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Physical enhanced residual learning(PERL)framework for vehicle trajectory prediction

Keke Long Zihao Sheng Haotian Shi Xiaopeng Li Sikai Chen Soyoung Ahn

交通研究通讯（英文）2025，Vol.5Issue(2)：36-47,12.

交通研究通讯（英文）2025，Vol.5Issue(2)：36-47,12.DOI:10.1016/j.commtr.2025.100166

Physical enhanced residual learning(PERL)framework for vehicle trajectory prediction

Keke Long ¹Zihao Sheng ¹Haotian Shi ¹Xiaopeng Li ¹Sikai Chen ¹Soyoung Ahn¹

作者信息

1. Department of Civil&Environmental Engineering,University of Wisconsin-Madison,Wisconsin,53706,USA
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摘要

关键词

Trajectory prediction/Residual/Car-following model/Neural network

Key words

Trajectory prediction/Residual/Car-following model/Neural network

引用本文复制引用

Keke Long,Zihao Sheng,Haotian Shi,Xiaopeng Li,Sikai Chen,Soyoung Ahn..Physical enhanced residual learning(PERL)framework for vehicle trajectory prediction[J].交通研究通讯（英文）,2025,5(2):36-47,12.

基金项目

This work was supported by the National Science Foundation Cyber-Physical Systems(CPS)program(No.2343167). （CPS）

交通研究通讯（英文）

ISSN：2772-4247

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