As autonomous vehicles begin venturing on the urban road, rational decision making is
essential for driving safety and efficiency. This paper presents a situation-aware decision …

Urban intersections are prone to delays and inefficiencies due to static precedence rules
and occlusions limiting the view on prioritized traffic. Existing approaches to improve traffic …

This paper presents an efficient hierarchical motion planning framework with a long
planning horizon for autonomous driving in structured environments. A 3D motion planning …

This paper presents an intention-aware online planning approach for autonomous driving
amid many pedestrians. To drive near pedestrians safely, efficiently, and smoothly …

Autonomy and connectivity are expected to enhance safety and improve fuel efficiency in
transportation systems. While connected vehicle-enabled technologies, such as coordinated …

When driving in urban environments, an autonomous vehicle must account for the
interaction with other traffic participants. It must reason about their future behavior, how its …

Motion planning is a process of constant negotiation with the rest of the traffic agents and is
highly conditioned by their movement prediction. Indeed, an incorrect prediction could cause …

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 …

Efficient driving in urban traffic scenarios requires foresight. The observation of other traffic
participants and the inference of their possible next actions depending on the own action is …

Motion planning plays an essential role in designing self-driving functions for connected and
autonomous vehicles. The methods need to provide a feasible trajectory for the vehicle to …