This paper presents a practical trajectory planning framework towards fully autonomous
driving in urban environments. Firstly, based on the behavioral decision commands, a …

Autonomous vehicle technology provides the means to optimize motion planning beyond
human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip …

This paper presents a learning-based model predictive trajectory planning controller for
automated driving in unstructured, dynamic environments with obstacle avoidance. We first …

Numerical experiments for motion planning of road vehicles require numerous components:
vehicle dynamics, a road network, static obstacles, dynamic obstacles and their movement …

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

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

This paper investigates real-time on-road motion planning algorithms for autonomous
passenger vehicles (APV) in urban environments, and propose a computationally efficient …

This letter presents a hierarchical motion planner for generating smooth and feasible
trajectories for autonomous vehicles in unstructured environments with static and moving …

We present a motion planner for autonomous on-road driving, especially on highways. It
adapts the idea of a on-road state lattice. A focused search is performed in the previously …

In this article, we propose a new approach to drive a vehicle at high speed along a
predetermined path using Model Predictive Control. Instead of modeling precise vehicle …