Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model
العنوان: | Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model |
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المؤلفون: | Mingtao Song, Feng Chen, Xiaoxiang Ma |
المصدر: | International Journal of Environmental Research and Public Health Volume 16 Issue 14 International Journal of Environmental Research and Public Health, Vol 16, Iss 14, p 2632 (2019) |
سنة النشر: | 2019 |
مصطلحات موضوعية: | Adult, Male, Computer science, Health, Toxicology and Mutagenesis, Poison control, lcsh:Medicine, Ordered probit, Crash, rear-end crash, Bivariate analysis, Severity of Illness Index, Article, law.invention, Correlation, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Sex Factors, law, 0502 economics and business, Injury prevention, Econometrics, Seat belt, Humans, 030212 general & internal medicine, 050210 logistics & transportation, random parameter bivariate ordered probit, Models, Statistical, 05 social sciences, lcsh:R, Public Health, Environmental and Occupational Health, Accidents, Traffic, Age Factors, Statistical model, Seat Belts, Middle Aged, Wounds and Injuries, injury severity, Female, Air Bags, Automobiles |
الوصف: | The existing studies on drivers&rsquo injury severity include numerous statistical models that assess potential factors affecting the level of injury. These models should address specific concerns tailored to different crash characteristics. For rear-end crashes, potential correlation in injury severity may present between the two drivers involved in the same crash. Moreover, there may exist unobserved heterogeneity considering parameter effects, which may vary across both crashes and individuals. To address these concerns, a random parameters bivariate ordered probit model has been developed to examine factors affecting injury sustained by two drivers involved in the same rear-end crash between passenger cars. Taking both the within-crash correlation and unobserved heterogeneity into consideration, the proposed model outperforms the two separate ordered probit models with fixed parameters. The value of the correlation parameter demonstrates that there indeed exists significant correlation between two drivers&rsquo injuries. Driver age, gender, vehicle, airbag or seat belt use, traffic flow, etc., are found to affect injury severity for both the two drivers. Some differences can also be found between the two drivers, such as the effect of light condition, crash season, crash position, etc. The approach utilized provides a possible use for dealing with similar injury severity analysis in future work. |
وصف الملف: | application/pdf |
تدمد: | 1660-4601 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9423992b72de08a2805d12f031dad926 https://pubmed.ncbi.nlm.nih.gov/31340600 |
حقوق: | OPEN |
رقم الأكسشن: | edsair.doi.dedup.....9423992b72de08a2805d12f031dad926 |
قاعدة البيانات: | OpenAIRE |
تدمد: | 16604601 |
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