CAVSim: A Microscopic Traffic Simulator for Evaluation of Connected and Automated Vehicles

被引:12
|
作者
Zhang, Jiawei [1 ]
Chang, Cheng [1 ]
He, Zimin [1 ]
Zhong, Wenqin [2 ]
Yao, Danya [3 ,4 ]
Li, Shen [5 ]
Li, Li [3 ]
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Shenzhen 518057, Peoples R China
[3] Tsinghua Univ, Dept Automat, BNRist, Beijing 100084, Peoples R China
[4] Jiangsu Prov Collaborat Innovat Ctr Modern Urban T, Nanjing 210096, Peoples R China
[5] Tsinghua Univ, Dept Civil Engn, Beijing 100084, Peoples R China
关键词
Connected and automated vehicles (CAVs); microscope traffic simulator; cooperative driving; string stability; COOPERATIVE DRIVING STRATEGY; STABILITY; MODELS;
D O I
10.1109/TITS.2023.3273565
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Connected and automated vehicles (CAVs) are expected to play a vital role in the emerging intelligent transportation system. In recent years, researchers have proposed various cooperative driving methods for CAVs, and there is an urgent need for a generic and unified traffic simulator to simulate and evaluate these methods. However, traditional traffic simulators have two critical deficiencies for CAV simulation needs: 1) the planning and dynamical modeling of vehicles in traditional simulators are based on a feedback mode, which is incompatible with the feed-forward decision and planning that CAVs commonly adopt; 2) the traditional simulators cannot provide typical traffic scenarios and corresponding standardized algorithms for multi-CAV cooperative driving. In this paper, we introduce CAVSim, a novel microscopic traffic simulator for CAVs, to address these deficiencies. CAVSim is developed modularly according to the emerging technology of the CAV environment, emphasizes feed-forward decision and planning for CAVs, and highlights the cooperative decision and planning components in the CAV environment. CAVSim incorporates rich and typical traffic scenarios and provides standardized cooperative driving algorithms and comparable performance metrics for multi-CAV cooperative driving. With CAVSim, researchers can conveniently deploy decision, planning, and control methods for CAVs at different levels, evaluate their performance, compare them with the standardized algorithms incorporated in CAVSim, and even further explore their impact on traffic flow. As a unified platform for CAVs, CAVSim can facilitate the studies on CAVs and promote the advancement of methods and techniques for CAVs.
引用
收藏
页码:10038 / 10054
页数:17
相关论文
共 50 条
  • [41] Evolution of Traffic Microsimulation and Its Use for Modeling Connected and Automated Vehicles
    Raju, Narayana
    Farah, Haneen
    JOURNAL OF ADVANCED TRANSPORTATION, 2021, 2021
  • [42] Coordination for Connected Automated Vehicles at Merging Roadways in Mixed Traffic Environment
    Viet-Anh Le
    Wang, Hao M.
    Orosz, Gabor
    Malikopoulos, Andreas A.
    2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC, 2023, : 4150 - 4155
  • [43] Centralized Traffic Control via Small Fleets of Connected and Automated Vehicles
    Daini, Chiara
    Goatin, Paola
    Delle Monache, Maria Laura
    Ferrara, Antonella
    2022 EUROPEAN CONTROL CONFERENCE (ECC), 2022, : 371 - 376
  • [44] Human Factors in Modelling Mixed Traffic of Traditional, Connected, and Automated Vehicles
    Sharma, Anshuman
    Ali, Yasir
    Saifuzzaman, Mohammad
    Zheng, Zuduo
    Haque, Md. Mazharul
    ADVANCES IN HUMAN FACTORS IN SIMULATION AND MODELING (AHFE 2017), 2018, 591 : 262 - 273
  • [45] Influence of dedicated lanes for connected and automated vehicles on highway traffic flow
    Kim, Jongho
    Lim, Donghyun
    Seo, Younghoon
    So, Jaehyun
    Kim, Hyungjoo
    IET INTELLIGENT TRANSPORT SYSTEMS, 2023, 17 (04) : 678 - 690
  • [46] Modeling System Dynamics of Mixed Traffic With Partial Connected and Automated Vehicles
    An, Lianhua
    Yang, Xianfeng
    Hu, Jia
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (09) : 15755 - 15764
  • [47] Distributed Maneuver Planning With Connected and Automated Vehicles for Boosting Traffic Efficiency
    Goulet, Nathan
    Ayalew, Beshah
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (08) : 10887 - 10901
  • [48] Modeling System Dynamics of Mixed Traffic with Partially Connected and Automated Vehicles
    An, Lianhua
    Yang, Xianfeng
    Zhang, Yiming
    Zhang, Zihan
    Hu, Jia
    Wang, Haoran
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 2569 - 2569
  • [49] The Penetration Rate Effect of Connected and Automated Vehicles in Mixed Traffic Routing
    Houshmand, Arian
    Wollenstein-Betech, Salomon
    Cassandras, Christos G.
    2019 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2019, : 1755 - 1760
  • [50] Optimal Control and Coordination of Connected and Automated Vehicles at Urban Traffic Intersections
    Zhang, Yue J.
    Malikopoulos, Andreas A.
    Cassandras, Christos G.
    2016 AMERICAN CONTROL CONFERENCE (ACC), 2016, : 6227 - 6232