Multi-agent collaborative perception depends on sharing sensory information to improve
perception accuracy and robustness, as well as to extend coverage. However, most …

Perceiving the surrounding environment is critical to enable cooperative driving automation,
which is regarded as a transformative solution to improving our transportation system …

In this paper, we tackle the problem of selecting connected autonomous vehicles (CAVs)
with the most valuable point cloud data for edge-coordinated on-road perception. Through …

The detection of occluded objects and small objects (including distant objects) by
autonomous vehicles is still at a low level. Even multi-sensor fusion cannot solve this …

With the rapid development of communication technology, cooperative perception between
vehicles and infrastructure improves the perception performance in complex scenarios …

3D object detection is a significant aspect of the perception module in autonomous driving;
however, with current technology, data sharing between vehicles and cloud servers for …

Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with that of other …

The objective of the collaborative vehicle-to-everything perception task is to enhance the
individual vehicle's perception capability through message communication among …

Autonomous vehicles and human drivers are prone to line-of-sight limitations. Road-side
mounted 3D sensors like LiDARs can augment a vehicle's on-board perception. However …

Recent research has demonstrated that the Vehicle-to-Everything (V2X) communication
techniques can fundamentally improve the perception system for autonomous driving by …