With extensive pretrained knowledge and high-level general capabilities, large language
models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in …

Verification and validation of autonomous driving (AD) systems and components is of
increasing importance, as such technology increases in real-world prevalence. Safety …

The increasing level of autonomy of robots poses challenges of trust and social acceptance,
especially in human-robot interaction scenarios. This requires an interpretable …

Obstacle avoidance under constrained visual perception presents a significant challenge,
requiring rapid detection and decision-making within partially observable environments …

Human-machine shared control in critical collision scenarios aims to aid drivers' accident
avoidance through intervening only when necessary. Existing methods count on replanning …

This paper presents a first-of-its-kind evaluation of integrating Large Language Models
(LLMs) within a Human-In-The-Loop (HITL) framework for risk analysis in machinery …

As an emerging mode of transportation, autonomous vehicles are increasingly attracting
widespread attention. To address the issues of the traditional reinforcement learning …