{"title":"碰撞面积和速度对动力两轮车碰撞死亡和受伤风险的影响","authors":"P. Terranova, F. Guo, Miguel A. Perez","doi":"10.4271/09-11-02-0010","DOIUrl":null,"url":null,"abstract":"<div>The primary objective of this study was to evaluate the fatality risk of powered two-wheeler (PTW) riders across different impact orientations while controlling for different opponent vehicle (OV) types. For the crash configurations with higher fatality rate, the secondary objective was to create an initial speed–fatality prediction model specific to the United States. Data from the NHTSA Crash Reporting Sampling System and the Fatality Analysis Reporting System from 2017 to 2020 was used to estimate the odds of the different possible vehicle combinations and orientations in PTW–OV crashes. Binary logistic regression was then used to model the speed–fatality risk relationship for the configurations with the highest fatality odds. Results showed that collisions with heavy trucks were more likely to be fatal for PTW riders than those with other OV types. Additionally, the most dangerous impact orientations were found to be those where the PTW impacted the OVs front or sides, with fatality odds, respectively, four and five times higher than when the OV rear-end was impacted. The high variability in the odds of different crash configurations suggests the importance of considering the impact orientation factor in future injury prediction models. The speed–fatality prediction models developed for head-on and side crashes could provide an initial tool to evaluate the effectiveness of advanced rider assistance systems and other safety countermeasures in the United States, particularly those that result in speed reductions.</div>","PeriodicalId":42847,"journal":{"name":"SAE International Journal of Transportation Safety","volume":"24 1","pages":"0"},"PeriodicalIF":0.7000,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact Area and Speed Effects on Powered Two-Wheeler Crash Fatality and Injury Risk\",\"authors\":\"P. Terranova, F. Guo, Miguel A. Perez\",\"doi\":\"10.4271/09-11-02-0010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>The primary objective of this study was to evaluate the fatality risk of powered two-wheeler (PTW) riders across different impact orientations while controlling for different opponent vehicle (OV) types. For the crash configurations with higher fatality rate, the secondary objective was to create an initial speed–fatality prediction model specific to the United States. Data from the NHTSA Crash Reporting Sampling System and the Fatality Analysis Reporting System from 2017 to 2020 was used to estimate the odds of the different possible vehicle combinations and orientations in PTW–OV crashes. Binary logistic regression was then used to model the speed–fatality risk relationship for the configurations with the highest fatality odds. Results showed that collisions with heavy trucks were more likely to be fatal for PTW riders than those with other OV types. Additionally, the most dangerous impact orientations were found to be those where the PTW impacted the OVs front or sides, with fatality odds, respectively, four and five times higher than when the OV rear-end was impacted. The high variability in the odds of different crash configurations suggests the importance of considering the impact orientation factor in future injury prediction models. The speed–fatality prediction models developed for head-on and side crashes could provide an initial tool to evaluate the effectiveness of advanced rider assistance systems and other safety countermeasures in the United States, particularly those that result in speed reductions.</div>\",\"PeriodicalId\":42847,\"journal\":{\"name\":\"SAE International Journal of Transportation Safety\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SAE International Journal of Transportation Safety\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4271/09-11-02-0010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"TRANSPORTATION SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SAE International Journal of Transportation Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4271/09-11-02-0010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Impact Area and Speed Effects on Powered Two-Wheeler Crash Fatality and Injury Risk
The primary objective of this study was to evaluate the fatality risk of powered two-wheeler (PTW) riders across different impact orientations while controlling for different opponent vehicle (OV) types. For the crash configurations with higher fatality rate, the secondary objective was to create an initial speed–fatality prediction model specific to the United States. Data from the NHTSA Crash Reporting Sampling System and the Fatality Analysis Reporting System from 2017 to 2020 was used to estimate the odds of the different possible vehicle combinations and orientations in PTW–OV crashes. Binary logistic regression was then used to model the speed–fatality risk relationship for the configurations with the highest fatality odds. Results showed that collisions with heavy trucks were more likely to be fatal for PTW riders than those with other OV types. Additionally, the most dangerous impact orientations were found to be those where the PTW impacted the OVs front or sides, with fatality odds, respectively, four and five times higher than when the OV rear-end was impacted. The high variability in the odds of different crash configurations suggests the importance of considering the impact orientation factor in future injury prediction models. The speed–fatality prediction models developed for head-on and side crashes could provide an initial tool to evaluate the effectiveness of advanced rider assistance systems and other safety countermeasures in the United States, particularly those that result in speed reductions.