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 …

This paper studies the decision making problem of autonomous vehicles in traffic. We model
the interaction between an autonomous vehicle and the environment as a stochastic Markov …

Autonomous vehicles promise to improve traffic safety while, at the same time, increase fuel
efficiency and reduce congestion. They represent the main trend in future intelligent …

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 proposes a learning-based behavior generation approach for automated
vehicles which is adapted sequentially. Instead of engineering behavioral policies for a …

In this work, the problem of path planning for an autonomous vehicle that moves on a
freeway is considered. The most common approaches that are used to address this problem …

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

This article presents a model-based motion planning and control system for autonomous
vehicles and its experimental validation. The system consists of four modules: 1) global …

This paper presents the design and first test on a simulator of a vehicle trajectory-planning
algorithm that adapts to traffic on a lane-structured infrastructure such as highways. The …

The development of automated vehicles brings new challenges to road safety. The behavior
of the automated vehicles should be carefully designed in order to interact with the …