Vehicle queue scale determination method and system based on traffic simulation vehicle-road cooperation environment, computer and storage medium

Abstract

The invention discloses a method for determining the scale of a vehicle queue in a vehicle-road cooperation environment based on traffic simulation, and the method comprises the steps: obtaining the actual traffic state information of a road, determining the function form of a vehicle head distance control coefficient and the to-be-calibrated parameters of the vehicle head distance control coefficient, and determining a vehicle head distance control function at the same time. And on the basis of actual traffic state information of a road, calibrating a headstock control coefficient function parameter, and determining a queue scale according to a headstock control function. Traffic simulation software is used for obtaining simulated traffic flow operation state information, on this basis, the error between the simulated headstock and the theoretical headstock is calculated, if the error is larger than a preset threshold value, the simulated traffic flow operation state information and the actual traffic state information are combined, headstock control coefficient function parameters are calibrated again, and the real headstock control coefficient function parameters are calculated; and finally, calculating to obtain a final queue scale.

Description

Technical Field

[0001] The present invention relates to the field of intelligent traffic control, and in particular to a method, system, computer and storage medium for determining the size of a vehicle queue in a traffic simulation vehicle-road cooperative environment. Background Art

[0002] Traffic simulation is a technology that uses computers to simulate the behavior and performance of traffic systems. By building a traffic simulation model, it is possible to simulate vehicle movement, traffic flow changes, traffic signal control, etc. Traffic simulation can provide data under various traffic conditions to help researchers and traffic managers evaluate the effectiveness of traffic strategies, predict traffic flow and congestion, and plan and optimize traffic systems.

[0003] In a vehicle-road collaborative environment, the determination of the size of a vehicle queue refers to the use of traffic simulation models and real-time data to estimate the number of vehicles in a vehicle queue. This method can be applied to traffic management, traffic flow prediction and other fields. By accurately determining the size of a vehicle queue, traffic control can be optimized, traffic flow efficiency can be improved, and real-time traffic information can be provided.

[0004] The vehicle queue size determination method based on traffic simulation combines vehicle-road cooperative technology and traffic simulation technology, which can provide accurate vehicle queue information, help traffic managers formulate reasonable traffic management and control strategies, optimize the operation efficiency of traffic flow, and improve the overall performance of the traffic system. The technical solution of this patent is of great significance for improving traffic congestion problems and enhancing the intelligence and sustainable development of the traffic system. Summary of the invention

[0005] Purpose of the invention: In order to overcome the deficiencies of the above-mentioned prior art, the purpose of the present invention is to propose a method, system, computer and storage medium for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation. Based on the actual traffic status information of the road, the function form of the headway control coefficient is determined and the function parameters are calibrated. Then, the traffic simulation software is used to obtain the simulated traffic flow operation status information. On this basis, the error between the simulated headway and the theoretical headway is calculated to verify the accuracy of the calibration parameters. If the error is greater than a preset threshold, the simulated traffic flow operation status information and the actual traffic status information are combined, and the headway control coefficient function parameters are recalibrated until the error is less than the preset threshold.

[0006] Technical solution, in order to solve the above technical problems, the present invention proposes a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, the method comprising the following steps:

[0007] (1) Determine the road traffic status information and mark the vehicle type, lane number, vehicle speed, minimum safe distance, headway and vehicle longitudinal position as the initial traffic flow data set;

[0008] (2) Determine the headway control coefficient and express the headway control coefficient in a function form;

[0009] (3) Calibrate the parameters in the headway control coefficient function according to the initial traffic flow data set, and record the calibrated parameters as the initial parameter set;

[0010] (4) Using the headway control coefficient, determine the control function of the headway between vehicles, and on this basis determine the initial queue size;

[0011] (5) Based on the initial queue size in step (4), the traffic flow of the road section is simulated using traffic simulation software, the simulated traffic flow operation status information is collected through the roadside equipment, marked as a simulated traffic flow data set, and the simulated headway is calculated;

[0012] (6) Substituting the simulated traffic flow operation status information and the headway control coefficient of step (5) into the headway control function to obtain the theoretical headway, and calculating the error between the simulated headway and the theoretical headway;

[0013] (7) Determine whether the error in step (6) exceeds a preset threshold. If so, merge the initial traffic flow data set and the simulated traffic flow data set into a new generation data set, and repeat steps (3) to (7) until the error does not exceed the threshold. If not, use the new generation parameter set as the final solution to obtain a headway control coefficient function that completes parameter calibration, calculate the final queue size, and end the calibration process.

