Chinese Journal of Intelligent Science and Technology ›› 2021, Vol. 3 ›› Issue (4): 399-411.doi: 10.11959/j.issn.2096-6652.202140

• Surveys and Prospectives • Previous Articles     Next Articles

Review of pedestrian trajectory prediction methods

Linhui LI1,2, Bin ZHOU1, Weiwei REN1, Jing LIAN1,2   

  1. 1 School of Automotive Engineering, Dalian University of Technology, Dalian 116024, China
    2 State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian 116024, China
  • Revised:2020-08-28 Online:2021-12-15 Published:2021-12-01
  • Supported by:
    The National Natural Science Foundation of China(51775082);The National Natural Science Foundation of China(61976039);The China Fundamental Research Funds for the Central Universities(DUT19LAB36);The China Fundamental Research Funds for the Central Universities(DUT20GJ207);Science and Technology Innovation Fund of Dalian(2018J12GX061)


With the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction were mainly reviewed.According to the different modeling methods, the existing methods were divided into shallow learning and deep learning based trajectory prediction algorithms, the advantages and disadvantages of representative algorithms in each type of method were analyzed and introduced.Then, the current mainstream public data sets were summarized, and the performance of mainstream trajectory prediction methods based on the data sets was compared.Finally, the challenges faced by the trajectory prediction technology and the development direction of future work were prospected.

Key words: trajectory prediction, deep learning, sequence decision

CLC Number: 

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