In complex driving scenarios, automated vehicles should behave reasonably and respond
adaptively with high computational efficiency. In this paper, a computational efficient motion …

In this article, we propose an optimization-based integrated behavior planning and motion
control scheme, which is an interpretable and adaptable urban autonomous driving solution …

Motion planning for merging scenarios accounting for measurement and prediction
uncertainties is a major challenge on the way to autonomous driving. Classical methods …

In this paper, we develop a unified trajectory planning and tracking control framework for
autonomous overtaking in structured roads. The framework consists of two individual MPC to …

Motion planning and control of connected and autonomous vehicles (CAVs) for improving
traffic efficiency and safety in intersections still meets many challenges due to its dynamic …

Trajectory planning in dynamic environments can be decomposed into two sub-problems: 1)
planning a path to avoid static obstacles, 2) then planning a speed profile to avoid dynamic …

A novel driving-behavior-oriented method is proposed in this paper for improving trajectory
planning performance of autonomous vehicle driving on urban structural road. Differ from …

Autonomous ground vehicles (AGVs) are receiving increasing attention, and the motion
planning and control problem for these vehicles has become a hot research topic. In real …

This paper presents a trajectory planning framework to deal with the highly dynamic
environments for on-road driving. The trajectory optimization problem with parameterized …

Autonomous vehicles need to perform social accepted behaviors in complex urban
scenarios including human‐driven vehicles with uncertain intentions. This leads to many …