A Survey on Deep-Learning Approaches for Vehicle Trajectory Prediction in Autonomous Driving-Reference-Cited by-同舟云学术

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A Survey on Deep-Learning Approaches for Vehicle Trajectory Prediction in Autonomous Driving

Published:2021-12-27 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)
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Author:

Liu Jianbang¹,Mao Xinyu¹,Fang Yuqi²,Zhu Delong¹,Meng Max Q.-H.³

Affiliation:

1. The Chinese University of Hong Kong,Department of Electronic Engineering,Hong Kong

2. The Chinese University of Hong Kong,Department of Biomedical Engineering,Hong Kong

3. The Southern University of Science and Technology,Department of Electronic and Electrical Engineering,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9739207/9739208/09739407.pdf?arnumber=9739407

Cited by 39 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A time-varying shockwave speed model for reconstructing trajectories on freeways using Lagrangian and Eulerian observations;Expert Systems with Applications;2024-11

2. Behavioral Intention Prediction in Driving Scenes: A Survey;IEEE Transactions on Intelligent Transportation Systems;2024-08

3. Multi-Class Trajectory Prediction in Urban Traffic Using the View-of-Delft Prediction Dataset;IEEE Robotics and Automation Letters;2024-05

4. Enhancing Driving Behavior Analysis in Autonomous Systems: A Reservoir Computing and Temporal-Aware Machine Learning Approach;2024 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST);2024-05-01

5. On the Way to Reliable Trajectory Prediction in Urban Traffic;Advances in Transdisciplinary Engineering;2024-02-19

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