traffic control optimization strategy and signal control constraints of the single-point intersection layer combined with the actual traffic arrival rate.
- the traffic volume of the intersection or short-connection intersection is large, short-cycle should be avoided; to avoid the queue overflow phenomenon at the short-circuit intersection, when the short-cycle cannot be used, the method of adjusting the phase difference can be used to reduce the red-light time. Arrival rate. Also extending the green time of the downstream intersection to create a shut-off effect at the upstream intersection also avoids the problem of queue overflow.
- the short-term intersection has a limitation on the length of the cycle when the traffic volume is high as follows.
- Equation (18) j- phase difference of one cycle; yj, y' j - flow ratio of j -th phase to design flow ratio; qd-design traffic volume, unit pcu/h; sd-design saturation flow, unit Pcu/h.
- intersection group coordinated traffic control reference period length takes the minimum of the above condition period:
- the phase difference optimization can be regarded as the optimization problem with the phase difference as the optimization parameter.
- the goal is that the value of a complex function is the largest or the smallest.
- the phase difference of the critical path should be optimized.
- each road segment in the intersection group is divided into several paths and optimized according to the importance of the critical path.
- the number of phase differences that may exist is (C/r)n-1, C is the period length (s), and r is the search step size (s). Therefore, the computational complexity of solving the phase difference is exponentially increasing in n, and an efficient optimization method is needed [6].
- the Link-Pivoting Combination Method (LPCM) is used to optimize the critical path of urban road intersections. The phase difference.
- the line-axis combination method uses a series of search and combination steps to make the road network equivalent to a road segment. Each combination is equivalent to converting an additional road segment into the same road segment as the previous road segment, so as to directly utilize the road segment optimized by the previous road segment.
- the flow rate is more suitable for the trunk line group in the central city. It optimizes the phase difference of the traffic signal control network in the form of a combination of "series" and "parallel".
- Step 1 Define the actual intersection Jo at the starting point of the optimized trunk road
- Step 2 sequentially combine the intersections on the dry line network according to the following process
- Step 3 For an isolated system, the adjustment set ⁇ j ⁇ of the phase difference can be specified to a specific value in order to specify that the phase difference of the intersection reaches the requirement.
- Optimizing the phase difference of the supersaturated intersection group requires, in particular, the limitation of the capacity of the downstream intersection and the intersection of other re-steering traffic flows that flow into the critical path.
- the optimization of the phase difference of the intersection group in the supersaturated state requires consideration of two constraints on the basis of the original scheme: that is, the phase difference is designed to prevent the overflow phenomenon and the green light floating phenomenon at the intersection.
- the optimization of the green letter ratio is the most active and frequent parameter in the adjustment of the four parameters (cycle, phase phase sequence, green signal ratio, phase difference) of the traffic signal control system.
- the key content of the single-point intersection green letter ratio optimization real-time adaptive control is as follows:
- the ratio of the effective green time of the signal phase to the period duration is defined as the filtering ratio of the signal phase, ie
- ⁇ is the green signal ratio
- C is the signal period duration
- ge is the effective green time
- ge g (green time) + A (yellow time)-L (start loss time)
- start loss time after the signal period C is determined, the green
- the optimization of the signal ratio ⁇ is to optimize the effective green time ge, and after determining the green time g, the ge is determined at the same time. In this paper, the optimization ge is to determine the optimization g.
- Vehicle detectors are buried in the upstream and downstream of each entrance line of the intersection;
- the green time of the phase can be determined by offline optimization, or the scheme of the previous time period can be called.
- the online optimization and adjustment can be continuously performed, and the optimization algorithm gradually conforms to the actual running state of the traffic flow.
- the ratio of the optimal green signal ratio of each phase of different signal periods is roughly proportional to the ratio of phase saturation flow ratio:
- gi, gj represent the optimal green signal ratio of phase i, j; yi, yj represent the saturation flow ratio of phase i, j; qi, qj represent the flow of phase i, j, si, sj represent phase i, j Saturated flow. Therefore, in the case that the signal period has been optimized and determined, the initial value of the green signal ratio under the single-point real-time adaptive control can be determined according to the principle of equal saturation distribution and the ratio of the saturation flow ratio of each phase.
- the constraints of the green letter ratio optimization are mainly signal period constraints, maximum and minimum green time constraints, and traffic capacity constraints:
- the green letter ratio is a multi-dimensional vector whose dimension is equal to the number of phases. Therefore, in the green letter ratio optimization, we must consider how to simplify the complexity and memory overhead of multidimensional space optimization while ensuring the optimization accuracy.
