The operational safety of automated driving system (ADS)-equipped vehicles (AVs) must be quantified using well-defined metrics in order to gain an unambiguous understanding of the level of risk associated with AV deployment on public roads. In this research, efforts to evaluate the operational safety assessment (OSA) metrics introduced in prior work by the Institute of Automated Mobility (IAM) are described. An initial validation of the proposed set of OSA metrics involved using the open-source simulation software Car Learning to Act (CARLA) and Scenario Runner, which are used to place a subject vehicle in selected scenarios and obtain measurements for the various relevant OSA metrics. Car following scenarios were selected from the list of 37 pre-crash scenarios identified by the National Highway Traffic Safety Administration (NHTSA) as the most common driving situations that lead to crash events involving two light vehicles. The resulting data were used to evaluate different parameters and thresholds of the metrics developed in the prior IAM work. The simulation and analysis results were used to evaluate the relevant metrics in the context of a proposed criteria as measurable and applicable to the operational safety of AVs and human-driven vehicles alike in a data-driven approach.
Evaluation of Operational Safety Assessment (OSA) Metrics for Automated Vehicles in Simulation
Sae Technical Papers
SAE WCX Digital Summit ; 2021
2021-04-06
Aufsatz (Konferenz)
Englisch
Evaluation of Operational Safety Assessment (OSA) Metrics for Automated Vehicles in Simulation
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|British Library Conference Proceedings | 2022
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