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- W618687572 abstract "Traffic safety is a top priority for most transportation agencies and many governments. In this study, the geometric details of Texas’ extensive highway network were mapped to a variety of traffic, demographic, and built environment variables, including land use, truck volumes, traffic intensity, local population and jobs density, rainfall, income, and education levels. A zero- inflated negative binomial (ZINB) model was used to allow for excess zeros and over-dispersion, and was statistically preferred to the zero-inflated Poisson (ZIP) and negative binomial (NB) models, thanks to lower prediction errors and more robust parameter inference. Estimation results show how crash frequencies and fatality rates clearly rise with local jobs and population densities (as proxies for land use intensities), as well as rainfall. Interestingly, speed limits and distances to the nearest hospitals have negative associations with segment-based crash rates (everything else constant) but, as expected, positive associations with fatality rates (presumably due to more severe collision impacts at higher speeds and time lost in transporting crash victims)." @default.
- W618687572 created "2016-06-24" @default.
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- W618687572 date "2014-01-01" @default.
- W618687572 modified "2023-09-24" @default.
- W618687572 title "Modeling Crash and Fatality Counts Along Mainlanes and Frontage Roads Across Texas: The Roles of Design, the Built Environment, and Weather" @default.
- W618687572 hasPublicationYear "2014" @default.
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