Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …

The article presents a review of recent literature on the performance metrics of Automated
Driving Systems (ADS). More specifically, performance indicators of environment perception …

To understand the formation of lighting-related traffic bottlenecks along the long freeway
tunnels in the daytime, this study develops an intelligent driver model incorporating the …

Abstract Autonomous Vehicles (AVs) have made remarkable developments and are
anticipated to replace human drivers. In transitioning from human-driven vehicles to fully …

Urban traffic is developing rapidly in the direction of intelligence and networking. In order to
further enhance the role of connected vehicles in improving the traffic characteristic of the …

The implementation of autonomous driving is inseparable from developing intelligent driving
decision-making models, which are facing high scene complexity, poor decision-making …

Forecasting vehicles' future motion is crucial for real-world applications such as the
navigation of autonomous vehicles and feasibility of safety systems based on the Internet of …

Merging areas serve as the potential bottlenecks for continuous traffic flow on freeways.
Traffic incidents in freeway merging areas are closely related to decision-making errors of …

Understanding human drivers' intentions and predicting their future motions are significant to
connected and autonomous vehicles and traffic safety and surveillance systems. Predicting …

Lane changes require dynamic decision-making and rapid behavior planning, which are
challenging for traffic modeling. We propose a two-dimensional following lane-changing …