This study presents an approach to decision making for autonomous driving based on
reinforcement learning and shared autonomy. Game theory is used to model the interaction …

In order to establish general principles in the topic of motion planning for fully-automated
driving, an intuitive problem statement in the form of an Euler-Lagrange Model is derived …

A vehicle navigating in an urban environment must obey traffic rules by properly setting its
speed, such as staying below the road speed limit and avoiding collision with other vehicles …

As members of a network share more information with Each other and network providers,
sensitive data leakage raises privacy concerns. To address this need for a class of …

During the past few decades automakers have consistently introduced technological
innovations aimed to make road vehicles safer. The level of sophistication of these …

Self-adaptive software systems make decisions at run time that seek to change their
behavior in response to faults, changing environments and attacks. Therefore, having an …

Using simulation models to conduct safety assessments can have several advantages as it
enables the evaluation of the safety of various design and traffic management options before …

To avoid accidents, warning driver assistance systems require an on-line estimation of the
current risk of collision. For that, a new method is proposed that-in principle-is able to deal …

This study presents solutions to decision making for autonomous driving based on
reinforcement learning and shared control between human driver and machine. The main …

Autonomous vehicles with mature technology can improve the safety and accessibility of
vehicle transportation and reshape their mobility based on improved operating efficiency …