Multianticipation for string stable Adaptive Cruise Control and increased motorway capacity without vehicle-to-vehicle communication

被引:21
作者
Dona, Riccardo [1 ]
Mattas, Konstantinos [2 ]
He, Yinglong [3 ]
Albano, Giovanni [4 ]
Ciuffo, Biagio [2 ]
机构
[1] Uni Syst Italy, Milan, Italy
[2] European Commiss Joint Res Ctr, Ispra, VA, Italy
[3] Univ Cambridge, Cambridge CB3 0HA, England
[4] Seidor Italia Srl, Milan, Italy
基金
英国科研创新办公室;
关键词
Adaptive cruise control; Car-following; Multianticipation; String stability; Traffic dynamics; Microsimulation; CAR-FOLLOWING MODELS; TRAFFIC-FLOW; STABILITY ANALYSIS; LINEAR-STABILITY; CONGESTION;
D O I
10.1016/j.trc.2022.103687
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
Adaptive Cruise Control (ACC) systems have been expected to solve many problems of motorway traffic. Now that they are widespread, it is observed that the majority of existing systems are string unstable. Therefore, small perturbations in the speed profile of a vehicle are amplified for the vehicles following upstream, with negative impacts on traffic flow, fuel consumption, and safety. Increased headway settings provide more stable flow but at the same time it deteriorates the capacity. Substantial research has been carried out in the past decade on utilizing connectivity to overcome this trade-off. However, such connectivity solutions have to overcome several obstacles before deployment and there is the concrete risk that motorway traffic flow will considerably deteriorate in the meanwhile. As an alternative solution, the paper explores multianticipation without inter-vehicle communication, taking advantage of the recent advancements in the field of RADAR sensing. An analytical study is carried out, based on the most widely used model and parameter settings used to simulate currently available commercial ACC systems, comparing the transfer functions and step responses for the nominal and the multi anticipative formulations. Then, a microsimulation framework is employed to validate our claim on different speed profiles. Analytical results demonstrate that multianticipation enhances stability without impacting traffic flow. On the contrary, the simulation study indicates that the multianticipative-ACC can produce higher road capacity even in the presence of external disturbances and for a wide range of calibrated parameters. Finally, optimality conditions for the tuning of the headway policy are derived from a Pareto optimization.
引用
收藏
页数:18
相关论文
共 66 条
  • [1] [Anonymous], 2021, ARXIV PREPRINT ARXIV
  • [2] [Anonymous], 2016, TESLA AUTOPILOT V80
  • [3] AN EXTENDED MODEL FOR CAR-FOLLOWING
    BEXELIUS, S
    [J]. TRANSPORTATION RESEARCH, 1968, 2 (01): : 13 - &
  • [4] The costs of urban congestion: Estimation of welfare losses arising from congestion on cross-town link roads
    Bilbao-Ubillos, Javier
    [J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2008, 42 (08) : 1098 - 1108
  • [5] Will Automated Vehicles Negatively Impact Traffic Flow?
    Calvert, S. C.
    Schakel, W. J.
    van Lint, J. W. C.
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2017,
  • [6] Effects of ACC and CACC vehicles on traffic flow based on an improved variable time headway spacing strategy
    Chen, Jianzhong
    Zhou, Yang
    Liang, Huan
    [J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2019, 13 (09) : 1365 - 1373
  • [7] Chen XQ, 2009, 2009 12TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC 2009), P72
  • [8] Requiem on the positive effects of commercial adaptive cruise control on motorway traffic and recommendations for future automated driving systems
    Ciuffo, Biagio
    Mattas, Konstantinos
    Makridis, Michail
    Albano, Giovanni
    Anesiadou, Aikaterini
    He, Yinglong
    Josvai, Szilard
    Komnos, Dimitris
    Pataki, Marton
    Vass, Sandor
    Szalay, Zsolt
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2021, 130
  • [9] A Review of Communication, Driver Characteristics, and Controls Aspects of Cooperative Adaptive Cruise Control (CACC)
    Dey, Kakan C.
    Yan, Li
    Wang, Xujie
    Wang, Yue
    Shen, Haiying
    Chowdhury, Mashrur
    Yu, Lei
    Qiu, Chenxi
    Soundararaj, Vivekgautham
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (02) : 491 - 509
  • [10] Dona R., ACCIDENT ANAL PREV