Automated driving: The role of forecasts and uncertainty—A control perspective. (July 2015) - Carvalho, Ashwin; Lefévre, Stéphanie; Schildbach, Georg; Kong, Jason; Borrelli, Francesco
Abstract: 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 overview of our findings and discusses relevant aspects of our recent results.