The main topic of this thesis is tactical decision-making for autonomous driving. An
autonomous vehicle must be able to handle a diverse set of environments and traffic …

The main topic of this thesis is tactical decision-making for autonomous driving. An
autonomous vehicle must be able to handle a diverse set of environments and traffic …

The tactical decision-making task of an autonomous vehicle is challenging, due to the
diversity of the environments the vehicle operates in, the uncertainty in the sensor …

Abstract The application of Reinforcement Learning to Autonomous Driving is a relevant
topic in the Machine Learning community. Reinforcement Learning techniques generate …

In autonomous driving, different Reinforcement Learning (RL) methods have been
implemented to deal with different challenges. One of its advantages is the capability to deal …

As automated driving development progresses forward, novel methods are required to
handle the vastness of possible road situations and to face end user's high demands. Trying …

Autonomous driving is a research field that has received attention in recent years, with
increasing applications of reinforcement learning (RL) algorithms. It is impractical to train an …

A world initiative was set in motion for decreasing the amount of traffic accidents.
Autonomous driving is a field which contributes to the initiative. Following report examines …

Reinforcement learning (RL) can be used to create a tactical decision-making agent for
autonomous driving. However, previous approaches only output decisions and do not …

In order to solve the traffic problem caused by the popularization of cars, autonomous driving
technology has developed rapidly. Reinforcement learning is an effective way to solve the …