SA-LSTM: A Trajectory Prediction Model for Complex off-road Multi-agent Systems Considering Situation Awareness Based on Risk Field-Reference-Cited by-同舟云学术

SA-LSTM: A Trajectory Prediction Model for Complex off-road Multi-agent Systems Considering Situation Awareness Based on Risk Field

Published:2023 Issue: Volume: Page:1-12
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Wang Yuning¹^ORCID,Wang Jiahao¹,Jiang Junkai¹^ORCID,Xu Shaobing¹^ORCID,Wang Jianqiang¹^ORCID

Affiliation:

1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Science Fund for Creative Research Groups

Tsinghua University Initiative Scientific Research Program

Tsinghua University Toyota Joint Research Center for AI Technology of Automated Vehicle

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/4356907/10158029.pdf?arnumber=10158029

Reference33 articles.

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4. Environment-Attention Network for Vehicle Trajectory Prediction

5. A Novel Spatio-Temporal Model for City-Scale Traffic Speed Prediction

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