Paper Search

Complex Systems and Complexity Science >

2024 , Vol. 21 >Issue 3: 128 - 135

DOI: https://doi.org/10.13306/j.1672-3813.2024.03.017

Research Paper

Evolutionary Game Mechanisms of Lane Changing for Intelligent Connected Vehicles on Traffic Flow Frequently Changing Sections

  • DAI Shouchen ,
  • QU Dayi ,
  • MENG Yiming ,
  • YANG Yufeng ,
  • WANG Qikun ,
  • DAI Shouchen ,
  • QU Dayi ,
  • MENG Yiming ,
  • YANG Yufeng ,
  • WANG Qikun
Expand
  • School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China

Received date: 2022-12-15

  Revised date: 2023-03-22

  Online published: 2024-11-07

Fold

Abstract

In order to study the evolutionary mechanism of lane changing for intelligent connected vehicles on urban traffic flow frequently changing sections and reduce the decision conflict of vehicle lane changing, the human-vehicle interaction was realized and the evolutionary dynamic equations were established by quantifying the vehicle revenue and weight coefficient. According to the Jacobi matrix of the game system, the stability of the equilibrium points were analyzed. Finally, the numerical simulation was used to determine the evolution path and the sensitivity analysis of the influencing factors was carried out. The results show that the initial ratio of different driving decisions will affect the evolution direction of the decision, and the left-turn green time will enhance the evolution of vehicle strategy in the direction of changing lane and giving way, and the evolution of vehicle strategy in the direction of changing lane and giving way as the position of decision time decreases.

Key words： intelligent connected vehicles; traffic flow frequently changing sections; forced lane change; evolutionary game

Cite this article

DAI Shouchen , QU Dayi , MENG Yiming , YANG Yufeng , WANG Qikun , DAI Shouchen , QU Dayi , MENG Yiming , YANG Yufeng , WANG Qikun . Evolutionary Game Mechanisms of Lane Changing for Intelligent Connected Vehicles on Traffic Flow Frequently Changing Sections[J]. Complex Systems and Complexity Science, 2024 , 21(3) : 128 -135 . DOI: 10.13306/j.1672-3813.2024.03.017

