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This work presents a behavior planning algorithm for automated driving in urban environments with an uncertain and dynamic nature. The algorithm allows to consi

This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work ana

In motion planning for automated vehicles, a thorough uncertainty consideration is crucial to facilitate safe and convenient driving behavior. This work present

Autonomous driving has the potential to significantly improve safety. Although progress has been made in recent years to deploy automated driving technologies,

This thesis considers risk aware planning and probabilistic prediction for autonomous systems under uncertain environments. Motion planning under uncertainty lo