Entering crossroads with blind corners. A safe strategy for autonomous vehicles

Abstract

Recent advances in the field of environment perception and cognition enable automated vehicles to safely drive in a growing variety of complex situations. However, in situations where required information cannot be observed directly and thus the consequences of the vehicle's actions cannot be estimated with high certainty, generating a safe behavior is still an unsolved problem. This paper tackles the scenario of a left turn maneuver in an urban environment with the presence of blind corners. We consider pedestrians and vehicles possibly hidden by parking cars, buildings or vegetation. In these cases, our approach allows to safely merge into traffic by using an environment representation based on tracked objects as well as an object-free sensor fusion including the calculation of unobservable regions in a digital map. A free-to-drive section of our desired path is obtained by long-term propagation of observed or possibly unobservable movement. The presented approach allows advancing into the road in a cautious manner, successively increasing the observable area.