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Jiachao Liu

3 accepted papers

2026

Decoupling Scene Perception and Ego Status: A Multi-Context Fusion Approach for Enhanced Generalization in End-to-End Autonomous Driving

AAAI 2026technical

Modular design of planning-oriented autonomous driving has markedly advanced end-to-end systems. However, existing architectures remain constrained by an over-reliance on ego status, hindering generalization and robust scene understanding. We identify the root cause as an inherent design within thes

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2025

Certificating Safety of Imitation Learning for Autonomous Driving With Learnable Weighted Control Barrier Functions

RA-L 2025

Imitation learning is increasingly utilized to improve driving performance using real-world data, yet ensuring the safety of its outputs remains a fundamental challenge. While differentiable optimization-based methods are widely employed to enhance safety of imitation planner, their joint training o

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2025

TrajFlow: Multi-modal Motion Prediction via Flow Matching

IROS 2025

Efficient and accurate motion prediction is crucial for ensuring safety and informed decision-making in autonomous driving, particularly under dynamic real-world conditions that necessitate multi-modal forecasts. We introduce TrajFlow, a novel flow matching-based motion prediction framework that add

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