Autonomous 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 …

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 …

This paper presents a generic approach for tactical decision-making under uncertainty in the
context of driving. The complexity of this task mainly stems from the fact that rational decision …

Real-world autonomous driving in city traffic must cope with dynamic environments including
other agents with uncertain intentions. This poses a challenging decision-making problem …

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 represent a complex environment for autonomous vehicles with many
sources of uncertainty. The vehicle must plan in a stochastic environment with potentially …

Autonomous driving in urban areas requires avoiding other road users with only partial
observability of the environment. Observations are only partial because obstacles can …

Cooperative driving behavior is essential for driving in traffic, especially for ramp merging,
lane changing or navigating intersections. Autonomous vehicles should also manage these …

Chance–constrained optimization has been studied in the context of autonomous vehicles.
The work in [4] addresses the tactical planning problem for autonomous vehicles in …

State of the art emergency brake assistant systems solely based on sensor measurements
reduced the number of traffic accidents and casualties drastically in recent years. In order to …