A platoon-based eco-driving control mechanism for low-density traffic flow

被引:2
作者
Liu, Qingling [1 ]
Xu, Xiaowen [1 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Shaanxi, Peoples R China
关键词
Eco-driving control mechanism; Platoon-based traffic flow with small-sized; platoons; Connected and automated vehicles; Low-density traffic corridors; SIGNALIZED INTERSECTION; TRAJECTORY DESIGN; FUEL-EFFICIENCY; VEHICLES; OPTIMIZATION; SYSTEM; DRIVER; MODEL; TECHNOLOGY; VICINITY;
D O I
10.1016/j.physa.2024.129540
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Forming traffic into platoons on the road has the potential for mitigation of traffic congestion and improvement in fuel economy, and can be more readily achieved by leveraging emerging connected and automated vehicles. This paper proposes a platoon-based eco-driving control mechanism that forms small-sized platoons and guides them to move on low-density traffic corridors. To facilitate this investigation, a low-density traffic corridor is divided into an initial road segment plus a series of subsequent road segments. To ensure computational efficiency, an approximate model based on the predefined function is employed. Simulation shows that traffic flow of small-sized platoons can bring considerable benefits in fuel consumption compared to that of large-sized platoons. This proposed control mechanism is shown to be significant in fuel economy.
引用
收藏
页数:10
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共 45 条
  • [11] Eco-driving technology for sustainable road transport: A review
    Huang, Yuhan
    Ng, Elvin C. Y.
    Zhou, John L.
    Surawski, Nic C.
    Chan, Edward F. C.
    Hong, Guang
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2018, 93 : 596 - 609
  • [12] Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment
    Jiang, Huifu
    Hu, Jia
    An, Shi
    Wang, Meng
    Park, Byungkyu Brian
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2017, 79 : 290 - 307
  • [13] Dynamical analysis of an optimal velocity model with time-delayed feedback control
    Jin, Yanfei
    Meng, Jingwei
    [J]. COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2020, 90
  • [14] Leveraging Connected Vehicle Technology and Telematics to Enhance Vehicle Fuel Efficiency in the Vicinity of Signalized Intersections
    Kamalanathsharma, Raj Kishore
    Rakha, Hesham A.
    [J]. JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 20 (01) : 33 - 44
  • [15] Nonlinear Consensus-Based Connected Vehicle Platoon Control Incorporating Car-Following Interactions and Heterogeneous Time Delays
    Li, Yongfu
    Tang, Chuancong
    Peeta, Srinivas
    Wang, Yibing
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 20 (06) : 2209 - 2219
  • [16] Nonlinear finite-time consensus-based connected vehicle platoon control under fixed and switching communication topologies
    Li, Yongfu
    Tang, Chuancong
    Li, Kezhi
    Peeta, Srinivas
    He, Xiaozheng
    Wang, Yibing
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 93 : 525 - 543
  • [17] An eco-driving strategy for electric vehicle based on the powertrain
    Liao, Peng
    Tang, Tie-Qiao
    Liu, Ronghui
    Huang, Hai-Jun
    [J]. APPLIED ENERGY, 2021, 302
  • [18] Optimal Platoon Trajectory Planning Approach at Arterials
    Liu, Meiqi
    Wang, Meng
    Hoogendoorn, Serge
    [J]. TRANSPORTATION RESEARCH RECORD, 2019, 2673 (09) : 214 - 226
  • [19] Parsimonious shooting heuristic for trajectory design of connected automated traffic part II: Computational issues and optimization
    Ma, Jiaqi
    Li, Xiaopeng
    Zhou, Fang
    Hu, Jia
    Park, B. Brian
    [J]. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2017, 95 : 421 - 441
  • [20] On-ramp merging strategy for connected and automated vehicles based on complete information static game
    Min, Haigen
    Fang, Yukun
    Wu, Xia
    Wu, Guoyuan
    Zhao, Xiangmo
    [J]. JOURNAL OF TRAFFIC AND TRANSPORTATION ENGINEERING-ENGLISH EDITION, 2021, 8 (04) : 582 - 595