References

[1] 丁建勋,郑杨边牧,张梦婷, 等.临近交叉口的车辆跟驰换道行为研究[J]. 交通运输系统工程与信息, 2017, 17(3): 60-66.
DING J X,ZHENG Y B M,ZHANG M T, et al. Car-following and lane-changing behaviors near an intersection[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(3): 60-66.
[2] 成卫,周通,李冰. 驾驶员变更车道对信号交叉口交通流的影响[J]. 昆明理工大学学报(自然科学版), 2021, 46(3): 149-154.
CHENG W, ZHOU T, LI B. Influence of driver changing lane on traffic flow at signalized intersections[J]. Journal of Kunming University of Science and Technology (Natural Sciences), 2021, 46(3): 149-154.
[3] ZHOU M F,YU Y,QU X B. Development of an efficient driving strategy for connected and automated vehicles at signalized intersections: a reinforcement learning approach[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(1): 433-443.
[4] 杨达,杨果,罗旭, 等. 考虑前车状态的智能网联车交叉口行为决策[J]. 西南交通大学学报, 2022, 57(2): 410-417,433.
YANG D,YANG G,LUO X, et al. Behavior decision of intelligent connected vehicles considering status of preceding vehicles at intersections[J]. Journal of Southwest Jiaotong University, 2022, 57(2): 410-417,433.
[5] 宗芳,石蕊,刘怿轩, 等. 信号交叉口行车风险场建立及车辆通行行为优化[J]. 中国公路学报, 2022, 35(10): 244-253.
ZONG F,SHI R,LIU Z X, et al. Construction of risk field and optimization of driving behaviors for signalized intersections[J]. China Journal of Highway and Transport, 2022, 35(10): 244-253.
[6] 叶颖俊,倪颖,孙剑. 高密度瓶颈交通流主动-回应汇入行为定义与建模[J]. 中国公路学报, 2022, 35(8): 278-290.
YE Y J,NI Y,SUN J. Defining and modeling active-responsive merging behavior at high-density expressway on-ramp bottlenecks[J]. China Journal of Highway and Transport, 2022, 35(8): 278-290.
[7] ZHANG K K,QU D Y,SONG H, et al. Analysis of lane-changing decision-making behavior and molecular interaction potential modeling for connected and automated vehicles[J]. Sustainability, 2022, 14(17): 1-20.
[8] 张可琨,曲大义,宋慧, 等. 自动驾驶车辆换道博弈策略分析及建模[J]. 复杂系统与复杂性科学, 2022, 12(7): 1-10.
ZHANG K K,QU D Y,SONG H, et al. Analysis and modeling for lane-changing game strategy of autonomous vehicles[J]. Complex Systems and Complexity Science, 2022, 12(7): 1-10.
[9] GUO J,HARMATI I. Lane-changing decision modelling in congested traffic with a game theory-based decomposition algorithm[J]. Engineering Applications of Artificial Intelligence, 2022, 107(5): 104530-50.
[10] QU D Y,ZHANG K K,SONG H, et al. Analysis and modeling of lane-changing game strategy for autonomous driving vehicles[J]. IEEE Access, 2022, 10(2): 69531-42.
[11] SHAO H P,ZHANG M R,FENG T, et al. A discretionary lane-changing decision-making mechanism incorporating drivers’heterogeneity: a signalling game-based approach[J]. Journal of Advanced Transportation, 2020, 10(16): 1-16.
[12] LADINO A,WANG M. A dynamic game formulation for cooperative and change strategies at highway merges[J]. IFAC-PapersOnLine. 2020, 53(2): 15059-64.
[13] 肖雪,李克平,彭博, 等. 基于决策-规划迭代框架的智驾车换道行为建模[J]. 吉林大学学报(工学版), 2023, 53(3): 746-757.
XIAO X,LI K P,PENG B, et al. Integrated lane-changing model of decision making and motion planning for autonomous vehicles[J]. Journal of Jilin University (Engineering Edition), 2023, 53(3): 746-757.
[14] 禹乐文,罗霞,刘仕焜. 复杂车路环境下自动驾驶车辆换道仿真研究[J]. 计算机仿真, 2021, 38(5): 146-152.
YU L W,LUO X,LIU S K. Research on simulation of lane-changing for autonomous vehicles under complex road conditions[J]. Computer Simulation, 2021, 38(5): 146-152.
[15] ZHANG X G,GAO J P,LI L, et al. Expressway lane change in fog environment by dynamic strategic game[J]. Journal of Advanced Transportation, 2022, 10(1): 1-10.
[16] PENG H,HUANG C,HU X Z, et al. Decision making for connected automated vehicles at urban intersections considering social and individual benefits[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23: 22549-56.
[17] 杜筱婧,姚荣涵. 智能网联公交车出站强制换道的演化博弈机制[J]. 吉林大学学报(工学版), 2024, 54(1): 124-135.
DU X J,YAO R H. Evolutionary game mechanism of mandatory lane changing for exiting for intelligent connected bus[J]. Journal of Jilin University (Engineering Edition), 2024, 54(1): 124-135.
[18] 李超然,刘举胜,宋美,等, 演化博弈视角下的医患关系分析及对策研究[J]. 复杂系统与复杂性科学, 2022, 19(3): 44-54.
LI C R,LIU J S,SONG M, et al. Analysis of doctor-patient relationship and countermeasures from the perspective of evolutionary game[J]. Complex Systems and Complexity Science, 2022, 19(3): 44-54.
[19] 彭伟华,侯仁勇,李光红. 基于演化博弈的网络平台就业多元协同治理研究[J]. 复杂系统与复杂性科学, 2022, 19(2): 9-16,30.
PENG W H,HOU R Y,LI G H. Research on multiple collaborative governance of network platform employment based on evolutionary game[J]. Complex Systems and Complexity Science, 2022, 19(2): 9-16,30.
[20] 李春发,刘焕星,胡培培. 政府分类规制、智能平台赋能与药企CSR策略演化[J]. 复杂系统与复杂性科学, 2022, 19(2): 17-30.
LI C F,LIU H X,HU P P. Government classification regulation, intelligent platform empowerment and CSR strategy evolution of pharmaceutical enterprises[J]. Complex Systems and Complexity Science, 2022, 19(2): 17-30.
Options
Outlines

/

〈 〉

Copyright © 2017 Editorial Office of Complex Systems and Complexity Science
Tel.：0532-85953597 E-mail:fzkxbjb@qdu.edu.cn