The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …

The use of neural networks and reinforcement learning has become increasingly popular in
autonomous vehicle control. However, the opaqueness of the resulting control policies …

Autonomous agents that drive on roads shared with human drivers must reason about the
nuanced interactions among traffic participants. This poses a highly challenging decision …

Devising planning algorithms for autonomous driving is non-trivial due to the presence of
complex and uncertain interaction dynamics between road users. In this paper, we introduce …

Autonomous driving is a complex task which requires advanced decision making and
control algorithms. Understanding the rationale behind the autonomous vehicles' decision is …

Vehicle autonomy has the potential to bring many social benefits, such as improved traffic
safety and increased productivity. Modern autonomous vehicles are able to sense their local …