Abstract:
Crash prediction models are useful tools for identifying locations that have a higher risk of crashes and for prioritizing projects. The focus of this study was on developing macroscopic or planning-level models for pedestrian safety. Although such efforts have been undertaken, they have generally focused on specific cities or counties with census tracts as the unit of the analysis. This study analyzed a larger study area (the state of Florida) at a finer spatial resolution (census block groups instead of tracts). Four models were developed to (...)
Crash prediction models are useful tools for identifying locations that have a higher risk of crashes and for prioritizing projects. The focus of this study was on developing macroscopic or planning-level models for pedestrian safety. Although such efforts have been undertaken, they have generally focused on specific cities or counties with census tracts as the unit of the analysis. This study analyzed a larger study area (the state of Florida) at a finer spatial resolution (census block groups instead of tracts). Four models were developed to determine the crash frequency for each census block group. The models were for total crashes, severe and fatal crashes, fatal crashes, and nighttime crashes. The estimated models captured the effects of several socioeconomic, transportation, land use, and contextual variables. The results generally reaffirmed past findings about the relationship between crashes and socioeconomic, transportation, and land use characteristics. However, the models in this study capture... (Read More)
Transportation Research Record: Journal of the Transportation Research Board ·
2014
Transport engineering |
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