Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …

With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

We present a simple yet effective approach that can transform the OpenAI GPT-3.5 model
into a reliable motion planner for autonomous vehicles. Motion planning is a core challenge …

Agent-based modeling and simulation has evolved as a powerful tool for modeling complex
systems, offering insights into emergent behaviors and interactions among diverse agents …

Abstract Recent progress in Large Multimodal Models (LMM) has opened up great
possibilities for various applications in the field of human-machine interactions. However …

Autonomous driving (AD) has made significant strides in recent years. However existing
frameworks struggle to interpret and execute spontaneous user instructions such as" …

Human-level driving is an ultimate goal of autonomous driving. Conventional approaches
formulate autonomous driving as a perception-prediction-planning framework, yet their …

One of the most challenging problems in human-machine co-work is the gap between
human intention and the machine's understanding and execution. Large Language Models …

The pursuit of autonomous driving technology hinges on the sophisticated integration of
perception, decision-making, and control systems. Traditional approaches, both data-driven …

The applications of Vision-Language Models (VLMs) in the fields of Autonomous Driving
(AD) and Intelligent Transportation Systems (ITS) have attracted widespread attention due to …