UCLA

Incorporating automated driving technologies in commercial heavy-duty operations aims to increase traffic efficiency and safety. However, developers, fleet operators, and regulators must address the unique safety risks that Automated Driving System (ADS) technology introduce. Potential Heavy-Duty Automated Vehicle (HD-AV) fleet operations envision a team of human and machine agents, including the ADS, an onboard safety driver, a fleet operations center, and, in some cases, an onboard safety operator. The complex interactions between these human and machine agents must be addressed when determining the system’s safety requirements and design. Safety metrics usually focus on ADS performance, but to adequately inform system design and safety requirements, these metrics must also focus on human-system interactions. This work proposes a system model-based approach to develop human-system interaction metrics focusing on hardware, software, and human impacts on the operational safety of automated driving system fleets.