Driving styles play a major role in the acceptance and use of autonomous vehicles. Yet,
existing motion planning techniques can often only incorporate simple driving styles that are …

The motion planners used in self-driving vehicles need to generate trajectories that are safe,
comfortable, and obey the traffic rules. This is usually achieved by two modules: behavior …

In this paper we propose a novel end-to-end learnable network that performs joint
perception, prediction and motion planning for self-driving vehicles and produces …

Behavior and motion planning play an important role in automated driving. Traditionally,
behavior planners instruct local motion planners with predefined behaviors. Due to the high …

With the integration of Autonomous Vehicles (AVs) into our transportation systems, their
harmonious coexistence with Human-driven Vehicles (HVs) in mixed traffic settings …

We present an approach for intention-aware motion planning in an autonomous driving
scenario, where a vehicle aims to traverse a road segment as quickly as possible, while …

Vehicle trajectory prediction is crucial for autonomous driving and advanced driver assistant
systems. While existing approaches may sample from a predicted distribution of vehicle …

We explore the complex design space of behaviour planning for autonomous driving.
Design choices that successfully address one aspect of behaviour planning can critically …

Autonomous vehicles face numerous challenges to ensure safe operation in unpredictable
and hazardous conditions. The autonomous driving environment is characterized by high …

Testing and verification is still an open issue on the way to fully automated driving.
Simulations can help to reduce the required testing efforts, however, classical simulators …