Abstract

Pedestrian safety is a top priority within the transportation planning community as cities promote sustainable transportation, alternative travel modes, and healthy lifestyles. If people feel unsafe while walking, they will choose other modes of transportation if they are able. To prioritize safety, it is important to know where pedestrian crashes are occurring and with what severity. Using spatial statistical methods including nearest neighbor index, Moran’s I, local indicators of spatial autocorrelation (LISA), and Getis-Ord G-statistic, this study seeks to analyze the pedestrian fatality locations within the state of Ohio over a 10-year period (2007–2016) to identify hot spots, cold spots, and spatial patterns across three different spatial scales: county, census tract, and traffic analysis zone (TAZ). It seeks to understand the effects of aggregated data across these spatial scales on the outcome of the analysis and determine the most useful spatial scale at which to study pedestrian fatalities. The study concludes that spatial analyses at small scales are most informative. It goes on to recommend locations within Ohio for further analysis based on the resulting maps, including areas with outliers. As of writing this, there is no current statewide pedestrian fatality analysis for the state of Ohio.

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