Eco-driving Trajectory Planning of a Heterogeneous Platoon in Urban Environments

被引:0
|
作者
Zhen, Hao [1 ]
Mosharafian, Sahand [2 ]
Yang, Jidong J. [1 ]
Velni, Javad Mohammadpour [2 ]
机构
[1] Univ Georgia, Sch Environm Civil Agr Mech Engn, Athens, GA 30602 USA
[2] Univ Georgia, Sch Elect & Comp Engn, Athens, GA 30602 USA
来源
IFAC PAPERSONLINE | 2022年 / 55卷 / 24期
基金
美国国家科学基金会;
关键词
Eco-driving; heterogeneous platoon; cooperative adaptive cruise control; trajectory planning; electric vehicles; connected and autonomous vehicles; VEHICLES; MODEL;
D O I
10.1016/j.ifaco1.2022.10.278
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Given the increasing popularity and demand for connected and autonomous vehicles (CAVs), Eco-driving and platooning in highways and urban areas to increase the efficiency of the traffic system is becoming a possibility. This paper presents an Eco-driving trajectory planning approach for a platoon of heterogeneous electric vehicles (EVs) in urban environments. The proposed control strategy for the platoon considers energy consumption, mobility and passenger comfort, with which vehicles may pass signalized intersections with no stops. For a given urban route, first, the platoon's leader vehicle employs dynamic programming (DP) to plan a trajectory for the anticipated path with the aim of balancing energy consumption, mobility and passenger comfort. Then, other following CAVs in the platoon either follow the preceding vehicles, using a PID-based cooperative adaptive cruise control, or plan their own trajectory by checking whether they can pass the next intersection without stopping. Furthermore, a heavy vehicle that cannot efficiently follow a light-weight vehicle would instead employ the DP-based trajectory planner. The results of simulation studies demonstrate the efficacy of the proposed control strategy with which the platoon's energy consumption is shown to reduce while the mobility is not compromised. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license
引用
收藏
页码:161 / 166
页数:6
相关论文
共 50 条
  • [41] Reactive Trajectory Planning and Tracking for Pedestrian-Aware Autonomous Driving in Urban Environments
    Cofield, Robert G.
    Gupta, Rakesh
    2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2016, : 747 - 754
  • [42] Uncertainties in Eco-Driving Instructions and Perceptions about Fuel Consumption Reduction Applying Eco-Driving Techniques
    Kreicbergs, J.
    Gailis, M.
    TRANSPORT MEANS 2015, PTS I AND II, 2015, : 119 - 122
  • [43] Behavioral Trajectory Planning for Motion Planning in Urban Environments
    Lim, Wonteak
    Lee, Seongjin
    Jo, Kichun
    Sunwoo, Myoungho
    2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2017,
  • [44] Eco-Driving System for Connected Automated Vehicles: Multi-Objective Trajectory Optimization
    Yang, Xianfeng Terry
    Huang, Ke
    Zhang, Zhehao
    Zhang, Zhao Alan
    Lin, Fang
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (12) : 7837 - 7849
  • [45] Eco-Driving: A Scientometric and Bibliometric Analysis
    Chen, Zhijun
    Xiong, Shengguang
    Chen, Qiushi
    Zhang, Yishi
    Yu, Jinqiu
    Jiang, Junfeng
    Wu, Chaozhong
    IEEE Transactions on Intelligent Transportation Systems, 2022, 23 (12): : 22716 - 22736
  • [46] Evaluation of an eco-driving support system
    Staubach, Maria, 1600, Elsevier Ltd (27):
  • [47] Modeling and Verification of Eco-Driving Evaluation
    Liu, Lin
    Hu, Nenglong
    Peng, Zhihu
    Zhan, Shuxian
    Gao, Jingting
    Wang, Hong
    JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2024, 20 (03): : 296 - 306
  • [48] Evaluation of an eco-driving support system
    Staubach, Maria
    Schebitz, Norbert
    Koester, Frank
    Kuck, Detlef
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2014, 27 : 11 - 21
  • [49] Benefits of Eco-Driving Case Study
    Pelenyte-Vysniauskiene, L.
    Silinskas, T.
    Bartulis, A.
    INTELLIGENT TECHNOLOGIES IN LOGISTICS AND MECHATRONICS SYSTEMS, ITELMS 2013, 2013, : 200 - 203
  • [50] On the Effectiveness of Hybridization Paired with Eco-Driving
    Nazari, Shima
    Prakash, Niket
    Siegel, Jason
    Stefanopoulou, Anna
    2019 AMERICAN CONTROL CONFERENCE (ACC), 2019, : 4635 - 4640