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面向智能网联汽车的车路协同感知技术及发展趋势

  • Xin Yu Zhang
  • , Yi Guo Lu
  • , Xin Gao*
  • , Yu Ning Huang
  • , Hua Ping Liu
  • , Yun Peng Wang
  • , Jun Li
  • *此作品的通讯作者
  • Tsinghua University
  • Xinjiang University
  • China University of Mining & Technology, Beijing

科研成果: 期刊稿件文献综述同行评审

摘要

With the continuous development of perception technology and the improvement of intelligent transportation infrastructure, the status of intelligent connected vehicle applications in the field of autonomous driving has been gradually improved. Autonomous driving perception has progressed from single-vehicle intelligence to vehicle-road collaboration, and several new collaborative perception technologies and methods have emerged in recent years. The purpose of this paper is to comprehensively describe the vehicle-road collaborative perception technology for intelligent connected vehicles, and summarize the relevant available data and the development trend in this direction. Firstly, the collaborative perception strategies for intelligent connected vehicles are divided, and the advantages and shortcomings of different perception strategies are summarized; Secondly, the key technologies of collaborative perception for intelligent connected vehicles are elaborated, including the perception technology and communication technology in the process of vehicle-road collaborative perception; Then the vehicle-road collaborative perception methods are summarized, and the research related to solving the problems of perception fusion (PF), perception selection and compression (SC) in collaborative perception in recent years are summarized; Finally, the large-scale dataset of vehicle-road collaborative perception is organized, and the development trend of collaborative perception of intelligent connected vehicles is analyzed.

投稿的翻译标题Vehicle-road Collaborative Perception Technology and Development Trend for Intelligent Connected Vehicles
源语言繁体中文
页(从-至)233-248
页数16
期刊Zidonghua Xuebao/Acta Automatica Sinica
51
2
DOI
出版状态已出版 - 2月 2025

关键词

  • Intelligent connected vehicles
  • autonomous driving
  • collaborative perception
  • secure communication
  • vehicle-road collaboration

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