弹道
深度学习
计算机科学
突出
人工智能
机器学习
物理
天文
作者
Huilin Yin,Yurong Wen,Jiaxiang Li
标识
DOI:10.1109/nnice58320.2023.10105706
摘要
Trajectory prediction is very important for autonomous driving vehicles. Deep-learning approaches can capture the interaction information. Therefore more and more researchers are using deep-learning models to accomplish vehicle trajectory prediction. This paper provides a detailed and comparative description of the methods for vehicle trajectory prediction based on deep-learning models. We start by modelling trajectory predictions for vehicles. Several common deep-learning models used in vehicle trajectory prediction are then highlighted. Next, we compare the structural features, salient advantages and applicable scenarios of commonly used deep-learning models. Future directions for vehicle trajectory prediction are discussed at the end.
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