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Cross-section fatal crash type prediction models

Posted on:2011-09-13Degree:Ph.DType:Dissertation
University:Oregon State UniversityCandidate:Zhu, HongFull Text:PDF
GTID:1442390002454886Subject:Statistics
Abstract/Summary:
The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes. The major research objectives are to investigate the relations between probabilities of fatal crash type occurrence and potential contributing factors from road geometric design characteristics and roadside, environmental features. This dissertation analyzes the regional fatal crash database and successfully develops statistical models to examine the relations and provided meaningful research findings.;This dissertation contributes to current traffic safety analysis by directly examining the connection between major fatal crash type occurrence and roadway geometrics, roadside characteristics, and environmental conditions through a regional case study. This study effort addresses the less understood relationship between fatal crash types and road features compared to other crash measures, such as crash frequency, crash rate, and injury severity. The developed fatal crash type prediction models not only demonstrate strong connections between crash types and road characteristics, but also provide a quantitative assessment tool for countermeasures in terms of reduction of fatal crash type occurrence. Since most countermeasures are more effective at mitigating certain type of crashes, the information revealed from the crash type prediction models help clarify the relationship between candidate countermeasures and expected crash reductions.
Keywords/Search Tags:Crash type, Models
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