A Markov Decision Process approach to human-autonomous driving control logic

Abstract

In the road toward autonomous vehicles, we will have to overcome the challenge that a car will not directly be able to drive fully autonomous in all situations a vehicle will come across. One way to tackle this problem is provided by the MEDIATOR project, which aims at creating a solution handling the continuous mediation between autonomous and human-controlled driving. This thesis focuses on one element of the MEDIATOR project referred to as the decision logic. It controls the level of automation the vehicle operates in, depending on the specific condition it encounters. One of the contributions of this thesis is the formalization of the decision logic as a mathematical problem; that is, it is modeled as a Markov decision process. This thesis also gives an implementation of such a model and tests it in a simulated environment for which a tailored simulator was constructed. The feasibility of the proposed Markov decision process approach was tested by comparing it to a simpler heuristic approach. Our results show that the new model is very promising both in terms of planning for the decision logic and meeting of the requirements of the original problem.