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

Recently significant progress has been made in vehicle prediction and planning algorithms
for autonomous driving. However, it remains quite challenging for an autonomous vehicle to …

Interactive behavior modeling of multiple agents is an essential challenge in simulation,
especially in scenarios when agents need to avoid collisions and cooperate at the same …

Effective interaction modeling and behavior prediction of dynamic agents play a significant
role in interactive motion planning for autonomous robots. Although existing methods have …

Local planning for a differential wheeled robot is designed to generate kinodynamic feasible
actions that guide the robot to a goal position along the navigation path while avoiding …

The recent development of cloud computing and edge computing shows great promise for
the Connected and Automated Vehicle (CAV), by enabling CAVs to offload their massive on …

Trajectory planning is crucial for the safe driving of autonomous vehicles in highway traffic
flow. Currently, some advanced trajectory planning methods utilize spatio-temporal voxels to …

Abstract Machine learning-based techniques have shown great promises in perception,
prediction, planning, and general decision-making for improving task performance of …