Cooperative Adaptive Cruise Control and Decision Making for Fuel-Efficient Vehicle Platooning

被引:0
|
作者
Jia, Xiaomeng [1 ,2 ]
Zhou, Jianshan [1 ,2 ]
Duan, Xuting [1 ,2 ]
Sheng, Zhengguo [3 ]
Tian, Daxin [2 ]
机构
[1] Minist Transport, Key Lab Technol Intelligent Transportat Syst, Beijing 100088, Peoples R China
[2] Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China
[3] Univ Sussex, Dept Engn & Design, Brighton BN1 9RJ, E Sussex, England
关键词
CACC; Fuel efficient; Vehicle platoon;
D O I
10.1007/978-981-99-0479-2_24
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cooperative Adaptive Cruise Control (CACC) is a new generation of driver assistance systems developed on the basis of traditional cruise control. It has played a positive role in improving driving safety, reducing the incidence of traffic accidents, and reducing fatigue in driving. At the same time, the application of this technology can help form a vehicle platoon with a certain distance among vehicles. During the driving of most vehicles, the platoon can effectively reduce the wind resistance of subsequent vehicles, thus improving fuel economy. However, in practice, whether the two vehicles need to form a platoon and whether the fuel consumption will be reduced after forming a platoon are both questions that need to be considered. In this paper, the vehicle kinematics model and control model based on Model Predictive Control (MPC) are given first, and a fuel-saving rate calculation model is established. According to the fuel saving rate, whether the vehicle is to join the vehicle platoon is determined. Finally, we develop a simulink-based simulation system and conduct simulation experiments to verify the effectiveness of our proposed method.
引用
收藏
页码:252 / 261
页数:10
相关论文
共 50 条
  • [21] Freeway vehicle fuel efficiency improvement via cooperative adaptive cruise control
    Liu, Hao
    Shladover, Steven E.
    Lu, Xiao-Yun
    Kan, Xingan
    JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 25 (06) : 574 - 586
  • [22] Fuel-Efficient Switching Control for Platooning Systems With Deep Reinforcement Learning
    Goncalves, Tiago Rocha
    Cunha, Rafael Fernandes
    Varma, Vineeth Satheeskumar
    Elayoubi, Salah Eddine
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (12) : 13989 - 13999
  • [23] Prediction of Preceding Driver Behavior for Fuel Efficient Cooperative Adaptive Cruise Control
    Lang, Dominik
    Schmied, Roman
    Del Re, Luigi
    SAE INTERNATIONAL JOURNAL OF ENGINES, 2014, 7 (01) : 14 - 20
  • [24] Truck platooning on uphill grades under cooperative adaptive cruise control (CACC)
    Chen, Danjue
    Ahn, Soyoung
    Chitturi, Madhav
    Noyce, David
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2018, 94 : 50 - 66
  • [25] Truck Platooning on Uphill Grades under Cooperative Adaptive Cruise Control (CACC)
    Chen, Danjue
    Ahn, Soyoung
    Chitturi, Madhav
    Noyce, David
    PAPERS SELECTED FOR THE 22ND INTERNATIONAL SYMPOSIUM ON TRANSPORTATION AND TRAFFIC THEORY, 2017, 23 : 1059 - 1078
  • [26] Impact of Communication Loss on MPC based Cooperative Adaptive Cruise Control and Platooning
    Razzaghpour, Mahdi
    Shahram, Shahriar
    Valiente, Rodolfo
    Fallah, Yaser P.
    2021 IEEE 94TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-FALL), 2021,
  • [27] Vehicle Sequence Reordering with Cooperative Adaptive Cruise Control
    Huang, Ta-Wei
    Tsai, Yun-Yun
    Lin, Chung-Wei
    Ho, Tsung-Yi
    2019 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2019, : 610 - 613
  • [28] Cooperative Adaptive Cruise Control of Heterogeneous Vehicle Platoons
    Lefeber, Erjen
    Ploeg, Jeroen
    Nijmeijer, Henk
    IFAC PAPERSONLINE, 2020, 53 (02): : 15217 - 15222
  • [29] Cooperative Adaptive Cruise Control With Unconnected Vehicle in the Loop
    Chen, Zheng
    Park, Byungkyu Brian
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (05) : 4176 - 4186
  • [30] Spacing Control of Cooperative Adaptive Cruise Control Vehicle Platoon
    Duc Lich Luu
    Lupu, Ciprian
    Ismail, Laith S.
    Alshareefi, Hamid
    PROCEEDINGS OF 2020 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION, QUALITY AND TESTING, ROBOTICS (AQTR), 2020, : 445 - 450