柏海舰  (副教授)

Xingyu CHEN , Haijian BAI, Heng DING, Jianshe GAO, Wenjuan HUANG. A Safety Control Method of Car-Following Trajectory Planning Based on LSTM

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DOI码：10.7307/ptt.v35i3.118

发表刊物：Traffic Transportation

关键字：car-following model; LSTM; Gipps model; safety control; potential collision point

摘要：This paper focuses on the potential safety hazards of collision in car-following behaviour generated by deep learning models. Based on an intelligent LSTM model, combined with a Gipps model of safe collision avoidance, a new, Gipps-LSTM model is constructed, which can not only learn the intelligent behaviour of people but also ensure the safety of vehicles. The idea of the Gipps-LSTM model combination is as follows: the concept of a potential collision point (PCP) is introduced, and the LSTM model or Gipps model is controlled and started through a risk judgment algorithm. Dataset 1 and dataset 2 are used to train and simulate the LSTM model and Gipps-LSTM model. The simulation results show that the GippsLSTM can solve the problem of partial trajectory collision in the LSTM model simulation. Moreover, the risk level of all trajectories is lower than that of the LSTM model. The safety and stability of the model are verified by multi-vehicle loop simulation and multi-vehicle linear simulation. Compared with the LSTM model, the safety of the Gipps-LSTM model is improved by 42.02%, and the convergence time is reduced by 25s.

论文类型：期刊论文

学科门类：工学

文献类型：J

是否译文：否

发表时间：2023-03-30