Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

Advances in Single-vehicle intelligence of automated driving has encountered great
challenges because of limited capabilities in perception and interaction with complex traffic …

Vehicle-to-everything (V2X) autonomous driving opens up a promising direction for
developing a new generation of intelligent transportation systems. Collaborative perception …

Accurate perception is essential for advancing autonomous driving and addressing safety
challenges in modern transportation systems. Despite significant advancements in computer …

Sharing information between connected and autonomous vehicles (CAVs) fundamentally
improves the performance of collaborative object detection for self-driving. However, CAVs …

LiDAR is an indispensable sensor for autonomous driving that can provide precise 3D
information about the environment. Among various types of LiDARs, mechanical LiDARs are …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

Object detection and multiple object tracking (MOT) are essential components of self-driving
systems. Accurate detection and uncertainty quantification are both critical for onboard …

Domain shifts such as sensor type changes and geographical situation variations are
prevalent in Autonomous Driving (AD), which poses a challenge since AD model relying on …

Multi-agent cooperative perception is an increasingly popular topic in the field of
autonomous driving, where roadside LiDARs play an essential role. However, how to …