In a lane change (LC) scenario, the lane change vehicle interacts with surrounding vehicles.
The interactions not only affect their driving behaviors but also influence the traffic flow. This …

To address the challenge of developing effective control methods for governing the entire
driving process of both connected and automated vehicles (CAVs) and human-driven …

Learning and understanding car-following (CF) behaviors are crucial for microscopic traffic
simulation. Traditional CF models, though simple, often lack generalization capabilities …

The survival analysis of driving trajectories allows for holistic evaluations of car-related risks
caused by collisions or curvy roads. This analysis has advantages over common Time-To-X …

This letter proposes a novel spatiotemporal learning model via mixture importance Gaussian
filtering (MIGF). In the MIGF, we explore the causal mapping between the target's true …

Following a leading vehicle is a daily but challenging task because it requires adapting to
various traffic conditions and the leading vehicle's behaviors. However, the question 'Does …

Autonomous driving decision is a critical component of automatic driving system, which
informs and updates the unmanned vehicle of object movements. However, end‐to‐end …

This paper attempts to propose a discretionary lane‐changing decision‐making model
based on signalling game in the context of mixed traffic flow of autonomous and regular …

Despite the rapid advancement in the field of autonomous driving vehicles, developing a
safe and sensible decision-making system remains a challenging problem. The driving …

Connected and automated vehicles (CAVs) have attracted more and more attention recently.
The fast actuation time allows them having the potential to promote the efficiency and safety …