Platoon Merging Approach Based on Hybrid Trajectory Planning and CACC Strategies

被引:26
|
作者
Hidalgo, Carlos [1 ]
Lattarulo, Ray [1 ]
Flores, Carlos [2 ]
Perez Rastelli, Joshue [1 ]
机构
[1] Tecnalia Res & Innovat, Ind & Transportat Div, Dept Automot, Derio 48160, Spain
[2] Univ Calif Berkeley, Inst Transportat Studies, Calif PATH Program, Richmond, CA 94804 USA
基金
欧盟地平线“2020”;
关键词
hybrid trajectory planning approach; CACC; cooperative merging; ADAPTIVE CRUISE CONTROL; PATH; VALIDATION; VEHICLES;
D O I
10.3390/s21082626
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Currently, the increase of transport demands along with the limited capacity of the road network have increased traffic congestion in urban and highway scenarios. Technologies such as Cooperative Adaptive Cruise Control (CACC) emerge as efficient solutions. However, a higher level of cooperation among multiple vehicle platoons is needed to improve, effectively, the traffic flow. In this paper, a global solution to merge two platoons is presented. This approach combines: (i) a longitudinal controller based on a feed-back/feed-forward architecture focusing on providing CACC capacities and (ii) hybrid trajectory planning to merge platooning on straight paths. Experiments were performed using Tecnalia's previous basis. These are the AUDRIC modular architecture for automated driving and the highly reliable simulation environment DYNACAR. A simulation test case was conducted using five vehicles, two of them executing the merging and three opening the gap to the upcoming vehicles. The results showed the good performance of both domains, longitudinal and lateral, merging multiple vehicles while ensuring safety and comfort and without propagating speed changes.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] Performance Analysis of V2V-Based Vehicular Platoon with Modified CACC Scheme
    Zhou, Siyuan
    Xiang, Liangliang
    Tan, Guoping
    WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, WASA 2021, PT III, 2021, 12939 : 491 - 502
  • [32] Trajectory Planning for Automated Merging Vehicles on Freeway Acceleration Lane
    Gu, Menglu
    Su, Yanqi
    Wang, Chang
    Guo, Yingshi
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 73 (11) : 16108 - 16124
  • [33] Optimal vehicle trajectory planning in the context of cooperative merging on highways
    Ntousakis, Ioannis A.
    Nikolos, Loannis K.
    Papageorgiou, Markos
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2016, 71 : 464 - 488
  • [34] Deep Q-Network-Enabled Platoon Merging Approach for Autonomous Vehicles
    Wang, Jiawen
    Hu, Chenxi
    Zhao, Jing
    Zhang, Lingzhi
    Han, Yin
    TRANSPORTATION RESEARCH RECORD, 2024, 2678 (07) : 17 - 31
  • [35] Receding Horizon Cooperative Platoon Trajectory Planning on Corridors with Dynamic Traffic Signal
    Liu, Meiqi
    Hoogendoorn, Serge
    Wang, Meng
    TRANSPORTATION RESEARCH RECORD, 2020, 2674 (12) : 324 - 338
  • [36] Optimal Platoon Merging and Catch-up Approach for Connected Electric Vehicles
    Su, Zifei
    Chen, Pingen
    2022 AMERICAN CONTROL CONFERENCE, ACC, 2022, : 1964 - 1969
  • [37] A Trajectory Based Optimization Approach for Hybrid Observer design
    Oliva, F.
    Mattogno, S.
    Tenaglia, A.
    Masocco, R.
    Martinelli, F.
    Carnevale, D.
    2023 62ND IEEE CONFERENCE ON DECISION AND CONTROL, CDC, 2023, : 1873 - 1878
  • [38] Comparative Study of Cooperative Platoon Merging Control Based on Reinforcement Learning
    Irshayyid, Ali
    Chen, Jun
    SENSORS, 2023, 23 (02)
  • [39] A cooperative merging speed control strategy of CAVs based on virtual platoon in on-ramp merging system
    Yang, Wenzhang
    Dong, Changyin
    Wang, Hao
    TRANSPORTMETRICA B-TRANSPORT DYNAMICS, 2023, 11 (01) : 1432 - 1454
  • [40] Hybrid optimization approach for rapid endo-atmospheric ascent trajectory planning
    Huang, Panxing
    Wei, Changzhu
    Gu, Yuanbei
    Cui, Naigang
    AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 2016, 88 (04): : 473 - 479