- the allocation of green signal ratio usually has the following methods:
- a.Saturation time-matching method based on the principle of fairness, according to the saturation flow ratio as the basis for optimization of green-tone ratio, it has the characteristics of simple, fast and approximate optimal, but the traffic efficiency and service level are not as good as the total delay. .
- Total delay minimization timing method Based on the principle of efficiency, the green letter ratio distribution is the best, and the traffic efficiency and service level are the best, but the calculation time is long and the model requirements are complex.
- the average delay time of the car is delayed: the delays of the cars in each phase are equal.
- the queuing rate is equal to the time method: the queuing rate of each phase traffic is equal.
- the optimization method based on the total delay minimization of equal saturation allocation is selected, and the green letter ratio of the equal saturation distribution is used as the initial green signal ratio of the system optimization, and then the optimal green signal ratio is gradually approached.
- the green letter ratio optimization operation process can be divided into three stages:
- the signal period duration is initially allocated according to the ratio of the saturated flow ratio of each phase, and the sum of the green signal ratios of each phase obeys the signal period constraint.
- maximum and minimum green light duration, maximum critical saturation constraint :
- m represents the number of phases of the intersection
- qi represents the traffic volume of the i-th phase
- Si represents the saturation flow rate of the i-th phase.
- the green light timing should be increased; otherwise, the green time should be reduced.
- the optimization of the green letter ratio starts from the extended phase green signal ratio on the main road of the intersection, and uses the hill climbing method to compare the green letter ratio performed in the previous cycle before the green light is turned on, searching for + ⁇ gs, 0, - ⁇ gs In the case of the change of the delay size of the intersection, find the green-tone ratio fine-tuning scheme with the smallest delay.
- the detector Since the detector is installed upstream and downstream of the system, it is possible to save the green light time according to the induction control, and redistribute the green time of the surplus to obtain better benefits and further reduce the delay value of the system.
- Three types of phases are established: extended phase, inductive phase, and basic phase; the purpose is mainly to facilitate the proper adjustment of the green light time of each phase in the induction control, and to preferentially allocate the green time of the non-extended phase to the extended phase with a large traffic volume.
- the extended phase is usually set in the main road with large traffic volume or large saturation flow ratio.
- the final green time can only be determined after the green signal ratio of other phases is determined, which is equal to the period time minus the remaining time after all other phases.
- the total number of extended phases should typically be less than the total number of set sensing phases.
- the extended phase After the extended phase is introduced, it is necessary to set the extended phase immediately after the inductive phase. When the inductive phase is skipped or there is excess green light savings, the extended phase can obtain the full green time of the induced phase. Conversely, setting the extended phase before the inductive phase is completed is not desirable because when the induced phase has not reached the maximum green light, the residual green time cannot be adjusted to extend the phase to ensure that the optimized cycle time is performed.
- a main path direction can usually be set to at most one extended phase, and it is not necessary to set an extended phase for each coordination direction, especially in the case of two phases.
- the basic phase is only the phase introduced to specify the direction in which the adjustment is performed, and it is not necessary to set the basic phase for each intersection, especially in the case of two phases. If the sensing control phase is skipped in the previous cycle, the minimum green time when the general phase is set is assigned to the initial optimized inductive phase green signal ratio at the green signal ratio optimization of the next cycle.
- the above content is mainly to describe the green letter ratio optimization in the case of single extended phase, but there will be cases where the extended phase is not unique. For example, there is a typical four-phase situation at a large intersection where two main roads intersect. At this time, there are two extended phases, and the two-way hill climbing method can be used for optimal search, and the optimal green signal ratio with the minimum delay is obtained. At this time, the green light distribution is performed according to equal saturation for all non-extended phases, and the green light distribution is performed according to equal saturation for all extended phases, but it is not equivalent to the completion of saturation between all phases in the case of calculating the initial green signal ratio, but the same phase. Relatively equal saturation.
- g1 and g3 be the green-to-signal ratios of non-extended phase 1 and 3
- g2 and g4 be the green-to-signal ratios of extended phase 2 and 4.
