SafeShift: Safety-Informed Distribution Shifts for Robust Trajectory Prediction in Autonomous Driving
Author:
Affiliation:
1. Carnegie Mellon University,School of Computer Science
2. Hanyang University,Department of Automotive Engineering
3. Bosch Center for Artificial Intelligence
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10587320/10588370/10588828.pdf?arnumber=10588828
Reference49 articles.
1. Maturity in Automated Driving on Public Roads: A Review of the Six-Year Autonomous Vehicle Tester Program
2. Learn-to-race challenge 2022: Benchmarking safe learning and cross-domain generalisation in autonomous racing;Francis,2022
3. Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives
4. Safety-Compliant Generative Adversarial Networks for Human Trajectory Forecasting
5. Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset
Cited by 1 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. Robustness in trajectory prediction for autonomous vehicles: a survey;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
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