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Automated driving system (ADS) developers need a way to describe safe and competent driving for automated driving system-dedicated vehicles (ADS-DVs) in a way that is relatable to how stakeholders interpret safe driving today. Metrics informed by competent and safe human behavior could improve understanding and confidence in ADS-DVs. One way to make ADS safety performance relatable to stakeholders is to adopt an intuitive comparison to behaviors displayed on the road by human drivers. This best practice outlines an approach which involves comparing the on-road driving behavior of ADSs to that of human drivers, aiming to gain a deeper understanding of ADS behavior and its implications. It includes and assessment that centers on the predictability and similarity of ADS behavior relative to observed human driving behavior. By adopting this approach, a more comprehensive evaluation of the performance of ADS fleets can be achieved.

AVSC Best Practice for Interactions Between ADS-DVs and Vulnerable Road Users (VRUs) AVSC00009202208 establishes common terminology and a baseline understanding of the challenges posed, and framework to evaluate automated driving system-dedicated vehicle (ADS-DV) interactions with VRUs. This best practice can facilitate communication among the industry and public, help calibrate expectations of all traffic participants, and improve broader acceptance of SAE level 4 and level 5 ADS-equipped vehicles.

Automated driving system-dedicated vehicles (ADS-DVs) can handle a wide variety of circumstances they might encounter on the road. When circumstances are encountered that exceed ADS design capabilities, the ADS is designed to bring the vehicle into a minimal risk condition (MRC). When an ADS-DV encounters these conditions—identified as “triggers” within this best practice—they can request remote assistance (RA) from a remotely located human operator. RA involves the provision of guidance, suggestions, or recommendations to a vehicle from a remote location, without direct control of the vehicle. RA has emerged as a useful tool in supporting the operation of an ADS. It can complement the capabilities of ADS-DVs and improve overall system performance and utilization, particularly in situations that exceed ADS design capabilities. This best practice provides guidelines for integrating remote assistance within the context of ADS.

Successful scaling of automated driving system (ADS) technology and realization of its full potential will require developers and service providers to continuously monitor performance of their fleet and enact prompt improvements should issues arise. ADS developers and manufacturers can use the data collected from vehicles in active deployments (e.g., safety performance data) to proactively confirm initial risk assumptions and feed other safety management processes. This best practice provides an approach to continuous monitoring and potential improvement of safety performance of ADS-DVs after deployment. It also outlines approaches to analyzing data related to known and unknown variations in the ADS-DV’s operating environment and complements other AVSC best practices that provide metrics and methods which can be used to monitor safety [AVSC00006202103, AVSC00008202111] while considering important factors pertaining to how data is collected, analyzed, and used [AVSC00004202009].