- the optimized search for the green-tone ratio uses the bidirectional mountain climbing method. Then there are:
- the double-extended phase green-tone ratio optimization uses the two-way hill climbing method, and its optimization objective function is:
- d(g1), d(g3), and d(g4) represent respective non-extended phase delay values obtained by the hill climbing method in the extended phase g2 direction; d(g11), d(g33), d (g44) represents each non-extended phase delay value obtained by the hill climbing method along the extended phase g4 direction; ⁇ g2 represents a search step length of the extended phase 2; ⁇ g4 represents a search step length of the extended phase 4; Representing the extended green signal ratio of the previous signal of phase 2; Represents the green signal ratio that is performed by a signal on the phase 4 extension.
- the adjustment interval of the green letter ratio In order to minimize the delay in the final determination of the signal period, it must be matched in real time to the changing traffic conditions of the various incoming connections.
- the adjustment interval of the green letter ratio When the adjustment interval of the green letter ratio is too long, the real-time performance is poor, and the system should be too lagging behind the change in traffic demand of each phase.
- the green letter ratio adjustment interval is too short, frequent adjustment will bring instability to the system operation. Since the optimal interval of the signal period as the main parameter of the strategy is two cycles, and the green-tone ratio is a pure tactical parameter, the adjustment interval should be lower than the signal period, so the optimization of the green-tone ratio is once per cycle.
- the optimization time of the green signal ratio generally optimizes the green signal ratio of the next cycle before the end of the signal of the cycle.
- the advance time T consists of the following two parts: First, the time T1 required for the system optimization operation depends on the performance of the algorithm, the calculation scale, and the hardware configuration. The second is the time T2 required for the execution of the system scheme: determined by the communication transmission time and the signal decoding time.
- the invention takes the dynamic traffic control optimization of the main road of the key road section optimized by the urban road network and the intersection group in the downtown area of Shenzhen as an example, as shown in FIG. 9 to FIG. 12 , wherein FIG. 9 is the central urban road network and related intersections. Group static model diagram; Figure 10 is a schematic diagram of the analysis of the status quo of the intersection traffic dynamic control; Figure 11 is the schematic diagram of the dynamic traffic control optimization of the Lianhua Road signal control intersection; Figure 12 is the dynamic traffic control optimization of the signal intersection of the Hung Hom Road schematic diagram.
- the method for optimizing the dynamic traffic control is specifically:
- Xinzhou Road an important main road in the north-south direction of the downtown area of Shenzhen, is located in the downtown area of Futian, from Furong Road in the south to Meihua Road in the north. It is responsible for the areas along the Meilin, Jingtian, Central City and Xinzhou areas.
- Xinping Road 2 plane supersaturated state intersections the entrances and exits of Lianhua Road and Hongqi Road are mostly “four changes, three changes and two changes” lanes; Xinzhou Road four interchange intersections: North Ring Interchange and Shennan Interchange
- the traffic flow between the Fumin interchange and the Binhe interchange has seriously affected the traffic of the inner main line; the main line of Xinzhou Road has a large slope, the driver's perspective is blocked, and it is not easy to find the entrance and exit; the new green road on Xinzhou Road and Hongqi Road is too long, leading to the south.
- the imported road vehicles line up to extend to the Shennan interchange; while the north exit road to Meihua Road has a low traffic density and the flow of the road section is not balanced.
- intersection control group-based traffic control method and system constructs a 360° intersection panoramic video real-time monitoring and modeling, intersection evaluation index and online simulation analysis, supersaturated intersection critical path and control strategy optimization, and crossover
- the “four-step method” method of port signal control optimization and intelligent robot linkage command is to establish a traffic control intelligent robot based on intersection group, solve the problem of single point operation optimization of urban road over-saturation intersection, and form an intelligent command city road.
