No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

Nowadays, with the advancement of technology, world is trending toward high mobility and
dynamics. In this context, intersection management (IM) as one of the most crucial elements …

Merging is, in general, a challenging task for both human drivers and autonomous vehicles,
especially in dense traffic, because the merging vehicle typically needs to interact with other …

We present a new method for multi-agent planning involving human drivers and
autonomous vehicles (AVs) in unsignaled intersections, roundabouts, and during merging …

In this paper, a three-level decision-making framework is developed to generate safe and
effective decisions for autonomous vehicles (AVs). A key component in this decision …

We propose GAMEOPT: a novel hybrid approach to cooperative intersection control for
dynamic, multi-lane, unsignalized intersections. Safely navigating these complex and …

Decision-making for autonomous driving is challenging, considering the complex
interactions among multiple traffic agents (eg, autonomous vehicles (AVs), human drivers …

This dissertation addressed many key problems in autonomous driving towards handling
dense, heterogeneous, and unstructured traffic environments. Autonomous vehicles (AV) at …

Risk assessment of driving scenarios is essential for both the research and development
(R&D) and the verification and validation (V&V) of autonomous vehicles (AVs), which is …

As an emerging technology, Connected Autonomous Vehicles (CAVs) are believed to have
the ability to move through intersections in a faster and safer manner, through effective …