Multi-vehicle Cooperative Merging Control Strategy for Expressway under New Mixed Traffic Environment

被引:0
|
作者
Chen, Ying [1 ]
E, Wenjuan [1 ]
Wang, Xiang [1 ]
Wan, Qixing [1 ]
Wang, Cheng [1 ]
Yang, Na [1 ]
机构
[1] Soochow Univ, Sch Rail Transportat, Suzhou, Peoples R China
来源
2022 IEEE 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION ENGINEERING, ICITE | 2022年
关键词
CVIS; mixed traffic; ramp merging; cooperative control; dedicated CAVs lane; AUTOMATED VEHICLES; CONTROL FRAMEWORK; PHASE; FLOW;
D O I
10.1109/ICITE56321.2022.10101440
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the in-depth application of cooperative vehicle infrastructure system (CVIS) and automatic driving technology, a new traffic situation of hybrid driving of human driving vehicles (HDVs) and connected and automated Vehicles (CAVs) will certainly appear on the road in the future. Facing the problem of multi-vehicles confluence in the merging area of the expressway under the new mixed traffic environment, a cooperative merging control strategy is proposed to optimize the driving trajectories for the CAVs and reduce the traffic congestion in the merging area. First, on the basis of setting a dedicated CAVs lane on the mainline, different merging scenes are divided according to the traffic situations that the CAVs may encounter. Then, the vehicle cooperative merging model in the merging area is constructed to control the speed of CAVs. Finally, the model is analyzed and verified by simulation experiments. The simulation results show that the multi-vehicle cooperative merging control strategy proposed in this paper can make the speed distribution of the vehicles more uniform in the process of driving, and effectively improve passenger comfort and traffic efficiency in the merging area. At the same time, when the CAVs permeability is 50%, the total travel time in the system is also increased by about 8.09%.
引用
收藏
页码:603 / 608
页数:6
相关论文
共 44 条
  • [31] Coupling Control of Traffic Signal and Entry Lane at Isolated Intersections Under the Mixed-Autonomy Traffic Environment
    Dai, Rongjian
    Ding, Chuan
    Wu, Xinkai
    Yu, Bin
    Lu, Guangquan
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (10) : 10628 - 10642
  • [32] Theory and Experiment of Cooperative Control at Multi-Intersections in Intelligent Connected Vehicle Environment: Review and Perspectives
    Zhang, Linan
    Wang, Yizhe
    Zhu, Huaizhong
    SUSTAINABILITY, 2022, 14 (03)
  • [33] Cooperative traffic optimization with multi-agent reinforcement learning and evolutionary strategy: Bridging the gap between micro and macro traffic control
    Feng, Jianshuai
    Lin, Kaize
    Shi, Tianyu
    Wu, Yuankai
    Wang, Yong
    Zhang, Hailong
    Tan, Huachun
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 647
  • [34] Cooperative Control Strategy of Freeway Off-Ramp and Vicinity of Urban Traffic Signal Light for Mixed Traffic in Cyber-Physical System
    Huang, Shuai
    Sun, Dihua
    Zhao, Min
    Cheng, Senlin
    Liao, Xiaoyong
    Liu, Weining
    CICTP 2022: INTELLIGENT, GREEN, AND CONNECTED TRANSPORTATION, 2022, : 306 - 317
  • [35] Modeling impacts of Cooperative Adaptive Cruise Control on mixed traffic flow in multi-lane freeway facilities
    Liu, Hao
    Kan, Xingan
    Shladover, Steven E.
    Lu, Xiao-Yun
    Ferlis, Robert E.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 95 : 261 - 279
  • [36] Multi-View Graph Convolution Network Reinforcement Learning for CAVs Cooperative Control in Highway Mixed Traffic
    Xu, Dongwei
    Liu, Peiwen
    Li, Haijian
    Guo, Haifeng
    Xie, Zijia
    Xuan, Qi
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2024, 9 (01): : 2588 - 2599
  • [37] Collaborative control method of vehicles in U-turn zone under environment of cooperative vehicle infrastructure system
    Wu W.-J.
    Chen R.-C.
    Jia H.-F.
    Luo Q.-Y.
    Sun D.
    Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2019, 49 (04): : 1100 - 1106
  • [38] Collision-avoidance lane change control method for enhancing safety for connected vehicle platoon in mixed traffic environment
    Ma, Yitao
    Liu, Qiang
    Fu, Jie
    Liufu, Kangmin
    Li, Qing
    ACCIDENT ANALYSIS AND PREVENTION, 2023, 184
  • [39] Consensus-Based Control Strategy for Mixed Platoon under Delayed V2X Environment
    Zhao, Hang
    Sun, Dihua
    Jin, Shuang
    Zhao, Min
    Chen, Xinhai
    JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS, 2023, 149 (05)
  • [40] A novel self adaptive-electric fish optimization-based multi-lane changing and merging control strategy on connected and autonomous vehicle
    Vaishnavi, T.
    Sheeba Joice, C.
    WIRELESS NETWORKS, 2022, 28 (07) : 3077 - 3099