My research focuses on the interplay between performance and social considerations in
human-AI joint decision-making. Performance considerations can include optimizing for …

Over the last few hundred years, best practice in some fields of human action—eg, the
treatment of heart disease, the transportation of persons, goods, and messages, and the …

Driver behavior recognition may be provided using a processor and a memory. The memory
may receive an image sequence and a corresponding vehicle data signal sequence. The …

Abstract Systems and methods for driver behavior recognition is provided. In one
embodiment a computer implemented method includes receiving image data associated …

Automated driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …

Cooperation at unsignalized intersections in mixed traffic environments, where Connected
and Autonomous Vehicles (CAVs) and Manually Driving Vehicles (MVs) coexist, holds …

The ability to interact with other road participants is essential for autonomous vehicles in
order to navigate under highly complex or critical driving scenarios. It is an extremely …

The objective of this dissertation is to develop deep reinforcement learning for multiple
autonomous vehicles under mixed traffic conditions in non-signalized junctions. To achieve …

Building self-driving vehicles is exciting and promising. It is going to transform the way we
live and provide safety, efficiency, and mobility for everyone. In this thesis, I present a …

The deployment of future self-driving vehicles is expected to have a major socioeconomic
impact due to their promise to be both safer and more traffic-efficient than human-driven …