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Intelligent prediction of mobile vehicle trajectory based on space-time information

  • 作者:
    Guan, Dong (1)[1] Zhao, Hui(赵慧) (1)[1] Zhao, Long(赵龙) (1)[1] Zheng, Kan(郑侃) (1)[1]
  • 地址:

    [1]Intelligent Computing and Communication Lab, Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing; 100876, China

  • 语种:
    英文
  • 期刊:
    IEEE Vehicular Technology Conference ISSN:1550-2252 2019 年 ; April 28, 2019 - May 1, 2019
  • 收录:
  • 摘要:

    To improve both efficiency and safety of automatic driving in complex traffic scenarios, autonomous vehicles need to have the ability to predict the future trajectories of vehicles. The interaction among vehicles in real traffic scenarios makes the trajectory prediction of vehicles challenging. By utilizing the historical trajectory of the targeted vehicle and the surrounding environment information, this paper proposes a coupling LSTM model in order to effectively predict the future trajectories of vehicles. The proposed model predicts the observable motion intentions of vehicles, and builds grids for the targeted vehicles to extract the implied space and intention information of the neighboring vehicles. Experiment results verify the proposed model in contrast to other basic models in real traffic scenarios. © 2019 IEEE.

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  • 推荐引用方式
    GB/T 7714:
    Guan Dong (1),Zhao Hui (1),Zhao Long (1), et al. Intelligent prediction of mobile vehicle trajectory based on space-time information [J].IEEE Vehicular Technology Conference,2019.
  • APA:
    Guan Dong (1),Zhao Hui (1),Zhao Long (1),Zheng Kan (1).(2019).Intelligent prediction of mobile vehicle trajectory based on space-time information .IEEE Vehicular Technology Conference.
  • MLA:
    Guan Dong (1), et al. "Intelligent prediction of mobile vehicle trajectory based on space-time information" .IEEE Vehicular Technology Conference(2019).
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