In recent years, great efforts have been devoted to deep imitation learning for autonomous
driving control, where raw sensory inputs are directly mapped to control actions. However …

The proper functioning of connected and autonomous vehicles (CAVs) is crucial for the
safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully …

Lane changes are complex driving behaviors and frequently involve safety–critical
situations. This study aims to develop a lane-change-related evasive behavior model, which …

Pedestrian distraction may provoke severe difficulties in automated vehicle (AV) control,
which may significantly affect the safety performance of AVs, especially at unsignalized mid …

While affordance detection and Human-Object interaction (HOI) detection tasks are related,
the theoretical foundation of affordances makes it clear that the two are distinct. In particular …

Reliable pedestrian crash avoidance mitigation (PCAM) systems are crucial components of
safe autonomous vehicles (AVs). The nature of the vehicle-pedestrian interaction where …

In this paper, a novel approach is presented for modeling the interaction dynamics between
an ego car and a bicycle in a traffic scenario using a hybrid reinforcement learning …

This paper studies an optimization problem of antenna placement for multiple heading
angles of the target in a distributed multiple-input multiple-output (MIMO) radar system. An …

Proper functioning of connected and automated vehicles (CAVs) is crucial for the safety and
efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous …

The deployment of autonomous driving technology is hindered by “corner cases”: unusual
nuanced conditions that the self-driving software cannot understand and act fully. We argue …