CN113658432B - Traffic optimization method at intersection without traffic lights based on vehicle traffic priority game - Google Patents

Abstract

A traffic optimization method based on vehicle traffic priority game at intersections without signal lights. When there is a collision conflict, each vehicle calculates the passing time of its own vehicle, and then broadcasts the passing time to other vehicles; The vehicle performs Nash equilibrium through the transit time, searches for the qualified Pareto optimal solution in the obtained Nash equilibrium solution set, and then updates the transit time of all vehicles and broadcasts it to other vehicles; when the transit time of all vehicles is the minimum transit time , carry out priority assignment and broadcast, and send the state quantity and control instructions of the vehicle to other vehicles to execute the control instructions; the present invention is in the intersection scene without signal lights and centralized controller, using the communication between vehicles Communication enables direct games between vehicles, which can effectively highlight the interaction characteristics between vehicles, strengthen targeted games between vehicles, and improve the traffic efficiency of intersections while ensuring safety.

Description

Traffic optimization method at intersection without traffic lights based on vehicle traffic priority game

technical field

The invention relates to a technology in the field of intelligent traffic management, in particular to a traffic optimization method at an intersection without a signal light based on a vehicle traffic priority game.

Background technique

Safety and traffic efficiency are the core concerns of intersection research. In the environment of intersections without signal lights, the lack of signal lights can easily lead to confusion and low traffic efficiency. In addition, the advanced assisted driving equipped on the intelligent vehicle is only within the visible range of the vehicle, that is, the vehicle's sensors can sense the range for safety assistance. Therefore, at the intersection where there is a perception blind spot, the advanced assisted driving is not enough to guarantee vehicle safety. The cooperative driving of intelligent vehicles using information exchange can effectively ensure driving safety by obtaining other vehicle information in advance. However, established traffic rules, such as first-come, first-served traffic rules, that is, fixed traffic priorities, cannot guarantee the optimization of traffic efficiency.

The traffic flow control technology of the existing intersection is only for the scene of the intersection where the controller has been deployed. If there is no controller at the intersection, the existing technology cannot be implemented; at the same time, if the controller is deployed at each intersection, installation and maintenance are required. Costs will increase substantially.

SUMMARY OF THE INVENTION

Aiming at the prior art method of determining priorities through bidding coordination, the present invention has the problems of unreasonable bids and low vehicle traffic efficiency caused by vehicles not cooperating all the time, and the prior art only cooperates with vehicles located in the conflict zone. Design, ignoring the impact of the priority on the traffic efficiency before the vehicle enters the conflict area, and proposes a traffic optimization method at the intersection without signal lights based on the priority game of vehicle traffic. In the scenario, the communication between vehicles is used to directly play games between vehicles, which can effectively highlight the interaction characteristics between vehicles, strengthen targeted games between vehicles, and improve the traffic efficiency of intersections while ensuring safety.

The present invention is achieved through the following technical solutions:

The invention relates to a traffic optimization method at an intersection without a signal light based on a vehicle traffic priority game, comprising:

Step A: Based on the broadcast of other vehicles, the vehicle receives the status information and driving intention of surrounding vehicles.

The state information includes: the position information of the vehicle, including the longitude, latitude and altitude information of the vehicle, the speed information of the vehicle, and the acceleration information of the vehicle.

The driving intention includes: going straight, turning left, and turning right.

Step B. By predicting the trajectory of other vehicles, and judging that when there is no collision conflict, set the vehicle to drive away safely under the specified speed constraint; when there is a collision conflict, each vehicle calculates the passing time of its own vehicle, and then Broadcast transit times to other vehicles.

The trajectory prediction refers to the position of the vehicle in the future time period calculated through the state information of other vehicles.

The collision conflict refers to: in a future time period, if there is an intersection point between the predicted trajectories of the vehicles, it is determined that there is a collision conflict.

The safe departure refers to: since it is judged that there is no collision conflict, the vehicle safely passes and leaves the intersection on the premise of satisfying the traffic rules.

Step C. In the priority game stage, the vehicle performs Nash equilibrium according to the travel time broadcast by other vehicles obtained in step B, and updates all vehicles after searching for the qualified Pareto optimal solution in the obtained Nash equilibrium solution set. Travel time and broadcast to other vehicles.

Step D. When the transit time of all vehicles is the minimum transit time, perform priority assignment and broadcast, and send the state quantity and control instructions of the vehicle to other vehicles to execute the control instructions, otherwise return to step C to re-play the priority game.

The priority assignment includes: the sequence of each vehicle passing through the intersection.

The state quantity of the own vehicle includes: position, speed and acceleration information of the own vehicle.

The control instructions include: vehicle bottom actuators, such as the control input obtained by the accelerator pedal, the brake pedal, and the steering wheel.

technical effect

The present invention solves the problem that the prior art is only aimed at vehicles in the conflict zone (intersection) and ignores the problem that the priority affects the traffic efficiency before the vehicle enters the conflict zone.

Compared with the prior art, by using a game method, by adding a vehicle traffic priority distribution layer, the continuity of vehicles entering and exiting the intersection is increased, and the traffic efficiency of the intersection is further improved. In addition, because this method does not need to deploy additional centralized controllers (coordinators/signals) at the intersection, hardware and maintenance costs will be greatly reduced.

Description of drawings

Fig. 1 is a flow chart of the present invention.

