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Jingchu Liu

3 accepted papers

2026

Drive in Corridors: Enhancing the Safety of End-To-End Autonomous Driving Via Corridor Learning and Planning

ICRA 2026poster

Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a scalable manner. However, existing approaches often face safety risks due to the lack of explicit behavior constraints.…

2025

Drive in Corridors: Enhancing the Safety of End-to-End Autonomous Driving via Corridor Learning and Planning

RA-L 2025

Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a scalable manner. However, existing approaches often face safety risks due to the lack of explicit behavior constraints.

Cited by 3SourcecodeScholar
2023

Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning

IROS 2023poster

Learning-based approaches have achieved remarkable performance in the domain of autonomous driving. Leveraging the impressive ability of neural networks and large amounts of human driving data, complex patterns and rules of driving behavior can be encoded as a model to benefit the autonomous driving…

Cited by 5SourceScholar