Planning-Level Model for Assessing Pedestrian Safety

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 captured relationships at the level of census block groups, whereas most past studies reported relationships at the level of census tracts. In addition, the models developed in this study included the effect of certain variables at multiple spatial scales and yielded interesting results. In particular, the variables at multiple scales clearly indicated locations with larger volumes of conflicting vehicular and pedestrian movements to be of higher risk for pedestrian crashes.

• Record URL:
  https://doi.org/10.3141/2464-14
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780309295567
• Authors:
  • Jermprapai, Khajonsak
  • Srinivasan, Sivaramakrishnan
• Publication Date: 2014

Language

• English

Media Info

• Media Type: Print
• Features: Figures; Maps; References; Tables;
• Pagination: pp 109–117
• Monograph Title: Pedestrians 2014
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 2464
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Crash risk forecasting; High risk locations; Pedestrian safety; Pedestrian vehicle crashes; Spatial analysis
• Geographic Terms: Florida
• Subject Areas: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; I81: Accident Statistics;

Filing Info

• Accession Number: 01518659
• Record Type: Publication
• ISBN: 9780309295567
• Report/Paper Numbers: 14-5360
• Files: TRIS, TRB, ATRI
• Created Date: Mar 20 2014 1:39PM