Adjacent intersection coordination control method and device based on low permeability trajectory data

Abstract

The present invention relates to a method and device for coordinated control of adjacent intersections based on low permeability trajectory data, the method comprising the following steps: step S1, obtaining low permeability trajectory data of two adjacent intersections, and calculating vehicle flow rate information; step S2, constructing a phase difference optimization model, based on the flow rate information, respectively constructing an optimization function with the goal of maximizing the average delay of the coordinated phase vehicle and minimizing the average delay of the coordinated phase vehicle to optimize the phase difference, and obtaining the maximum average delay and the minimum average delay by changing the phase difference; step S3, based on the maximum average delay and the minimum average delay, judging whether the adjacent intersections are coordinated controlled, and if so, the two adjacent intersections are coordinated controlled. Compared with the prior art, the present invention judges whether the adjacent intersections are suitable for coordinated control from the perspective of the coordinated control results.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic signal coordination control, and in particular to a method and device for coordinated control of adjacent intersections based on low-permeability trajectory data. Background Art

[0002] As a basic node in the urban road traffic network, intersections are an important bottleneck affecting road traffic efficiency. Scientific intersection signal control methods are crucial to solving traffic problems. In the urban road network, the correlation between intersections is becoming increasingly obvious. Congestion at one intersection may gradually spread to several surrounding intersections or even all intersections in the area over time. Signal coordination control is one of the most effective traffic control methods and is widely used in urban road networks. Among them, the division of coordinated sub-areas is an important part of coordinated control, and whether the division of sub-areas is reasonable is also the key to affecting the coordination effect.

[0003] With the continuous advancement of GPS technology, vehicle trajectory data has the advantages of wide coverage and low installation and maintenance costs compared to fixed detection data, and is widely used in traffic control. Trajectory data can provide real-time information such as vehicle speed and location, and also provide a new solution to the problem of coordinating sub-area division. However, the proportion of connected vehicles on the road is still small, and only low-penetration trajectory data can be provided.

[0004] The existing urban road signal coordination sub-division methods are mainly based on intersection correlation or green wave bandwidth. The intersection correlation method mainly divides the intersection based on three parameters: flow, distance, and cycle, without considering the impact of single-point signal timing on the coordination effect. The method based on green wave bandwidth requires the use of an optimization model to find the sub-division scheme with the largest bandwidth. The algorithm for solving the model is complex and the calculation speed is slow. Moreover, neither the correlation nor the green wave bandwidth can directly reflect the coordination benefits, and it is impossible to prove that the obtained sub-division scheme can make the road network obtain better benefits.

[0005] In summary, there is currently a lack of a coordinated control method for adjacent intersections under low-permeability trajectories to determine whether adjacent intersections should be coordinated after the timing plan for a single-point intersection is determined. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method and device for coordinated control of adjacent intersections based on low permeability trajectory data, so as to judge whether adjacent intersections are suitable for coordinated control from the perspective of coordinated control results.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] One aspect of the present invention provides a method for coordinated control of adjacent intersections based on low permeability trajectory data, comprising the following steps:

[0009] Step S1, obtaining low permeability trajectory data of two adjacent intersections and calculating vehicle flow rate information;

[0010] Step S2, constructing a phase difference optimization model, based on the flow rate information, respectively constructing an optimization function to optimize the phase difference with the goal of maximizing the average vehicle delay of the coordinated phase and minimizing the average vehicle delay of the coordinated phase, and obtaining the maximum average vehicle delay and the minimum average vehicle delay by changing the phase difference;

[0011] Step S3, based on the maximum average vehicle delay and the minimum average vehicle delay, determine whether two adjacent intersections are divided into the same sub-area, complete the sub-area division, and implement intersection coordination control based on the divided sub-areas.

[0012] As a preferred technical solution, the flow rate information calculation process includes the following steps:

[0013] Step S101, calculating the estimated time for the vehicle to reach the stop line based on the low permeability trajectory data;

[0014] Step S102, taking the start time of the red light as the starting point of each cycle, superimposing the trajectory data of multiple cycles to obtain the arrival curve and departure curve of the vehicle in one signal cycle, and calculating the flow rate information.

[0015] As a preferred technical solution, the flow rate information includes arrival flow rate, departure flow rate and saturation flow rate, wherein the saturation flow rate is the average of the departure flow rate within a period of time after the green light is turned on.

