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 …

The operational space of an autonomous vehicle (AV) can be diverse and vary significantly.
Due to this, formulating a rule based decision maker for selecting driving maneuvers may …

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 …

Autonomous driving decision-making is a challenging task due to the inherent complexity
and uncertainty in traffic. For example, adjacent vehicles may change their lane or overtake …

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 …

Autonomous driving vehicles can reduce congestion and improve safety while increasing
traffic efficiency. To reflect the quality of driving more comprehensively, the driving safety …

In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …

This paper describes a game theoretical model of traffic where multiple drivers interact with
each other. The model is developed using hierarchical reasoning, a game theoretical model …

There are still some problems need to be solved though there are a lot of achievements in
the field of automatic driving. One of those problems is the difficulty of designing a decision …