Paired Safety Rule Structure for Human-Machine Cooperation with Feature Update and Evolution

Autonomous control systems are used in an open environment where humans exist. Therefore, a safety design needs to be created corresponding to evolutions and changes in the behavior of humans and machines in accordance with an open changing environment. In this study, we propose a structure and derivation method of safety rules based on a pairing structure for the cooperation of humans and machines, which can facilitate feature updates and evolutions in the behavior of humans and machines. For a feature update, feature trees utilizing methods of software product line correspond to the evolution of behavior of a human and a machine by using a pairing safety rule structure. The results of a case study simulating autonomous driving systems and pedestrians in a city showed that the proposed safety rule structure can facilitate rule switching when features change. The results also showed that human-machine cooperation efficiency could be improved and safety maintained by operation following the change of safety rules in accordance with the proposed structure when the behavior of pedestrians and autonomous vehicles evolved.