Planning and decision-making technology at intersections is a comprehensive research
problem in intelligent transportation systems due to the uncertainties caused by a variety of …

The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …

The intersection is a critical traffic problem from the perspective of safety and traffic
efficiency. As wireless communication technology advances, vehicle infrastructure …

This paper presents a novel interactive motion planning approach for left-turning of
autonomous vehicles at uncontrolled intersections. A typical left-turning scenario that …

Reinforcement learning-based techniques, empowered by deep-structured neural nets,
have demonstrated superiority over rule-based methods in terms of making high-level …

Efficient public transportation has always intrigued extensive research. Aiming to improve
the commuting efficiency and fuel economy of the autonomous hybrid electric buses in the …

Turning behaviour is one of the most challenging driving manoeuvres that take place at
intersections. Autonomous vehicles (AVs) are often overly conservative in these scenarios …

Manually planning a crane's lifting path is complicated and laborious since it typically
depends on the planner's experience. We examined dynamic three-dimensional lift …

Modeling and control of dynamic systems that experience abrupt changes are challenging
and fundamental tasks in applications of different areas of engineering. Among these …

Controlling an autonomous vehicle's unprotected left turn at an intersection is a challenging
task. Traditional rule‐based autonomous driving decision and control algorithms struggle to …