Kristofer D. Kusano , John M. Scanlon , Yin-Hsiu Chen , Timothy L. McMurry , Ruoshu Chen , Tilia Gode , Trent Victor
{"title":"在 710 万英里的里程数上,Waymo 骑手专用碰撞数据与人类基准数据的比较。","authors":"Kristofer D. Kusano , John M. Scanlon , Yin-Hsiu Chen , Timothy L. McMurry , Ruoshu Chen , Tilia Gode , Trent Victor","doi":"10.1080/15389588.2024.2380786","DOIUrl":null,"url":null,"abstract":"<div><h3>Objectives</h3><div>This article examines the safety performance of the Waymo Driver, an SAE level 4 automated driving system (ADS) used in a rider-only (RO) ride-hailing application without a human driver, either in the vehicle or remotely.</div></div><div><h3>Methods</h3><div>ADS crash data were derived from NHTSA’s Standing General Order (SGO) reporting over 7.14 million RO miles through the end of October 2023 in Phoenix, Arizona, San Francisco, California, and Los Angeles, California, and compared to human benchmarks from the literature.</div></div><div><h3>Results</h3><div>When considering all locations together, the <em>any injury reported</em> crashed vehicle rate was 0.6 incidents per million miles (IPMM) for the ADS vs. 2.80 IPMM for the human benchmark, an 80% reduction or a human crash rate that is 5 times higher than the ADS rate. <em>Police-reported</em> crashed vehicle rates for all locations together were 2.1 IPMM for the ADS vs. 4.68 IPMM for the human benchmark, a 55% reduction or a human crash rate that was 2.2 times higher than the ADS rate. <em>Police-reported</em> crashed vehicle rate reductions for the ADS were statistically significant when compared in San Francisco and Phoenix, as well as combined across all locations and the any-injury-reported reductions were statistically significant in San Francisco and in all locations. The <em>any property damage or injury</em> comparison had statistically significant decreases in 3 comparisons but also nonsignificant results in 3 other benchmarks. When excluding ADS crashes with a delta-V less than 1 mph (a measure of sensitivity to lower reporting threshold), about half of the ADS collisions were excluded, resulting in comparisons that showed a large statistically significant reduction in all comparisons except for one comparison from San Francisco.</div></div><div><h3>Conclusions</h3><div>The statistically significant reductions in <em>police-reported</em> and <em>any injury reported</em> crash rates indicate a promising positive safety impact of ADS. The direction and significance of comparisons in the <em>any property damage or injury</em> outcome group are inconclusive due to difficulties in estimating a matching human benchmark. More research is needed on defining <em>any property damage or injury</em> benchmarks with clear lower reporting thresholds to reduce the systematic uncertainty in the benchmark rates. Together, these crash rate results contribute to the continuous growth in confidence, together with other methodologies, in a safety case approach.</div></div>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":"25 1","pages":"Pages S66-S77"},"PeriodicalIF":1.6000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Waymo rider-only crash data to human benchmarks at 7.1 million miles\",\"authors\":\"Kristofer D. Kusano , John M. Scanlon , Yin-Hsiu Chen , Timothy L. McMurry , Ruoshu Chen , Tilia Gode , Trent Victor\",\"doi\":\"10.1080/15389588.2024.2380786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objectives</h3><div>This article examines the safety performance of the Waymo Driver, an SAE level 4 automated driving system (ADS) used in a rider-only (RO) ride-hailing application without a human driver, either in the vehicle or remotely.</div></div><div><h3>Methods</h3><div>ADS crash data were derived from NHTSA’s Standing General Order (SGO) reporting over 7.14 million RO miles through the end of October 2023 in Phoenix, Arizona, San Francisco, California, and Los Angeles, California, and compared to human benchmarks from the literature.</div></div><div><h3>Results</h3><div>When considering all locations together, the <em>any injury reported</em> crashed vehicle rate was 0.6 incidents per million miles (IPMM) for the ADS vs. 2.80 IPMM for the human benchmark, an 80% reduction or a human crash rate that is 5 times higher than the ADS rate. <em>Police-reported</em> crashed vehicle rates for all locations together were 2.1 IPMM for the ADS vs. 4.68 IPMM for the human benchmark, a 55% reduction or a human crash rate that was 2.2 times higher than the ADS rate. <em>Police-reported</em> crashed vehicle rate reductions for the ADS were statistically significant when compared in San Francisco and Phoenix, as well as combined across all locations and the any-injury-reported reductions were statistically significant in San Francisco and in all locations. The <em>any property damage or injury</em> comparison had statistically significant decreases in 3 comparisons but also nonsignificant results in 3 other benchmarks. When excluding ADS crashes with a delta-V less than 1 mph (a measure of sensitivity to lower reporting threshold), about half of the ADS collisions were excluded, resulting in comparisons that showed a large statistically significant reduction in all comparisons except for one comparison from San Francisco.