[0014] Furthermore, in step (1), the road traffic status information includes: the position coordinates (x c ,y c ), roadside equipment control area [x c -C l ,x c +C l ], where C l is the maximum communication transmission distance of the roadside equipment; the initial traffic flow data set q0 = {q 0_1 ,q 0_2 ,…,q 0_n ,…,q 0_N-1 ,q 0_N}, where the nth data q 0_n ={type,lane,v 0_n ,s 0_n ,h 0_n ,x 0_n}, type, lane, v 0_n 、s0_n 、h 0_n 、x 0_n They are respectively the vehicle type, lane number, vehicle speed, minimum safe distance, headway, and vehicle longitudinal position in the nth data, n=1, 2, ..., N, N is the number of vehicles on the road at the initial moment, and the vehicle types include autonomous driving vehicles and human-driven vehicles.

[0015] Furthermore, in step (2), the function expression of the headway control coefficient is:

[0016] ψ=ω1Q t +ω2m+ω3v r

[0017] Where ψ is the headway control coefficient; Q t is the road traffic flow at time t, K is the amount of data within the control range of the roadside equipment, h t_i is the headway of vehicle i at time t; m is the proportion of autonomous driving vehicles within the control range of the roadside equipment; v r is the average speed of vehicles within the control range of the roadside equipment, v i is the speed of vehicle i within the control range of the roadside equipment; ω1, ω2, ω3 are the weight parameters to be calibrated.

[0018] Furthermore, in step (3), the initial traffic flow data set q0 is used to apply the least squares method to calibrate the weight parameters ω1, ω2, ω3 of the headway control coefficient function, and the calibrated parameters are recorded as the initial parameter set.

[0019] Furthermore, in step (4), the vehicle headway control function is:

[0020]

[0021] Among them, R t_(i-1,i) is the headway distance between vehicle i and vehicle i-1 at time t; s t_i is the minimum safe distance of vehicle i at time t; v t_i is the vehicle speed of vehicle i at time t;

[0022] In step (4), the calculation formula for the initial queue size is:

[0023]

[0024] Where Φ(t) is the size of the vehicle queue at time t, and [·] is the rounding function.

[0025] Furthermore, in step (5), the simulated traffic flow operation status information collected is as follows:

[0026] The simulated traffic flow data set q at time t t = {q t_1 ,q t_2 ,…,q t_n ,…,q t_N’-1 ,q t_N’}, where the nth data q t_n ={type,lane,v t_n ,s t_n ,h t_n ,x t_n}, where v 0_n 、s 0_n 、h 0_n 、x 0_n They represent the vehicle speed, minimum safe distance, headway, and longitudinal position of the vehicle in the nth data at time t, respectively. n = 1, 2, ..., N', where N' is the amount of traffic flow data at time t. The simulated headway is calculated as follows:

[0027] r t_(i-1,i) =x t_i-1 -x t_i

[0028] Among them, r t_(i-1,i) is the simulated headway at time t, x t_i-1 ,x t_i is the longitudinal position of the i-1th and i-th vehicles at time t.

[0029] Furthermore, in step (6), the error is calculated as follows:

[0030]

[0031] Among them, Δ is the error between the theoretical headway and the simulated headway;

[0032] In step (7), determine whether Δ is equal to a preset threshold Δ lim =5% of the size relationship, if Δ≤Δ lim , the new generation parameter set is taken as the final solution; if Δ>Δ lim , merge the initial data set and the simulated data set into a new generation data set, and repeat steps (3)-(7).

[0033] In addition, the present invention proposes a vehicle queue size determination system in a vehicle-road cooperative environment based on traffic simulation, the system comprising a signal collector, an autonomous driving vehicle and a server thereof, the signal collector and the autonomous driving vehicle are both connected to the server;

[0034] Among them, the signal collector is used to collect road traffic status information and feed it back to the server;

[0035] The autonomous driving vehicle feeds back its own speed to the server;

[0036] The server calculates the size of the vehicle queue using the method and feeds it back to the corresponding autonomous driving vehicle.