[0016] As a preferred technical solution, the optimization function is:

[0017]

[0018]

[0019] in, is the delay of all vehicles in the coordinated phase, d is the delay of all vehicles in the forward coordinated phase, is the average delay of the coordinated phase in the reverse direction, A(C) is the cumulative number of vehicles arriving within 0 to C seconds, C is, Rn(t) is the number of queued vehicles at the downstream intersection at the tth second in the cycle, They are the cumulative number of vehicles arriving in the opposite direction from 0 to C seconds and the number of vehicles queuing at the downstream intersection at the tth second in the cycle, and C is the signal cycle.

[0020] As a preferred technical solution, it is characterized in that the optimization function is solved by an optimization solver to obtain the maximum average vehicle delay and the minimum average vehicle delay.

[0021] As a preferred technical solution, the optimization solver is GUROBI.

[0022] As a preferred technical solution, the step S3 is specifically as follows:

[0023] Step S31, calculating an intersection coordination index based on the maximum average vehicle delay and the minimum average vehicle delay;

[0024] Step S32: Based on the intersection coordination index, determine whether adjacent intersections are suitable for coordinated control according to preset rules.

[0025] As a preferred technical solution, the intersection coordination index is calculated using the following formula:

[0026]

[0027] Where ICI is the intersection coordination index, d max ,d min The maximum average delay per vehicle and the minimum average delay per vehicle are calculated respectively.

[0028] Another aspect of the present invention provides an electronic device, comprising: one or more processors and a memory, wherein the memory stores one or more programs, and the one or more programs include instructions for executing the above-mentioned adjacent intersection coordination control method based on low permeability trajectory data.

[0029] Another aspect of the present invention provides a computer-readable storage medium comprising one or more programs for execution by one or more processors of an electronic device, wherein the one or more programs include instructions for executing the above-mentioned method for coordinated control of adjacent intersections based on low-permeability trajectory data.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] (1) It is possible to easily determine whether coordinated control is to be performed: Different from the existing scheme of subdividing the area based on intersection correlation or green wave bandwidth and then performing coordinated control, this application constructs a phase difference optimization model to calculate the maximum average vehicle delay and the minimum average vehicle delay as the coordination result of two local intersections, and directly judges whether adjacent intersections are coordinated from the perspective of the coordination result. This can reduce the influence of subjective factors while simply and effectively predicting the results after coordination, thereby determining whether coordinated control is to be performed. In addition, in view of the current situation where the proportion of connected vehicles is still small and only low-penetration trajectory data can be provided, this application can determine whether coordinated control is to be performed based on low-penetration trajectory data.

[0032] (2) Close to reality, the influence of signal conditions on coordinated control is taken into account: Under realistic conditions, the signal timing of a single-point intersection needs to be determined based on the traffic demands of the main road and branch roads. The present invention is suitable for determining whether adjacent intersections should be coordinated after the timing scheme of a single-point intersection is determined.

[0033] (3) Easy to solve optimization problems: The problem can be quickly solved with the help of mature optimization solvers, and the optimization model is simple. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Flow chart of the adjacent intersection coordination control method based on low permeability trajectory data in an embodiment. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0036] Example 1

[0037] See also Figure 1 The present application provides a method for coordinated control of adjacent intersections based on low-permeability trajectory data, which evaluates the coordination benefits of adjacent intersections based on sparse trajectory data and provides a basis for coordinated sub-area division. The arrival flow rate, departure flow rate, and saturation flow rate of vehicles are extracted based on the sparse trajectory data, and the maximum and minimum values ​​of the average vehicle delay are calculated by changing the phase difference using an optimization model, and the intersection coordination index (ICI) is calculated to determine whether adjacent intersections are coordinated.

[0038] This method comprises the following steps:

[0039] Step S1, extracting the arrival flow rate, departure flow rate, and saturation flow rate of vehicles based on the sparse trajectory data, and using the trajectory data superposition method to reflect the arrival distribution of all vehicles using the low-permeability trajectory data.

[0040] Specifically, the parameters that can be directly obtained using trajectory data include: the time t when the vehicle starts to stop due to the influence of the intersection signal light s , the distance d from the parking position to the parking line of the entrance road s and the time t when the vehicle leaves the stop line of the intersection d The estimated time t of a vehicle arriving at the stop line without considering the parking queue needs to be calculated. a , which can be divided into two situations.

[0041] For vehicles that pass through without stopping, there are:

[0042] t a =t d

[0043] For vehicles passing through the intersection after parking in a queue, the average vehicle speed v a It can be calculated based on the driving distance and time before the vehicle stops:

[0044]

[0045] Taking the start time of the red light as the starting point of each cycle, the sparse trajectory data of multiple cycles are superimposed to obtain the arrival curve and departure curve of the vehicle in a signal cycle. The time is discretized in seconds, and the arrival flow rate and departure flow rate of the superimposed trajectory are extracted per second. The departure flow rate within 5 seconds after the green light is turned on is averaged to obtain the saturated flow rate after trajectory superposition.

