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原文传递 Rural Pedestrian Crash Rate: Alternative Measures of Exposure

题名：	Rural Pedestrian Crash Rate: Alternative Measures of Exposure
作者：	John Ivan; Paul J. Ossenbruggen; Xiao Qin; Jyothi Pendarkar
关键词：	Pedestrian Exposure; Highway Safety; Rural; General Linear Regression (GLM); Logistic Regression; Duncan Multiple Comparison of Means; Prediction Model; Land Use, Pedestrians, Traffic Control, Roadway Design.
摘要：	The objective of this research is to better understand how to prevent pedestrian fatalities by investigating new means of measuring pedestrian exposure to crashes. The study involves finding ways to estimate pedestrian volumes (pedestrians per week) on specific facilities, focusing on rural areas. Part I investigates the relationship between the weekly pedestrian exposure in rural areas of Connecticut and factors such as population density, sidewalk system, number of lanes, area type, signal type and median household income. General Linear Regression (GLM) and Tukey or Duncan multiple comparison of means methods are used to identify the significant factors. Only the number of lanes, area type and sidewalk system are significant in the resulting model for pedestrian exposure Other factors do not significantly explain the variation in the pedestrian exposure. Part n identifies site characteristics, i.e., factors describing land use activity, roadside design, merging and crossing traffic, traffic control and vehicular speed, that can be used to predict roadway risk, the probability of a crash leading to injury md/or death. All variables, with the exception of crosswalks, street parking and paved shoulder width, proved significant. Typical village and residential sites proved to be the least hazardous and shopping sites the most hazardous. The findings from this project could significantly change the way pedestrian crashes are reported and analyzed, and thus improve their usefulness and meaning. This new reporting format could help jurisdictions decide how to allocate funds for enhancing pedestrian safety by giving them more detailed information about where the enhancements are best applied. This research also has applications toward general travel demand forecasting, by providing insight into how to better predict the choice of walking as a travel mode.
报告类型：	科技报告