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Abstract
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- 一种基于交叉口群的交通控制方法,包括以下步骤:步骤a:通过智能机器人实时动态采集交叉口360°全景视频,根据视频数据建立交叉口运行模型,并根据交叉口运行模型分析交叉口群交通特性;步骤b:根据交通特性进行交叉口评估指数与在线仿真分析,识别交叉口群交通运行状态;步骤c:对过饱和状态交叉口群的关键路径进行过饱和交叉口信号配时控制方案优化,调整过饱和状态交叉口群交通信号控制策略;步骤d:运行调整后的交叉口群交通信号控制策略,实现交叉口控制信号配时优化方案稳态运行与智能机器人联动指挥。
- 根据权利要求1所述的基于交叉口群的交通控制方法,其特征在于,所述步骤a还包括:对交叉口运行模型进行运行态势监测;所述运行态势监测方法包括:分析交叉口群拥堵形成及疏散机理及交通运行参数的采集与处理;所述交通运行参数采集与处理方法具体包括:视频车辆检测和交通关联性指标建模。
- 根据权利要求2所述的基于交叉口群的交通控制方法,其特征在于,所述步骤b中,所述识别交叉口群交通运行状态具体包括:交叉口群范围界定、交叉口群过饱和状态识别、交叉口群的关键路径检测及交通参数短时预测建模与仿真。
- 根据权利要求3所述的基于交叉口群的交通控制方法,其特征在于,在所述步骤c中,所述对过饱和状态交叉口群的关键路径进行过饱和交叉口信号配时控制方案优化方式具体包括:交叉口信号配时控制优化方案静态优化;动态协同交通信号控制交叉口群;分层筛选过饱和状态交叉口群的交通控制策略;基于非支配排序遗传算法优化协调配时方案,作为信号控制动态优化的基准配时方案;交通参数实时动态优化算法。
- 根据权利要求1所述的基于交叉口群的交通控制方法,其特征在于,在所述步骤d中,所述交叉口信号控制优化方案与智能机器人联动指挥的方法包括:城市道路过饱和交叉口群动静协同交通控制;交叉口群关键路径协调控制周期的选择;过饱和交叉口群关键路径的相位差在线优化;混合交通流对绿信比优化的影响在最大最小绿灯时间和绿灯间隔时间约束中合理考虑;建立新交叉口信号配时控制协同联动与指挥运行模式。
- 一种基于交叉口群的交通控制系统,其特征在于,包括智能机器人,所述智能机器人包括第一视频摄像模块、第二视频摄像模块和数据处理器模块;所述第一视频摄像模块和第二视频摄像模块分别与数据处理器模块连接;所述第一视频摄像模块和第二视频摄像模块用于实时动态采集交叉口360°全景视频,并将拍摄的视频数据传输至数据处理器模块,所述数据处理器模块用于根据视频数据建立交叉口运行模型,根据交叉口运行模型分析交叉口群交通特性,根据交叉口群交通特性进行交叉口评估指数与在线仿真分析,识别交叉口群交通运行状态,从而对过饱和状态交叉口群的关键路径进行过饱和交叉口信号配时控制方案优化, 调整过饱和状态交叉口群交通信号控制策略,并控制智能机器人运行调整后的交叉口群交通信号控制策略,实现交叉口控制信号配时优化方案稳态运行与智能机器人联动指挥。
- 根据权利要求7所述的基于交叉口群的交通控制系统,其特征在于,所述第一视频摄像模块为高度可以伸缩的360°全景高清视频摄像机,设于智能机器人的头部上方,所述第二视频摄像模块为高清视频摄像机,设于智能机器人的眼部。
- 根据权利要求8所述的基于交叉口群的交通控制系统,其特征在于,所述数据处理器模块包括模型建立单元、交通特性分析单元、交通运行状态识别单元、策略优化单元和方案运行单元;模型建立单元用于接收第一视频摄像模块及第二视频摄像模块传输的视频数据,并对视频数据进行归类筛选、图像识别及特征提取等处理后生成交叉口实时动态信息环境,建立画面清晰、视野开阔的交叉口运行模型;交通特性分析单元用于对交叉口运行模型进行运行态势监测,并根据交叉口运行模型分析交叉口群交通特性;交通运行状态识别单元用于根据交通特性进行交叉口评估指数与在线仿真分析,识别交叉口群交通运行状态;策略优化单元用于对过饱和状态交叉口群的关键路径进行过饱和交叉口信号配时控制方案优化与诱导,调整过饱和状态交叉口群交通信号控制策略;方案运行单元用于运行调整后的交叉口群交通信号控制策略,实现交叉口控制信号配时优化方案稳态运行与智能机器人联动指挥。
- 根据权利要求9所述的基于交叉口群的交通控制系统,其特征在于,所述智能机器人还包括显示模块,所述显示模块为触摸显示屏,位于智能机器人的身体部位,所述第一视频摄像模块和第二视频摄像模块分别与显示模块连接,所述第一视频摄像模块和第二视频摄像模块将拍摄的视频数据传输至显示模块,所述显示模块用于显示第一视频摄像模块和第二视频摄像模块拍摄的视频数据。
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