[0046] Step S2, establish a phase difference optimization model, take the maximum and minimum delay as optimization targets, optimize the phase difference, and calculate the maximum and minimum average vehicle delay that can be obtained by changing the phase difference when parameters such as cycle and green-to-signal ratio remain unchanged.

[0047] Specifically, the phase difference optimization model takes the maximum and minimum delay as the optimization target. The model constraints are as follows:

[0048] The cumulative number of arriving vehicles A(t) is the sum of the vehicle arrival flow rate Aq(k) within 0 to t seconds, and the cumulative number of leaving vehicles D(t) is the sum of the vehicle departure flow rate Dq(k) within 0 to t seconds:

[0049]

[0050]

[0051] The number of vehicles queuing at the downstream intersection at the tth second in the cycle, Rn(t), is the difference between the cumulative number of arriving vehicles and the cumulative number of leaving vehicles at this time:

[0052]

[0053] The departure flow rate Dq(t) at the tth second in the cycle is calculated from the maximum departure flow rate D max The cumulative number of vehicles staying is determined by the arrival flow rate Aq(t) at that moment and the queue length Rn(t-1) at t-1 seconds:

[0054]

[0055] Among them, the maximum departure flow rate Dmax (t) is related to the signal G(t) of the coordinated phase. If it is green at t seconds, define G(t) = 1; if it is red at t seconds, define G(t) = 0. When the coordinated phase is green, D max (t) can reach the saturation flow rate S. When the coordinated phase is red, vehicles cannot pass through:

[0056]

[0057] For the opposite direction, there are the same constraints:

[0058]

[0059]

[0060]

[0061]

[0062]

[0063] The relative phase difference between adjacent intersections satisfies the time range:

[0064] 0 ≤ Os ≤ C - 1

[0065] For the upstream direction, there are two cases. When O s ≤ GL, the auxiliary 0 - 1 variable α = 0; when O s ≥ GL, α = 1:

[0066] -(1 - α)M ≤ O s -GL ≤ αM

[0067] In the case of α = 0, when Os ≤ t < Os + RL, the coordinated phase is red and G(t) = 0; when t ≤ Os or t ≥ Os + RL, the coordinated phase is green and G(t) = 1:

[0068]

[0069]

[0070]

[0071] In the case of α = 1, when Os - GL ≤ t ≤ Os, the coordinated phase is green and G(t) = 1; when t ≤ Os - GL or t ≥ Os, the coordinated phase is red and G(t) = 0:

[0072]

[0073]

[0074]

[0075] There are also two cases for the downlink direction. Time auxiliary 0-1 variable hour

[0076]

[0077] exist In the case of When the coordinated phase is green Or when t≥C-Os, the coordination phase is red light G(t)=0:

[0078]

[0079]

[0080]

[0081] exist In the case of When the coordinated phase is red t≤C-Os or When the coordinated phase is green

[0082]

[0083]

[0084]

[0085] The optimization model has two objective functions, namely, the minimum average delay of the coordinated phase vehicles (P1) and the maximum average delay of the coordinated phase vehicles (P2):

[0086]

[0087]

[0088] Under the condition that the above constraints are met, P1 and P2 are optimized with the help of the optimization solver (GUROBI) to obtain the maximum and minimum values ​​of the average vehicle delay.

[0089] Step S3, calculating the intersection coordination index (ICI) according to the result of step S2 to determine whether adjacent intersections are coordinated and controlled.

[0090] According to the calculated maximum average vehicle delay (d max ) and minimum value (d min), the intersection coordination index is calculated as follows:

[0091]

[0092] The thresholds of the intersection coordination index (ICI) are shown in Table 1.

[0093] Table 1 Thresholds of intersection coordination index ICI

[0094]

[0095] All adjacent intersections in the road network are calculated for ICI. According to the judgment result of ICI, if adjacent intersections are coordinated and controlled, the two intersections are placed in the same coordination sub-area. After completing the sub-area division of the entire road network, a coordination control scheme can be designed based on the existing trunk coordination algorithm, or signal control systems such as SCATS and SCOOT can be used for coordinated control.

[0096] The present invention has the following advantages:

[0097] Judging whether adjacent intersections should be coordinated directly from the perspective of coordination benefits and using the optimization model to calculate indicators can simply and effectively predict the effect after coordination.

