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- W2912971670 abstract "This study combined vehicle to vehicle crash frequency and severity estimations to examine factor impacts on Wisconsin highway safety in rainy weather. Primary tasks for this study were conducted as follows. Due to data deficiency, real-time rainfall intensity, water film depth, stopping sight distance, deficiency of car-following distance, and vertical curve grade were estimated through available data sources and GIS analysis to capture rainy weather conditions at the crash location and time. For crash frequency, a negative binomial regression model was estimated while ordered logit and multinomial logit models were compared for crash severity estimation. In crash frequency estimation, average annual daily traffic per lane and the interaction between posted speed limit change and off-ramp existence were found to increase the likelihood of vehicle to vehicle crash occurrences under rainfall. However, more average monthly rainfall and a wider left shoulder width were identified as factors that decrease the likelihood of vehicle to vehicle crash occurrences. In crash severity estimation, higher speed limit, driver's lateral lane control, and no use of safety belt were found to increase the likelihood of severe crashes, especially fatal, incapacitating, and non-incapacitating crashes under rainfall in the multinomial logit model that outperformed the ordered logit model. As an exploratory data analysis, this study provide insight into potential strategies for rainy weather highway safety improvement. The following weather sensitive strategies could prove effective: education enhancement, road design, and intelligent transportation system implementation for driver's safety awareness under rainfall." @default.
- W2912971670 created "2019-02-21" @default.
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- W2912971670 date "2013-01-16" @default.
- W2912971670 modified "2023-09-27" @default.
- W2912971670 title "IMPACTS OF INFLUENTIAL FACTORS ON VEHICLE TO VEHICLE CRASH FREQUENCY AND SEVERITY IN RAINY WEATHER" @default.
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