[0037] In addition, the present invention proposes a computer device for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any of the methods when executing the computer program.

[0038] In addition, the present invention provides a storage medium having a computer program stored thereon, wherein the computer program implements the steps of any of the methods when executed by a processor.

[0039] Beneficial effects: Compared with the prior art, the technical solution of the present invention has the following beneficial technical effects:

[0040] The present invention discloses a method, system, computer and storage medium for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, which realizes accurate determination of the size of a vehicle queue by determining traffic state information, formulating a headway control strategy and a parameter calibration process. The method can optimize traffic flow operation efficiency, improve traffic safety and system performance, provide important decision-making basis for traffic management in a vehicle-road cooperative environment, and is beneficial to solving urban traffic congestion problems and improving the intelligence level of the traffic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0042] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0043] like Figure 1 As shown, an embodiment of the present invention discloses a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, and the method comprises the following steps:

[0044] (1) Determine the road traffic status information and mark the traffic flow, vehicle speed, headway, and headway time as the initial traffic flow data set.

[0045] Specifically, the road attributes are:

[0046]

[0047] Traffic flow characteristics are:

[0048]

[0049]

[0050] (2) Determine the function form of the headway control coefficient and its parameters to be calibrated. Headway control coefficient ψ = ω1Q t *10 -5 +ω2m*10 -3 +ω3v r *10 -4 .in, m = 11 / 30 = 0.37; K=30.

[0051] (3) Based on the initial traffic flow data set, the parameters in the headway control coefficient function are calibrated and marked as the initial parameter set; based on the initial traffic flow data set, the least squares method is used to calibrate the weight parameters of the headway control coefficient function:

[0052]

[0053] (4) Determine the vehicle headway control strategy. The vehicle headway control strategy is:

[0054]

[0055] (5) Determine the initial queue size based on the headway control strategy, where C l =450m;

[0056]

[0057] (6) Based on the queue size determined in step (5), the traffic flow of the road section is simulated using traffic simulation software. Through the communication between vehicles and roadside equipment, the simulated traffic flow operation status information is collected and the simulated headway is calculated. The simulated traffic flow operation status information is:

[0058]

[0059]

[0060]

[0061] (7) Substituting the simulated traffic flow operation status information and the initial parameter set of step (6) into the headway control strategy to obtain the theoretical headway;

[0062] Theoretical headroom

[0063] (8) Calculate the error between the simulated headway and the theoretical headway;

[0064]

[0065] (9) The error in step (8) is Δ=0.49%<Δ lim =5% does not exceed the preset threshold, and the new generation parameter set is used as the final solution to obtain the headway control coefficient function that completes parameter calibration, and the calibration process ends. Among them, ω1, ω2, and ω3 are -0.21, -0.49, and 0.30 respectively.

[0066] It should be emphasized that the examples described in the present invention are illustrative rather than restrictive, and therefore the present invention is not limited to the examples described in the specific embodiments. Any other embodiments derived by those skilled in the art based on the technical solution of the present invention that do not depart from the purpose and scope of the present invention, whether modified or replaced, also fall within the scope of protection of the present invention.

Claims

1. A method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: The method comprises the following steps: (1) Determine the road traffic status information and mark the vehicle type, lane number, vehicle speed, minimum safe distance, headway and vehicle longitudinal position as the initial traffic flow data set; (2) Determine the headway control coefficient and express the headway control coefficient in a function form; (3) Calibrate the parameters in the headway control coefficient function according to the initial traffic flow data set, and record the calibrated parameters as the initial parameter set; (4) Using the headway control coefficient, determine the control function of the headway between vehicles, and on this basis determine the initial queue size; (5) Based on the initial queue size in step (4), the traffic flow of the road section is simulated using traffic simulation software, the simulated traffic flow operation status information is collected through the roadside equipment, marked as a simulated traffic flow data set, and the simulated headway is calculated; (6) Substituting the simulated traffic flow operation status information and the headway control coefficient of step (5) into the headway control function to obtain the theoretical headway, and calculating the error between the simulated headway and the theoretical headway; (7) Determine whether the error in step (6) exceeds a preset threshold. If so, merge the initial traffic flow data set and the simulated traffic flow data set into a new generation data set, and repeat steps (3) to (7) until the error does not exceed the threshold. If not, use the new generation parameter set as the final solution to obtain a headway control coefficient function that completes parameter calibration, calculate the final queue size, and end the calibration process.

