Autonomous driving technology, a catalyst for revolutionizing transportation and urban
mobility, has the tend to transition from rule-based systems to data-driven strategies …

Urban environments, characterized by their complex, multi-layered networks encompassing
physical, social, economic, and environmental dimensions, face significant challenges in the …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

Traffic signal control is crucial for optimizing the efficiency of road network by regulating
traffic light phases. Existing research predominantly focuses on heuristic or reinforcement …

Autonomous Driving (AD) faces crucial hurdles for commercial launch, notably in the form of
diminished public trust and safety concerns from long-tail unforeseen driving scenarios. This …

Traffic accidents, being a significant contributor to both human casualties and property
damage, have long been a focal point of research for many scholars in the field of traffic …

This study presents a novel approach to enhance Large Language Models (LLMs) like
Alpaca by dynamically integrating real-time information. This method addresses the issue of …

In the case of this research paper, the concept of “AI traffic management” can be noted in a
reliable and significant way. Nowadays, the application of AI is getting higher in the case of …