</div></div><div><h3>Conclusions</h3><div>The statistically significant reductions in <em>police-reported</em> and <em>any injury reported</em> crash rates indicate a promising positive safety impact of ADS. The direction and significance of comparisons in the <em>any property damage or injury</em> outcome group are inconclusive due to difficulties in estimating a matching human benchmark. More research is needed on defining <em>any property damage or injury</em> benchmarks with clear lower reporting thresholds to reduce the systematic uncertainty in the benchmark rates. Together, these crash rate results contribute to the continuous growth in confidence, together with other methodologies, in a safety case approach.</div></div>\",\"PeriodicalId\":54422,\"journal\":{\"name\":\"Traffic Injury Prevention\",\"volume\":\"25 1\",\"pages\":\"Pages S66-S77\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Traffic Injury Prevention\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/org/science/article/pii/S1538958824001413\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traffic Injury Prevention","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S1538958824001413","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Comparison of Waymo rider-only crash data to human benchmarks at 7.1 million miles
Objectives
This article examines the safety performance of the Waymo Driver, an SAE level 4 automated driving system (ADS) used in a rider-only (RO) ride-hailing application without a human driver, either in the vehicle or remotely.
Methods
ADS crash data were derived from NHTSA’s Standing General Order (SGO) reporting over 7.14 million RO miles through the end of October 2023 in Phoenix, Arizona, San Francisco, California, and Los Angeles, California, and compared to human benchmarks from the literature.
Results
When considering all locations together, the any injury reported crashed vehicle rate was 0.6 incidents per million miles (IPMM) for the ADS vs. 2.80 IPMM for the human benchmark, an 80% reduction or a human crash rate that is 5 times higher than the ADS rate. Police-reported crashed vehicle rates for all locations together were 2.1 IPMM for the ADS vs. 4.68 IPMM for the human benchmark, a 55% reduction or a human crash rate that was 2.2 times higher than the ADS rate. Police-reported crashed vehicle rate reductions for the ADS were statistically significant when compared in San Francisco and Phoenix, as well as combined across all locations and the any-injury-reported reductions were statistically significant in San Francisco and in all locations. The any property damage or injury comparison had statistically significant decreases in 3 comparisons but also nonsignificant results in 3 other benchmarks. When excluding ADS crashes with a delta-V less than 1 mph (a measure of sensitivity to lower reporting threshold), about half of the ADS collisions were excluded, resulting in comparisons that showed a large statistically significant reduction in all comparisons except for one comparison from San Francisco.
Conclusions
The statistically significant reductions in police-reported and any injury reported crash rates indicate a promising positive safety impact of ADS. The direction and significance of comparisons in the any property damage or injury outcome group are inconclusive due to difficulties in estimating a matching human benchmark. More research is needed on defining any property damage or injury benchmarks with clear lower reporting thresholds to reduce the systematic uncertainty in the benchmark rates. Together, these crash rate results contribute to the continuous growth in confidence, together with other methodologies, in a safety case approach.
期刊介绍:
The purpose of Traffic Injury Prevention is to bridge the disciplines of medicine, engineering, public health and traffic safety in order to foster the science of traffic injury prevention. The archival journal focuses on research, interventions and evaluations within the areas of traffic safety, crash causation, injury prevention and treatment.
General topics within the journal''s scope are driver behavior, road infrastructure, emerging crash avoidance technologies, crash and injury epidemiology, alcohol and drugs, impact injury biomechanics, vehicle crashworthiness, occupant restraints, pedestrian safety, evaluation of interventions, economic consequences and emergency and clinical care with specific application to traffic injury prevention. The journal includes full length papers, review articles, case studies, brief technical notes and commentaries.