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To investigate pedestrian exposure when only pedestrian-crash data are available, the quasi-induced exposure method is used to identify the factors that contributed to pedestrian-vehicle crashes in Las Vegas from 2004 to 2008. The results show that overall crash severity, light conditions, and weather conditions are potentially risky factors in pedestrian crashes, and the time of day or day of the week are less risky. Multiple-correspondence analysis (MCA) is then used to investigate how pedestrian crash severity is influenced by the interactions among a range of variables. The results indicate that among instances of pedestrian-vehicle crashes cases of property damage only tend to occur during off-peak daytime hours and under dark or dawn light conditions in clear weather. Crashes resulting in injuries usually occur during weekday peak hours in daylight and under rainy conditions. Most fatal crashes occur during off-peak hours, at night on the weekends. [ABSTRACT FROM AUTHOR]

Minority status and low-income are two important criteria on which environmental-justice areas are being identified. These unique areal characteristics have been of particular interest to traffic safety analysts in investigating pedestrian safety planning factors in deprived areas. In this study, a pedestrian crash model was developed for these areas explicitly accounting for the spatial autocorrelations of different zonal factors commonly used in the traditional transportation planning models. It was found that the Bayesian Poisson-lognormal model with a spatial effect term performed the best compared to the models without accounting for spatial autocorrelations. [ABSTRACT FROM AUTHOR]