匝道合流区智能网联车辆协同控制方法

doi:10.13229/j.cnki.jdxbgxb.20220830

摘要/Abstract

摘要：

为解决智能网联环境下匝道合流过程中车辆通行的效率和安全问题，提出了一种基于博弈论的智能车辆协同控制方法。该方法构建了以匝道外侧车道车辆为主体的三方博弈对局，并从换道、安全和行驶效率收益方面综合建立车辆收益函数；以博弈对局整体收益最大为控制目标，依据夏普利值进行收益分配，得到三方博弈对局中车辆最优控制策略。实验选取重庆市玉马路与重庆内环快速路包头方向合流区为路网原型，对合流区的车辆运行场景采用SUMO/TraCI和Python进行联合仿真分析。结果表明：本文所提出的合作博弈控制方法与演化博弈控制方法相比，总体平均行程时间缩短3.22%，平均延误时间缩短14.47%；车辆严重冲突降低54.04%，碰撞时间小于3 s的比例总体降低了26.56%；有效降低了交通冲突时间，改善了合流区交通运行效率。

关键词: 交通工程, 纳什均衡, 合作博弈控制, 匝道合流区, 智能网联

Abstract:

In order to solve the efficiency and safety problems of vehicle passage during ramp confluence in an intelligent network environment， a cooperative control method for intelligent vehicles based on game theory was proposed. In this method， a three-way game with vehicles on the outside of the ramp as the main body was constructed， and the vehicle revenue function was established from three aspects of safety， lane change and vehicle efficiency. Based on Shapley's value， the optimal control strategy of the vehicle in a three-way game was obtained. In the experiment， the merging area of Chongqing Yuma Road and Baotou direction of Chongqing Inner Ring Expressway was selected as the prototype of the road network， and the vehicle running scene in the merging area was co-simulated by SUMO/TraCI and Python. The results show that compared with the evolutionary game control method， the overall average travel time ratio is reduced by 3.22%， and the average delay time is reduced by 14.47%，the time-to-collision （TTC） less than 3 s decreased by 26.56%. It effectively reduces the traffic conflict time and improves the traffic operation efficiency in the confluence area.

Key words: traffic engineering, Nash equilibrium, cooperative game control, ramp confluence area, intelligent networked

中图分类号:

U491.54

马庆禄,闫浩,聂振宇,李杨梅. 匝道合流区智能网联车辆协同控制方法[J]. 吉林大学学报(工学版), 2024, 54(5): 1332-1346.

Qing-lu MA,Hao YAN,Zhen-yu NIE,Yang-mei LI. Cooperative control method for intelligent networked vehicles in ramp confluence area[J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(5): 1332-1346.

图/表 17

图1

图2

图3

表1

图4

图5

图6

表2

平均行程时间和延误"

参数	$f p 1$	$f p 2$	$f p 3$	$f p 4$	$f p 5$	$f q 1$	$f q 2$	$f q 3$	$f q 4$	$f q 5$
平均行程时间/s	33.92	31.83	27.09	25.39	25.24	31.22	30.30	25.97	25.92	25.44
平均延误时间/s	11.17	8.84	4.98	2.92	2.53	8.51	7.67	3.90	3.50	2.76

表2

图7

图8

图9

图10

图11

图12

图13

图14

表3

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S	［C₁］	［C₁， C₂］	［C₁， C₃］	［C₁， C₂， C₃］
策略	x₂， x₂， x₂	x₁， y₁， x₂	x₂， x₂，x₂	x₁， y₁， x₂；x₁， x₁， y₁
V（S）	F₁（t）	F₁（t）+F₂（t）	F₁（t）+F₃（t）	F₁（t）+F₂（t）+F₃（t）
V（S-i）	0	F' 2（t）	F' 3（t）	F' 2（t）+F' 3（t）
V（S）-V（S-i）	F₁（t）	F₁（t）+F₂（t）-F' 2（t）	F₁（t）+F₃（t）-F' 3（t）	F₁（t）+F₂（t）+F₃（t）-F' 2（t）-F' 3（t）
\|S\|	1	2	2	3
W（\|S\|）	1/3	1/6	1/6	1/3

编号	均值/s	偏度	峰度	统计量	秩平均值
1	3.23	1.68	3.36	0.83	1268.08
2	3.10	1.74	3.68	0.83	1247.32
3	2.37	1.79	4.47	0.82	881.67
4	4.49	1.16	1.39	0.91	1553.75