A Methodology to Identify Factors associated with Pedestrian High Crash Clusters Using GIS Based Local Spatial Autocorrelation

In order to identify high crash locations, the Tennessee Department of Transportation (TDOT) has an extensive road safety audit program which uses criteria based on the ratio of crashes to average daily traffic but does not target locations with a high number of pedestrian crashes since there are no pedestrian counts. Apart from ratio approach, a robust methodology is not currently available to identify pedestrian high-crash locations in Tennessee. The objective of this study is to develop a different methodology based on Anselin’s Local Moran I index in Geographic Information System (GIS) to detect high crash clusters and investigate the factors that influence the concentration of pedestrian crashes. Using pedestrian crash data from Shelby County in Tennessee, the study found that spatial dependence plays a strong role during the analyses of pedestrian crashes. These spatial dependencies, accounted through spatial autocorrelation, helped to detect statistically significant clusters of crashes in a GIS framework. These clusters were then overlaid with selected socio-economic and population demographic data in order to identify their association with high crash clusters. The study found the following factors to be associated with high crash clusters: when more than 25% percentage of the population is 18 years of age and younger, when the population of seniors is greater than 13%, when there’s a high population density of low income people, and when the percentage of families below poverty level is greater than 10%. The cluster maps may help transportation agencies to understand issues of pedestrian crashes for safety enhancements.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ANF10 Pedestrians.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Emaasit, Daniel
  • Chimba, Deo
  • Cherry, Christopher R
  • Kutela, Boniphace
  • Wilson, Jessica
• Conference:
  • Transportation Research Board 92nd Annual Meeting
  • Location: Washington DC, United States
  • Date: 2013-1-13 to 2013-1-17
• Date: 2013

Language

• English

Media Info

• Media Type: Digital/other
• Features: Maps; References; Tables;
• Pagination: 20p
• Monograph Title: TRB 92nd Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Age; Autocorrelation; Cluster analysis; Crash analysis; Geographic information systems; High risk locations; Income; Pedestrian safety; Pedestrian vehicle crashes; Spatial analysis
• Subject Areas: Pedestrians and Bicyclists; Safety and Human Factors; I83: Accidents and the Human Factor;

Filing Info

• Accession Number: 01472449
• Record Type: Publication
• Report/Paper Numbers: 13-0634
• Files: TRIS, TRB, ATRI
• Created Date: Feb 19 2013 8:46AM