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

Motion planners for autonomous driving improve traffic safety through collision-free motion
generation along the path. However, conventional motion planners render passengers …

This paper proposes a novel motion planning and tracking framework based on improved
artificial potential fields (APFs) and a lane change strategy to enhance the performance of …

The predictive motion prediction of surrounding vehicles is an essential precondition for
precise collision risk assessment and path planning. In this paper, we propose a motion …

Safety is the cornerstone of autonomous driving vehicles. For autonomously controlled
vehicles driving safely in complex and dynamic traffic scenarios, it is essential to precisely …

Motion planning for autonomous vehicles becomes more challenging when both driver
comfort and collision risk are considered. To overcome this challenge, a human-like motion …

This paper describes a lane-changing motion planning model for intelligent vehicles under
constraints of collision avoidance in dynamical driving environments. The key innovation is …

In this paper, a hierarchical motion planning framework is proposed to solve complex
navigation problem in realistic dynamic traffic environments. Firstly, according to the …

This paper proposes a motion planner for intelligent vehicles in real time. The motion
planner can adaptively sample a number of states according to the initial state of the …

This paper presents a novel local motion planning framework in a hierarchical manner for
autonomous vehicles to follow a trajectory and agilely avoid obstacles. In the upper layer, a …