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作者:

Fu, Anqi (Fu, Anqi.) | Chen, Sijia (Chen, Sijia.) | Qiao, Junfei (Qiao, Junfei.) | Yu, Chengpu (Yu, Chengpu.)

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摘要:

Cooperative Adaptive Cruise Control (CACC) based vehicle platooning can increase the safety and efficiency of traffic. This work looks into the communication and control problems of vehicle platooning, and proposes a control and communication co-design for CACC. First, an integrated radar system is presented. This system integrates sensing of relative position, speed, and communication between a predecessor and its follower. Second, a working scheme for the integrated radar system is presented. This scheme allows the radar systems to switch periodically between different working modes without interferences from other modes. Therefore, the relative position, speed, and communication can be asynchronously periodically updated to the controller. Third, a periodic event-triggered control approach is presented. This approach allows asynchronous periodic sampling of the output, and is deeply co-designed with the radar system and its working scheme. Delays are also considered in the control approach. The co-design CACC approach can guarantee the vehicle platoons to be string stable. A numerical example has shown the feasibility of the approach. © 2023 Association for Computing Machinery. All rights reserved.

关键词:

Vehicle to vehicle communications Adaptive cruise control Cooperative communication Vehicles

作者机构:

  • [ 1 ] [Fu, Anqi]Faculty of Information Technology, Beijing University of Technology, Key Laboratory of Computational Intelligence and Intelligent Systems, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection; Beijing Artificial Intelligence Institute,, China
  • [ 2 ] [Chen, Sijia]Faculty of Information Technology, Beijing University of Technology, Key Laboratory of Computational Intelligence and Intelligent Systems, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection; Beijing Artificial Intelligence Institute,, China
  • [ 3 ] [Qiao, Junfei]Faculty of Information Technology, Beijing University of Technology, Key Laboratory of Computational Intelligence and Intelligent Systems, Beijing University of Technology, Beijing Laboratory of Smart Environmental Protection; Beijing Artificial Intelligence Institute,, China
  • [ 4 ] [Yu, Chengpu]School of Automation, Beijing Institute of Technology, China and Beijing Institute of Technology Chongqing Innovation Center,, China

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来源 :

ACM Transactions on Cyber-Physical Systems

ISSN: 2378-962X

年份: 2023

期: 4

卷: 7

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