Bivariate Ordered Modeling of Crash Injury Severity Level of Drivers and School-Age Passengers

Traffic safety has been a serious public health issue, and there have been considerable efforts to minimize the injury severity of crashes if it is inevitable to avoid the occurrence. If this is the case, it is important to put efforts to minimize the severity of crashes to save lives or lessen injury severities. Many previous studies have explored the severity of traffic crashes. Among those studies, many studies have analyzed the highest severity level of crashes has been analyzed with characteristics of drivers, vehicles, roadway, etc. On the other hand, some other studies have investigate the severity level of individual road users including vehicle occupants, pedestrians, bicyclists, etc. Nevertheless, no studies have explored the severity of multiple passengers simultaneously. As it is expected that vehicle occupants in a same vehicle are likely to receive a similar level of crash impact, it would be desirable to consider the shared effects the severity levels of a driver and passenger. In this study, the authors aim at analyzing the severity level of driver and school-age passenger by adopting a bivariate ordered probit model to explore four severity levels (i.e., no injury, possible injury, non-incapacitating injury, and the sum of incapacitating injury and fatal injury). The results indicate that the contributing factors for the severity level of drivers and school-age passengers are quite different. They include individual, vehicle, and residence socio-economic characteristics. It is expected that the findings from this study will contribute to an efficient strategic plan to reduce traffic crashes.

Language

  • English

Media Info

  • Pagination: pp 96 - 102
  • Monograph Title: International Conference on Transportation and Development 2019: Smarter and Safer Mobility and Cities

Subject/Index Terms

Filing Info

  • Accession Number: 01729746
  • Record Type: Publication
  • ISBN: 9780784482575
  • Files: TRIS, ASCE
  • Created Date: Aug 28 2019 3:01PM