Developing autonomous driving technologies necessitates addressing safety and cost
concerns. Both academic research and commercial applications of autonomous driving …

This study presents a comprehensive analysis of the impact of autonomous vehicles (AVs)
on urban landscapes, focusing on traffic management, urban planning, and environmental …

In this paper, we explore the potential of using a large language model (LLM) to understand
the driving environment in a human-like manner and analyze its ability to reason, interpret …

Existing learning-based autonomous driving (AD) systems face challenges in
comprehending high-level information, generalizing to rare events, and providing …

In recent years, significant achievements have been made in motion planning for intelligent
vehicles. However, as a typical unstructured environment, open-pit mining attracts limited …

A growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their
promise for enhanced safety, efficiency, and economic benefits. While previous surveys …

Autonomous vehicle control systems are unavoidably influenced by diverse noise
perturbations from the unpredictable external environment and internal system. In this …

This letter is part of the Intelligent Mining Development Forum and aims to summarize the
discussions of Mining 5.0 from Intelligent Vehicle 5.0 project by IEEE TIV, which represents a …

This study focuses on optimizing resource allocation problems in complex dynamic
environments, specifically vehicle dispatching in closed bipartite queuing networks. We …

Deep learning-based intelligent vehicle perception has been developing prominently in
recent years to provide a reliable source for motion planning and decision making in …