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 …

Autonomous vehicles require safe motion planning in uncertain environments, which are
largely caused by surrounding vehicles. In this paper, a driving environment uncertainty …

This paper presents a novel motion planning and tracking framework for automated vehicles
based on artificial potential field (APF) elaborated resistance approach. Motion planning is …

Navigation algorithms for autonomous vehicles have become the subject of increasing
interest, but most of them heavily rely on expensive high-precision positioning equipment …

A path planning and tracking framework is presented to maintain a collision-free path for
autonomous vehicles. For path-planning approaches, a 3-D virtual dangerous potential field …

Path planning for autonomous vehicles in dynamic environments is an important but
challenging problem, due to the constraints of vehicle dynamics and existence of …

This paper focuses on the real-time trajectory planning problem for autonomous vehicles
driving in realistic urban environments. To solve the complex navigation problem, we adopt …

Accurate trajectory prediction of surrounding vehicles enables lower risk path planning in
advance for autonomous vehicles, thus promising the safety of automated driving. A low-risk …

This paper introduces an efficient motion planning method for on-road driving of the
autonomous vehicles, which is based on the rapidly exploring random tree (RRT) algorithm …

Trajectory planning is of vital importance to decision-making for autonomous vehicles.
Currently, there are three popular classes of cost-based trajectory planning methods …