3 papers
cs.HC2026
Perceived risk evolution in automated driving inferred from large-scale discrete ratings
Xiaolin He, Zirui Li, Xinwei Wang +2
Perceived risk in automated driving is often measured as discrete scores that summarise riding experience but this obscures volatile peaks from sustained elevation. Here we treat d…
cs.RO2025
Dynamic Risk-Aware MPPI for Mobile Robots in Crowds via Efficient Monte Carlo Approximations
Elia Trevisan, Khaled A. Mustafa, Godert Notten +2
Deploying mobile robots safely among humans requires the motion planner to account for the uncertainty in the other agents' predicted trajectories. This remains challenging in trad…
cs.AI2025
H2C: Hippocampal Circuit-inspired Continual Learning for Lifelong Trajectory Prediction in Autonomous Driving
Yunlong Lin, Zirui Li, Guodong Du +5
Deep learning (DL) has shown state-of-the-art performance in trajectory prediction, which is critical to safe navigation in autonomous driving (AD). However, most DL-based methods…