A systemic pedestrian safety planning tool for rural and small urban areas

Abstract

Rural areas bear a disproportionate number of pedestrian fatalities: the fatality rate per 100 million vehicle miles traveled is 2.5 times higher in rural areas than in urban areas. To measurably improve pedestrian safety, it is paramount to predict crash hot spots and apply cost-effective countermeasures. This dissertation work developed a new systemic pedestrian safety tool to enhance crash hotspot identification and safety project prioritization for rural and small urban areas. This new tool suggested a six-step systemic safety framework: (1) initial screening, which identifies what type of facilities are more prone to pedestrian crashes, (2) pedestrian exposure estimation, which provides an area-level exposure metric using National Household Travel Survey (NHTS) 2009, (3) crash risk factor identification, which identifies the factors that contribute to the occurrence and high severity levels of pedestrian crashes, (4) hotspot identification, which identifies the locations that are more likely to experience pedestrian crashes using two-step floating catchment area (2SFCA) method, (5) countermeasure selection, which provides candidate countermeasures through literature sources, and (6) project prioritization, which ranks safety projects through a mixed linear programming. This study incorporated three states' pedestrian crash data from 2011 to 2013: Texas, Oregon, and Montana. It was found that in rural and small urban areas pedestrian safety is associated negatively with male and elderly drivers, shoulder presence, bike lane presence, higher speed limit, number of lanes, wet surface, pedestrian exposure, hospital distance, population density, median income, share of industrial and commercial areas, and dark hours. In contrast, the pedestrian safety is associated positively with signal control, sidewalk and warning sign presence, median presence, icy and snowy surface, higher AADT, and high densely household areas. To validate the proposed hotspot and project prioritization methods, this study used the pedestrian crash data set from 2014 to 2016 in the City of Bozeman, a small urban area. According to findings, about 60 percent of crash locations fall on areas with a high crash risk index. Reasonable countermeasures were suggested for twenty intersections with highest crash risk index. It was found that budget of $100,000 is the optimal budget, where the crash risk index was reduced by 63 percent.