Improving Interaction-Based Vehicle Trajectory Prediction via Handling Sensing Failures-Reference-Cited by-同舟云学术

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Improving Interaction-Based Vehicle Trajectory Prediction via Handling Sensing Failures

Published:2024-07-15 Issue:14 Volume:24 Page:22907-22915
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Li Yongwei¹,Jiang Yongzhi¹,Xiong Zhongxia¹,Wu Xinkai²^ORCID

Affiliation:

1. School of Transportation Science and Engineering, Beihang University, Beijing, China

2. Key Laboratory of Intelligent Transportation Technology and System, School of Transportation Science and Engineering, Ministry of Education, Beihang University, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Natural Science Foundation for Young Scientists of Shanxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7361/10599846/10546983.pdf?arnumber=10546983

Reference36 articles.

1. BVTracker: Multivehicle Tracking Based on Behavioral-Visual Features

2. Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data

3. GRIP++: Enhanced graph-based interaction-aware trajectory prediction for autonomous driving;Li;arXiv:1907.07792,2019

4. Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving

5. Graph Neural Networks for Modelling Traffic Participant Interaction

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