This paper addresses the trajectory planning problem for autonomous vehicles in traffic. We
build a stochastic Markov decision process (MDP) model to represent the behaviors of the …

Research in the field of automated driving has created promising results in the last years.
Some research groups have shown perception systems which are able to capture even …

Aggressive vehicle maneuvers such as those performed by professional racing drivers
achieve high agility motion at the edge of handling limits. These aggressive maneuvers can …

Currently autonomous or self-driving vehicles are at the heart of academia and industry
research because of its multi-faceted advantages that includes improved safety, reduced …

This paper outlines a predictive maneuver-planning method for autonomous vehicle
navigating public highway traffic. The method integrates discrete maneuvering decisions, ie …

Discover the latest research in path planning and robust path tracking control In
Autonomous Road Vehicle Path Planning and Tracking Control, a team of distinguished …

Motion planning algorithms, an essential part of the autonomous driving system, have been
extensively studied. However, in large-scale complex scenarios, how to develop an optimal …

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 …

We present the motion planning framework for an autonomous vehicle navigating through
urban environments. Such environments present a number of motion planning challenges …

Efficient trajectory planning for intelligent vehicles in dynamic environments is a non-trivial
task due to the diversity and complexity of driving scenarios. It requires the planner to be …