[0098] The optimization model is simple and can be solved quickly with the help of existing optimization solvers.

[0099] The influence of signal conditions on coordinated control is considered. Under realistic conditions, the signal timing of a single-point intersection needs to be determined according to the traffic demand of the main road and branch roads. The present invention is suitable for determining whether adjacent intersections should be coordinated after the timing scheme of a single-point intersection is determined.

[0100] Example 2

[0101] This embodiment provides an electronic device, including: one or more processors and a memory, wherein the memory stores one or more programs, and the one or more programs include instructions for executing the adjacent intersection coordination control method based on low permeability trajectory data as described in Example 1.

[0102] Example 3

[0103] This embodiment provides a computer-readable storage medium, including one or more programs for execution by one or more processors of an electronic device, wherein the one or more programs include instructions for executing the adjacent intersection coordination control method based on low permeability trajectory data as described in Example 1.

[0104] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for coordinated control of adjacent intersections based on low permeability trajectory data, characterized in that: The steps include: Step S1, obtaining low permeability trajectory data of the road network and calculating the flow rate information of the vehicle; Step S2, constructing a phase difference optimization model, based on the flow rate information, respectively constructing an optimization function to optimize the phase difference with the goal of maximizing the average vehicle delay of the coordinated phase and minimizing the average vehicle delay of the coordinated phase, and obtaining the maximum average vehicle delay and the minimum average vehicle delay by changing the phase difference; Step S3, based on the maximum average vehicle delay and the minimum average vehicle delay, determine whether two adjacent intersections are divided into the same sub-area, complete the sub-area division, and implement intersection coordination control based on the divided sub-areas. The optimization function includes two objective functions, namely, the minimum average vehicle delay P1 of the coordinated phase and the maximum average vehicle delay P2 of the coordinated phase. By solving P1 and P2 respectively, the maximum and minimum values ​​of the average vehicle delay are obtained. The two objective functions are: P1： ； P2： ； in, To coordinate the phases, all vehicles were delayed. The forward coordination phase vehicles are all delayed. The vehicles in the reverse coordination phase are all delayed. It is 0~ The total number of vehicles arriving within seconds, Is the downstream intersection in the cycle The number of vehicles in the queue per second, , They are 0~ in opposite directions respectively The cumulative number of vehicles arriving within seconds and the number of downstream intersections in the cycle The number of vehicles in the queue per second, is the signal period.

2. The method for coordinated control of adjacent intersections based on low permeability trajectory data according to claim 1, characterized in that: The calculation process of the flow rate information includes the following steps: Step S101, calculating the estimated time for the vehicle to reach the stop line based on the low permeability trajectory data; Step S102, taking the start time of the red light as the starting point of each cycle, superimposing the trajectory data of multiple cycles to obtain the arrival curve and departure curve of the vehicle in one signal cycle, and calculating the flow rate information.

3. The method for coordinated control of adjacent intersections based on low permeability trajectory data according to claim 1, characterized in that: The flow rate information includes the arrival flow rate, the departure flow rate and the saturation flow rate, wherein the saturation flow rate is the average of the departure flow rate within a period of time after the green light is turned on.

4. The method for coordinated control of adjacent intersections based on low permeability trajectory data according to claim 1, characterized in that: The optimization function is solved by an optimization solver to obtain the maximum average vehicle delay and the minimum average vehicle delay.

5. The method for coordinated control of adjacent intersections based on low permeability trajectory data according to claim 4, characterized in that: The optimization solver is GUROBI.

6. The method for coordinated control of adjacent intersections based on low permeability trajectory data according to claim 1, characterized in that: The step S3 is specifically as follows: Step S31, calculating an intersection coordination index based on the maximum average vehicle delay and the minimum average vehicle delay; Step S32: Based on the intersection coordination index, determine whether adjacent intersections are suitable for coordinated control according to preset rules.

7. The method for coordinated control of adjacent intersections based on low permeability trajectory data according to claim 6, characterized in that: The intersection coordination index is calculated using the following formula: ， in, is the intersection coordination index, , The maximum average delay per vehicle and the minimum average delay per vehicle are calculated respectively.

8. An electronic device, characterized in that: include: One or more processors and a memory, wherein the memory stores one or more programs, wherein the one or more programs include instructions for executing the adjacent intersection coordination control method based on low permeability trajectory data as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that: It includes one or more programs for execution by one or more processors of an electronic device, and the one or more programs include instructions for executing the adjacent intersection coordinated control method based on low-permeability trajectory data as described in any one of claims 1-7.

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