This paper presents an efficient hierarchical motion planning framework with a long
planning horizon for autonomous driving in structured environments. A 3D motion planning …

In this work, we present a decision-making system for automated vehicles driving in highway
environments. The task is modeled as a Partially Observable Markov Decision Process, in …

For automated driving vehicles, trajectory planning is responsible for obtaining feasible
trajectories with velocity profiles according to driving environments. From the perspective of …

Trajectory planning for autonomous vehicles (AVs) by considering conflicting moving objects
(CMOs) is a challenging problem to AV operations. This paper investigates an AV trajectory …

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

This study presents a general optimal trajectory planning (GOTP) framework for autonomous
vehicles (AVs) that can effectively avoid obstacles and guide AVs to complete driving tasks …

In the field of path planning for autonomous vehicle, the existing studies separately consider
the path planning and path tracking problem. To fill in this research gap, this study proposes …

Motion planning is an essential component in intelligent vehicle study. Rapidly-exploring
Random Tree (RRT) and its variants are popular algorithms that have been successfully …

Trajectory planning is one of the fundamental and core components of autonomous ground
vehicles (AGVs). A sequence of movement states should be planned satisfying both …

Motion planning in an effective and safe manner is a critical yet challenging task for
autonomous driving. Learning-based framework as a new fashion in simulation and …