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A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System
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Cloud Control System Architectures, Technologies and Applications on Intelligent and Connected Vehicles: a Review

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  • Published: 09 March 2023

A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System

  • Bolin Gao  ORCID: orcid.org/0000-0002-5582-72891,
  • Keke Wan1,2,
  • Qien Chen1,3,
  • Zhou Wang1,4,
  • Rui Li1,2,
  • Yu Jiang1,2,
  • Run Mei1,4,
  • Yinghui Luo2 &
  • …
  • Keqiang Li  ORCID: orcid.org/0000-0001-6223-54011 

Machine Intelligence Research (2023)Cite this article

  • 64 Accesses

  • 1 Altmetric

  • Metrics details

Abstract

With the application of mobile communication technology in the automotive industry, intelligent connected vehicles equipped with communication and sensing devices have been rapidly promoted. The road and traffic information perceived by intelligent vehicles has important potential application value, especially for improving the energy-saving and safe-driving of vehicles as well as the efficient operation of traffic. Therefore, a type of vehicle control technology called predictive cruise control (PCC) has become a hot research topic. It fully taps the perceived or predicted environmental information to carry out predictive cruise control of vehicles and improves the comprehensive performance of the vehicle-road system. Most existing reviews focus on the economical driving of vehicles, but few scholars have conducted a comprehensive survey of PCC from theory to the status quo. In this paper, the methods and advances of PCC technologies are reviewed comprehensively by investigating the global literature, and typical applications under a cloud control system (CCS) are proposed. Firstly, the methodology of PCC is generally introduced. Then according to typical scenarios, the PCC-related research is deeply surveyed, including freeway and urban traffic scenarios involving traditional vehicles, new energy vehicles, intelligent vehicles, and multi-vehicle platoons. Finally, the general architecture and three typical applications of the cloud control system (CCS) on PCC are briefly introduced, and the prospect and future trends of PCC are proposed.

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Acknowledgements

This work was supported by the National Key Research and Development Program (No. 2021YFB2501000).

Author information

Authors and Affiliations

  1. School of Vehicle and Mobility, Tsinghua University, Beijing, 100084, China

    Bolin Gao, Keke Wan, Qien Chen, Zhou Wang, Rui Li, Yu Jiang, Run Mei & Keqiang Li

  2. College of Engineering, China Agricultural University, Beijing, 100083, China

    Keke Wan, Rui Li, Yu Jiang & Yinghui Luo

  3. School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China

    Qien Chen

  4. School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Zhou Wang & Run Mei

Authors
  1. Bolin Gao
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  2. Keke Wan
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  4. Zhou Wang
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  5. Rui Li
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  6. Yu Jiang
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  8. Yinghui Luo
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Corresponding author

Correspondence to Keqiang Li.

Additional information

Bolin Gao received the B. Sc. and M. Sc. degrees in vehicle engineering from Jilin University, China in 2007 and 2009, respectively, and the Ph. D. degree in vehicle engineering from Tongji University, China in 2013. He is now an associate research professor at School of Vehicle and Mobility, Tsinghua University, China. His research directions include the theoretical research and engineering application of the dynamic design and control of intelligent and connected vehicles.

His research interests include the collaborative perception and tracking method in cloud control system, intelligent predictive cruise control system on commercial trucks with cloud control mode, as well as the test and evaluation of intelligent vehicle driving system.

E-mail: gaobolin@tsinghua.edu.cn

ORCID iD: 0000-0002-5582-7289

Keke Wan received the B. Eng. degree in vehicle engineering from Henan University of Engineering, China in 2020. He is currently a master student in vehicle engineering at College of Engineering, China Agricultural University, China. He is engaged in research work in Intelligent and Connected Vehicle of Tsinghua (THICV) Group, School of Vehicle and Mobility, Tsinghua University, China, with a research focus on predictive cruise control and cloud control system.

His research interests include cloud-based predictive cruise control, vehicle-road-cloud collaborative control and cloud control architecture.

E-mail: wankeke@cau.edu.cn

Qien Chen received the B. Eng. degree in industrial engineering from Shanghai Ocean University, China in 2020. Currently, he is a master student in vehicle engineering at School of Electro-mechanical Engineering, Guangdong University of Technology, China. Since 2021, he has engaged in research work in School of Vehicle and Mobility, Tsinghua University, China.

His research interests include predictive cruise control and cloud control system.

E-mail: 2112001475@mail2.gdut.edu.cn

Zhou Wang received the B. Eng. degree in instrument science and technology from Wuhan University of Technology, China in 2019. Currently, he is a master student in instruments science and technology at School of Mechanical and Electrical Engineering, Wuhan University of Technology, China. He is engaged in research work in School of Vehicle and Mobility, Tsinghua University, China.

His research interests include predictive cruise control of vehicle platoon and cloud control system.

E-mail: wz2020@whut.edu.cn

Rui Li received the B. Eng. degree in vehicle engineering from Shandong University of Technology, China in 2020. He is currently a master student in mechanical engineering at College of Engineering, China Agricultural University, China. He is engaged in research work in THICV Group, School of Vehicle and Mobility, Tsinghua University, China, with a research focus on adaptive cruise control.

His research interests include cloud-based predictive adaptive cruise control and cloud control system.

E-mail: lirui@cau.edu.cn

Yu Jiang received the B. Eng. degree in vehicle engineering from Harbin Institute of Technology, China in 2021. Currently, he is a master student in mechanical engineering, College of Engineering, China Agricultural University, China. And he is engaged in research work in School of Vehicle and Mobility, Tsinghua University, China.

His research interests include lane-changing decision and control, and cloud control system.

E-mail: jiangyu@cau.edu.cn

Run Mei received the B. Eng. degree in instrument science and technology from Wuhan University of Technology, China in 2020. Currently, he is a master student in instruments science and technology at School of Mechanical and Electrical Engineering, Wuhan University of Technology, China. He is engaged in research work in School of Vehicle and Mobility, Tsinghua University, China.

His research interests include platoon lane-changing and cloud control system.

E-mail: 1301076746@qq.com

Yinghui Luo received the B. Eng. degree in engineering from Luoyang Institute of Science and Technology, China in 2020. He is currently a master student in vehicle engineering at College of Engineering, China Agricultural University, China.

His research interests include intelligent controls and machine learning.

E-mail: luoyinghui@cau.edu.cn

Keqiang Li received the B. Sc. degree in mechanical engineering from Tsinghua University, China in 1985, and the M. Sc. and Ph. D. degrees in mechanical engineering from Chongqing University, China in 1988 and 1995, respectively. He is an academician of the Chinese Academy of Engineering, and a professor at School of Vehicle and Mobility, Tsinghua University, China. He is also the director of State Key Laboratory of Automotive Safety and Energy and a senior member of SAE-China. He has authored over 200 articles and holds over 60 patents.

His research interests include intelligent and connected vehicles, vehicle dynamics, and cloud control system.

E-mail: likq@mail.tsinghua.edu.cn (Corresponding author)

ORCID iD: 0000-0001-6223-5401

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Gao, B., Wan, K., Chen, Q. et al. A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System. Mach. Intell. Res. (2023). https://doi.org/10.1007/s11633-022-1395-3

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  • Received: 11 August 2022

  • Accepted: 11 November 2022

  • Published: 09 March 2023

  • DOI: https://doi.org/10.1007/s11633-022-1395-3

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Keywords

  • Predictive cruise control (PCC)
  • cloud control system (CCS)
  • cooperative control
  • efficient operation
  • intelligent connected vehicle
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