Review of pedestrian trajectory prediction methods
DOI:
https://doi.org/10.54097/fcis.v1i3.2135Keywords:
Pedestrian trajectory prediction, Automatic driving, Deep learning, Prediction method, Neural networkAbstract
Urban driverless vehicles will inevitably interact with pedestrians in the process of driving. In order to avoid path conflict with pedestrians, the research on pedestrian trajectory prediction is of great significance. This paper mainly summarizes the technical classification and research status of pedestrian trajectory prediction at this stage in detail. According to the different modeling methods, the existing trajectory prediction methods are divided into shallow learning-based trajectory prediction methods and depth learning based trajectory prediction methods. The advantages and disadvantages of the depth learning based trajectory prediction methods are compared, and the current mainstream pedestrian trajectory prediction public dataset is summarized, and the performance of the mainstream pedestrian trajectory prediction methods is compared in the dataset. Finally, the challenges and development trend of pedestrian trajectory prediction at this stage are prospected.
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