Operational safety hazard identification methodology for automated driving systems fleets

Abstract

The safety of Automated Driving Systems (ADS) operating as Mobility as a Service (MaaS) depends on multiple factors in addition to the vehicle’s functionality, reliability, and performance. Currently, no comprehensive approach has been formally developed to identify operational safety hazards and define the operational safety responsibilities of the key agents involved in Level 4 (L4) ADS MaaS operations. This work develops and applies a structured hazard identification methodology for this operation. The methodology leverages and complements the strengths of various hazard identification and modeling methods, including Event Sequence Diagram (ESD), Concurrent Task Analysis (CoTA), System-Theoretic Process Analysis (STPA), and Fault Tree Analysis (FTA). The methodology is applied to analyze the operation of a fleet of L4 ADS vehicle fleets without a safety driver, monitored and supervised by remote operators. The results highlight the fleet operator’s role in ensuring the correct vehicle operation and preventing and mitigating incidents. The analysis demonstrates the developed methodology’s strengths and suitability for operational safety analysis of complex systems’ operations, considering the inherent complexity of the interactions between multiple human and machine agents.