撞车
毒物控制
工程类
航空学
法律工程学
运输工程
伤害预防
人为因素与人体工程学
职业安全与健康
医疗急救
计算机科学
医学
病理
程序设计语言
作者
Kristofer D. Kusano,John M. Scanlon,Yin-Hsiu Chen,Timothy L. McMurry,Tilia Gode,Trent Victor
标识
DOI:10.1080/15389588.2025.2499887
摘要
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 developed from state vehicle miles traveled (VMT) and police-reported crash data. 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 were 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% confidence interval) and a 91% reduction in Airbag Deployment (76-98% confidence interval) 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 (Airbag Deployment and Suspected Serious Injury+) and analyzed crash rates on a crash type basis. The crash type breakdown applied in the current analysis provides unique insight into the direction and magnitude of safety impact being achieved by a currently deployed ADS system. This work should be considered by stakeholders, regulators, and other ADS companies aiming to objectively evaluate the safety impact of ADS technology.
科研通智能强力驱动
Strongly Powered by AbleSci AI