Pedestrians and bicyclists are the most vulnerable road users and suffer the most severe consequences when crashes take place. An extensive literature is available for crash severity in terms of driver safety, but fewer studies have explored non-motorized users' crash severity. Furthermore, most research efforts have examined pedestrian and bicyclist crash severity in urban areas. This study focuses on state roads (mostly outside major urban areas) and aims to identify contributing risk factors of fatal and severe crashes involving pedestrians and bicyclists in state roads. Two ordinal regression models were developed (one for pedestrian and the other for bicyclist crashes) to examine crash severity risk factors. Additional models were developed to investigate road and traffic characteristics that could increase the likelihood of fatal crashes. In the model for pedestrian crash severity risk factors such as age, vehicle type and movement, light conditions, road classification, traffic control device, posted speed limit, location of the pedestrian and wet road surface during clear weather conditions are statistically significant. The bicyclist crash severity model indicates that age, crash location, vehicle movement and alcohol intoxication during dark conditions are statistically significant. In terms of road characteristics and traffic conditions, the models suggested risk factors such as arterials, light conditions, posted speed limit, roadways, and high heavy vehicle volume, increased the odds of a crash being fatal.
The results seem to suggest that besides improvements in roadway characteristics, additional countermeasures to reduce crash severity for vulnerable users should include separation of vulnerable users from traffic, educational campaigns, more strict control of alcohol intoxicated drivers, and protection strategies of senior pedestrians.
| Identifer | oai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-5072 |
| Date | 08 December 2017 |
| Creators | Caviedes Cómbita, Àlvaro Alfonso |
| Publisher | PDXScholar |
| Source Sets | Portland State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations and Theses |
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