吉林大学学报(工学版) ›› 2024, Vol. 54 ›› Issue (1): 124-135.doi: 10.13229/j.cnki.jdxbgxb.20220207

• 交通运输工程·土木工程 • 上一篇    

智能网联公交车出站强制换道的演化博弈机制

杜筱婧(),姚荣涵()   

  1. 大连理工大学 交通运输学院,辽宁 大连 116024
  • 收稿日期:2022-03-04 出版日期:2024-01-30 发布日期:2024-03-28
  • 通讯作者: 姚荣涵 E-mail:duxiaojing@mail.dlut.edu.cn;cyanyrh@dlut.edu.cn
  • 作者简介:杜筱婧(1991-),女,博士研究生.研究方向:车辆驾驶行为的博弈分析.E-mail: duxiaojing@mail.dlut.edu.cn
  • 基金资助:
    国家自然科学基金项目(52172314);中央高校基本科研业务费专项资金项目(DUT20JC40);辽宁省自然科学基金项目(2022-MS-150)

Evolutionary game mechanism of mandatory lane changing for exiting for intelligent connected bus

Xiao-jing DU(),Rong-han YAO()   

  1. School of Transportation and Logistics,Dalian University of Technology,Dalian 116024,China
  • Received:2022-03-04 Online:2024-01-30 Published:2024-03-28
  • Contact: Rong-han YAO E-mail:duxiaojing@mail.dlut.edu.cn;cyanyrh@dlut.edu.cn

摘要:

为缓解智能网联公交车出站强制换道时与社会车辆之间的冲突,分析了智能网联公交车与社会车辆行为决策的演化博弈机制。考虑社会车辆为人工驾驶社会车辆和智能网联社会车辆两种场景,从安全效用、时间效用和节能效用角度构建演化博弈效用函数,并以此建立演化博弈的复制动态方程。根据动态博弈系统的雅克比矩阵的行列式和迹,分析不同情况下博弈的均衡点及其稳定性,并探讨动态博弈系统对合作策略与非合作策略差值的灵敏度。结果表明,动态博弈系统可能的演化方向包括“智能网联公交车换道、社会车辆让路”,“智能网联公交车不换道、社会车辆不让路”和“智能网联公交车不换道、社会车辆让路”。从整体最优的角度看,调整社会车辆安全效用和时间效用的相关变量,能够保证更多车辆在智能网联公交车出站强制换道过程中的安全和效率。节能效用对(换道,让路)策略组合有促进作用,对(不换道,不让路)策略组合有抑制作用。

关键词: 交通工程, 智能网联公交车, 强制换道, 演化博弈, 行为决策

Abstract:

To relieve the conflicts between the intelligent connected bus and the social vehicle in the mandatory lane changing for bus exiting, the evolutionary game mechanisms for their behavioral decision-makings are analyzed. Two scenarios where the social vehicles are human-driven and intelligent connected are considered. The utility functions in different strategy profiles of the evolutionary game are formulated from the perspectives of safety utility, time utility and energy-saving utility. On this basis, the replicator dynamics equations for the two scenarios are constructed. According to the determinant and trace of Jacobi matrix in the dynamic game system, the equilibrium points and their stability in different situations are analyzed deeply. The sensitivity of evolutionary results to the difference between the cooperative and non-cooperative strategies is explored. The results reveal that: the possible evolutionary directions in the dynamic game system involve “intelligent connected buses changing lanes, and social vehicles giving way”, “intelligent connected buses not changing lanes, and social vehicles not giving way”, and “intelligent connected buses not changing lanes, and social vehicles giving way”. From the perspective of overall optimization, adjusting the relevant variables of the safety and time utility of social vehicles can ensure the safety and efficiency of more vehicles in the process of mandatory lane changing of intelligent connected bus. The energy-saving utility promotes the strategy profile of changing lanes and giving way, and inhibits the strategy profile of not changing lanes and not giving way.

Key words: traffic engineering, intelligent connected bus, mandatory lane changing, evolutionary game, behavioral decision-making

中图分类号: 

  • U121

图1

智能网联公交车出站强制换道时与社会车辆不发生博弈的场景"

图2

智能网联公交车出站强制换道时的博弈场景"

表1

场景1中博弈的效用矩阵"

策略让路不让路
换道uBT-11+uVS-11+uBS-12-uVS-12-
不换道uBS-21++uBT-21-uVS-21++uVT-21-uBS-22+uVT-22+

表2

场景2中博弈的效用矩阵"

策略让路不让路
换道uBT-11+uVS-11++uVE-11+uBS-12-uVS-12-
不换道uBS-21++uBT-21-uVS-21++uVT-21-+uVE-21+uBS-22+uVT-22+

表3

各均衡点对应的雅克比矩阵的行列式和迹"

均衡点行列式
(0,0)-ΔB2?ΔS2-ΔB2+ΔS2
(0,1)ΔB1?ΔS2-ΔB1-ΔS2
(1,0)ΔB2?ΔS1ΔB2+ΔS1
(1,1)-ΔB1?ΔS1ΔB1-ΔS1
ΔS2/ΔS2-ΔS1,ΔB2/ΔB2-ΔB1ΔB1?ΔB2?ΔS1?ΔS2(ΔB1-ΔB2)?(ΔS1-ΔS2)0

表4

均衡点稳定性分析"

均衡点情形1情形2情形3情形4
(0,0)鞍点稳定点鞍点稳定点
(0,1)稳定点鞍点鞍点不稳定点
(1,0)不稳定点不稳定点不稳定点不稳定点
(1,1)鞍点鞍点稳定点稳定点
ΔS2/ΔS2-ΔS1,ΔB2/ΔB2-ΔB1---纳什均衡点

表5

不同类型效用的统计结果"

效用物理量平均值最大值最小值归一化值
安全效用/(m·s-2uBS-12--1.52-0.01-3.08-0.49
uBS-2j+1.443.360.020.42
uVS-i1+0.611.910.010.32
uVS-12--0.82-0.01-3.53-0.23
时间效用/suBT-11+664.751190.00234.500.45
uBT-21--778.10-448.90-1504.80-0.31
uVT-21--4.07-2.30-9.70-0.24
uVT-22+3.427.101.500.34
节能收益/[kg·(100 km)-1uVE-i1+7.4493.004.700.03

图3

p和q取不同初始值时的演化路径"

图4

初始状态为(0.8,0.3)时p和q的演化路径"

图5

不同ΔB1时策略比例的演化收敛图"

图6

不同ΔB2时策略比例的演化收敛图"

图7

不同ΔS1时策略比例的演化收敛图"

图8

不同ΔS2时策略比例的演化收敛图"

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