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arXiv:2505.01515cs.RO

Comparison of Waymo Rider-Only Crash Rates by Crash Type to Human Benchmarks at 56.7 Million Miles

Kristofer D. Kusano, John M. Scanlon, Yin-Hsiu Chen, Timothy L. McMurry, Tilia Gode, Trent Victor

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Abstract

SAE Level 4 Automated Driving Systems (ADSs) are deployed on public roads, including Waymo's Rider-Only (RO) ride-hailing service (without a driver behind the steering wheel). The objective of this study was to perform a retrospective safety assessment of Waymo's RO crash rate compared to human benchmarks, including disaggregated by crash type. Eleven crash type groups were identified from commonly relied upon crash typologies that are derived from human crash databases. Human benchmarks were aligned to the same vehicle types, road types, and locations as where the Waymo Driver operated. Waymo crashes were extracted from the NHTSA Standing General Order (SGO). RO mileage was provided by the company via a public website. Any-injury-reported, Airbag Deployment, and Suspected Serious Injury+ crash outcomes were examined because they represented previously established, safety-relevant benchmarks where statistical testing could be performed at the current mileage. Data was examined over 56.7 million RO miles through the end of January 2025, resulting in a statistically significant lower crashed vehicle rate for all crashes compared to the benchmarks in Any-Injury-Reported and Airbag Deployment, and Suspected Serious Injury+ crashes. Of the crash types, V2V Intersection crash events represented the largest total crash reduction, with a 96% reduction in Any-injury-reported (87%-99% CI) and a 91% reduction in Airbag Deployment (76%-98% CI) events. Cyclist, Motorcycle, Pedestrian, Secondary Crash, and Single Vehicle crashes were also statistically reduced for the Any-Injury-Reported outcome. There was no statistically significant disbenefit found in any of the 11 crash type groups. This study represents the first retrospective safety assessment of an RO ADS that made statistical conclusions about more serious crash outcomes and analyzed crash rates on a crash type basis.

arXiv comments
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DOI
Subjects
cs.RORobotics cs.CYComputers and Society

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