2. According to claim 1, a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: In step (1), the road traffic status information includes: the position coordinates (x c ,y c ), roadside equipment control area [x c -C l , x c +C l ], where C l is the maximum communication transmission distance of the roadside equipment; the initial traffic flow data set q0 = {q 0_1 ,q 0_2 ,…,q 0_n ,…,q 0_N-1 ,q 0_N }, where the nth data q 0_n ={type,lane,v 0_n ,s 0_n ,h 0_n ,x 0_n }, type, lane, v 0_n 、s 0_n 、h 0_n 、x 0_n They are respectively the vehicle type, lane number, vehicle speed, minimum safe distance, headway, and vehicle longitudinal position in the nth data, n=1, 2, ..., N, N is the number of vehicles on the road at the initial moment, and the vehicle types include autonomous driving vehicles and human-driven vehicles.

3. According to claim 1, a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: In step (2), the function expression of the headway control coefficient is: ψ=ω1Q t +ω2m+ω3v r Where ψ is the headway control coefficient; Q t is the road traffic flow at time t, K is the amount of data within the control range of the roadside equipment, h t_i is the headway of vehicle i at time t; m is the proportion of autonomous driving vehicles within the control range of the roadside equipment; v r is the average speed of vehicles within the control range of the roadside equipment, v i is the speed of vehicle i within the control range of the roadside equipment; ω1, ω2, ω3 are the weight parameters to be calibrated.

4. According to claim 3, a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: In step (3), the initial traffic flow data set q0 is used to calibrate the weight parameters ω1, ω2, ω3 of the headway control coefficient function using the least squares method, and the calibrated parameters are recorded as the initial parameter set.

5. According to claim 3, a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: In step (4), the vehicle headway control function is: Among them, R t_(i-1,i) is the headway distance between vehicle i and vehicle i-1 at time t; s t_i is the minimum safe distance of vehicle i at time t; v t_i is the vehicle speed of vehicle i at time t; The formula for calculating the initial queue size is: Where Φ(t) is the size of the vehicle queue at time t, and [·] is the rounding function.

6. According to claim 5, a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: In step (5), the simulated traffic flow operation status information collected is as follows: Set the simulated traffic flow data set q at time t t = {q t_1 ,q t_2 , …, q t_n , …, q t_N’-1 ,q t_N’ }, where the nth data q t_n ={type, lane, v t_n ,s t_n ,h t_n , x t_n }, where v 0_n 、s 0_n 、h 0_n 、x 0_n They represent the vehicle speed, minimum safe distance, headway, and longitudinal position of the vehicle in the nth data at time t, respectively. n = 1, 2, ..., N', where N' is the amount of traffic flow data at time t. The simulated headway is calculated as follows: r t_(i-1,i) =x t_i-1 -x t_i Among them, r t_(i-1,i) is the simulated headway at time t, x t_i-1 ,x t_i is the longitudinal position of the i-1th and i-th vehicles at time t.

7. According to claim 6, a method for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, characterized in that: In step (6), the error is calculated as follows: Among them, Δ is the error between the theoretical headway and the simulated headway; In step (7), determine whether Δ is equal to a preset threshold Δ lim If Δ≤Δ lim , the new generation parameter set is taken as the final solution; if Δ>Δ lim , merge the initial data set and the simulated data set into a new generation data set, and repeat steps (3)-(7).

8. A vehicle queue size determination system in a vehicle-road cooperative environment based on traffic simulation, characterized in that: The system includes a signal collector, an autonomous driving vehicle and a server thereof, wherein the signal collector and the autonomous driving vehicle are both connected to the server; The signal collector is used to collect road traffic status information and feed it back to the service end; The autonomous driving vehicle feeds back its own speed to the server; The server calculates the size of the vehicle queue using any of the methods described in claims 1 to 7, and feeds it back to the corresponding autonomous driving vehicle.

9. A computer device for determining the size of a vehicle queue in a vehicle-road cooperative environment based on traffic simulation, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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