A surveillance and safety system based on performance criteria and functional degradation for an autonomous vehicle

Autonomous driving in urban environments is potentially dangerous since a malfunction of vehicle guidance systems can lead to severe situations for passengers inside the autonomous vehicle and other road users. Therefore both, monitoring the current system operation state by a surveillance system, which is able to detect failures of software and hardware modules, and a safety system, which reacts on these failures immediately, is necessary. In this paper an approach based on performance criteria and functional degradation is proposed, which is used in the autonomous vehicle Leonie developed within the Stadtpilot project. The surveillance part of the system collects data from sensors, software modules, hardware, and the vehicle to combine this data with heuristics to performance criteria. Based on these criteria degradation actions are executed to keep the operation of Leonie in a safe state. The safety system can influence driving maneuvers like lane changes and turning maneuvers, modify driving parameters like maximum speed and safe time headway and even force driving maneuvers like emergency stops and controlled stops at the side of the road. Currently, the safety driver onboard of Leonie is the fallback solution in case of a system malfunction. Using the proposed safety system should reduce the number of situations where the safety driver has to take control over the vehicle though.