Browse Standards J3237
WIP 2020-09-16

Driving Assessment (DA) Metrics for Automated Driving Systems J3237

This SAE Recommended Practice provides definitions, taxonomy, and characteristics for DA metrics used to quantify the driving performance of ADS-operated vehicles. Here, the primary focus is on the safety-related driving performance, which is considered to be related to completion of the dynamic driving task (DDT) . Driving performance is a subset of overall operational performance of ADS-operated vehicles. Thus, assessments of cybersecurity, maintenance, interactions with passengers, etc., while important, are out of scope for this document. Note that the DA metrics do not specify the actions and/or maneuvers to be executed by the subject vehicle.

A literature review of DA metrics that have been proposed and, in some cases, used in previous studies was conducted. From this literature review, a set of DA metrics has been created with example usage. Evidence of prior research indicating that a metric has a relationship with safety outcome(s) is included where applicable.

DA metrics might use parameterized variables, assumptions, and thresholds in their formulation. Defining or recommending values for these quantities used in the metrics formulation is outside the scope of this document. It is expected that the methodologies for collecting and assigning such values for these metrics will be developed based on field and other learned experiences with production and prototype vehicles and systems. Values could also be established by regulation, industry best practices, improved technology development, academic research, among others, and may change based on the operating conditions within the ODD. In the interim, it will be the responsibility of the implementer of these metrics to choose values for these quantities.

The DA metrics can be implemented in both development and deployment phases. For example, the metrics can be used as part of a verification and validation (V&V) scenario-based testing process wherein individual scenarios are tested. The metrics measurements can also be aggregated over a period of time or number of scenarios (i.e., a period of time could be considered to be a sequence of scenarios), for example in a public road deployment, in order to monitor driving safety performance.

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