Driving requires forecasts. Forecasted movements of objects in the driving scene are
uncertain. Inevitably, decision and control algorithms for autonomous driving need to cope
with such uncertain forecasts. In assisted driving, the uncertainty in the human/vehicle
interaction further increases the complexity of the control design task. Our research over the
past ten years has focused on control design methods which systematically handle
uncertain forecasts for autonomous and semi-autonomous vehicles. This paper presents an …