Detailed ways

As shown in FIG. 1 , the present embodiment relates to a traffic optimization method at an intersection without a signal light based on a vehicle traffic priority game algorithm, which specifically includes:

Step A: Based on the broadcast of other vehicles, the vehicle receives the status information and driving intention of surrounding vehicles.

Step B. By predicting the trajectory of other vehicles and judging whether there is a conflict, when there is no collision and conflict, the vehicle drives away safely under the specified speed constraint; when there is a conflict, calculate the travel time of all vehicles, that is, the vehicle passes through the intersection. time.

其中：g()为具有求解通行时间功能的函数定义，单个车辆通过交叉口时间

其中：v为速度，a为加速度，m为车辆ID，i为迭代次数，p为位置。The transit time of all vehicles is the maximum transit time of vehicles, that is, the time of the last vehicle passing through, not the cumulative sum of all vehicle times, specifically:

Among them: g() is the function definition with the function of solving the passing time, and the time for a single vehicle to pass through the intersection

Where: v is the velocity, a is the acceleration, m is the vehicle ID, i is the number of iterations, and p is the position.

表示每辆车选取一种控制量参与纳什均衡计算，比如组合

In this embodiment, three vehicles are taken as an example, the subscripts 1, 2, and 3 are the vehicle IDs, respectively, u* is the optimal control amount, u ^s is the progressive control amount,

Indicates that each vehicle selects a control quantity to participate in the Nash equilibrium calculation, such as a combination

The time is obtained through different combinations, so the solution set of T _total is a 1×6 matrix, that is, there are six different combinations, but each combination needs to be enumerated and calculated.

Step C. In the priority game stage, the vehicle calculates the Nash equilibrium by obtaining the transit time broadcast by other vehicles, and at the same time, after acquiring the Pareto optimal solution set, the transit time of all vehicles is updated and broadcast to other vehicles.

其中：g()定义同上，

中上角标p为区分帕累托最优的控制量。The update of all vehicle transit times refers to:

Among them: g() is defined as above,

The superscript p is the control variable that distinguishes Pareto optimality.

Step D. When the transit time of all vehicles is the minimum transit time, perform priority assignment and broadcast, and send the state quantity and control instructions of the vehicle to other vehicles to execute the control instructions, otherwise return to step C to re-play the priority game.

In this embodiment, in the hardware-in-the-loop environment, three vehicles are deployed for experiments, specifically:

Vehicle 1: 90m away from the intersection, speed 15m/s, acceleration 0, priority 1;

Vehicle 2: 100m from the intersection, speed 15m/s, acceleration 0, priority 3;

Vehicle 3: 90m from the intersection, speed 13m/s, acceleration 0, priority 2;

The obtained experimental data are shown in Table 1.

Table 1 Intersection travel time

Note: s is the time unit second.

To sum up, compared with the prior art, the method can significantly improve the passing efficiency of the intersection, and shorten the time for vehicles to pass through, that is, the time for the last vehicle to pass through the intersection.

The above-mentioned specific implementation can be partially adjusted by those skilled in the art in different ways without departing from the principle and purpose of the present invention. The protection scope of the present invention is subject to the claims and is not limited by the above-mentioned specific implementation. Each implementation within the scope is bound by the present invention.

Claims (1)

1. a kind of traffic optimization method based on vehicle traffic priority game, it is characterized in that, comprising: Step A. Based on the broadcast of other vehicles, the vehicle receives the status information and driving intention of surrounding vehicles; Step B. By predicting the trajectory of other vehicles, and judging that when there is no collision conflict, set the vehicle to drive away safely under the specified speed constraint; when there is a collision conflict, each vehicle calculates the passing time of its own vehicle, and then Broadcast transit times to other vehicles; Step C. In the priority game stage, the vehicle performs Nash equilibrium according to the travel time broadcast by other vehicles obtained in step B, and updates all vehicles after searching for the qualified Pareto optimal solution in the obtained Nash equilibrium solution set. transit time and broadcast to other vehicles; The transit time of all vehicles is the maximum transit time of vehicles, that is, the time of the last vehicle passing through, not the cumulative sum of all vehicle times, specifically:

Among them: g() is the function definition with the function of solving the passing time, and the time for a single vehicle to pass through the intersection

Where: v is the speed, a is the acceleration, m is the vehicle ID, i is the number of iterations, and p is the position; The update of all vehicle transit times refers to:

Among them: g() is defined as above,

The superscript p is the control variable that distinguishes Pareto optimal; Step D, when the transit time of all vehicles is the minimum transit time, carry out priority assignment and broadcast, and send the state quantity and control instruction of the vehicle to other vehicles to execute the control instruction, otherwise return to step C to re-play the priority game; The state information includes: the position information of the vehicle, including the longitude, latitude and altitude information of the vehicle, the speed information of the vehicle, and the acceleration information of the vehicle; The driving intention includes: going straight, turning left, and turning right; The trajectory prediction refers to: the position of the vehicle in the future time period calculated through the state information of other vehicles; The collision conflict refers to: in the future time period, if there is an intersection between the predicted trajectories of the vehicles, it is judged that there is a collision conflict; The safe driving off means: since it is judged that there is no collision conflict, the vehicle passes and leaves the intersection safely on the premise that the traffic rules are met; The control instruction includes: the control input of the vehicle bottom actuator.

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