An Exploration of Pedestrian Safety Through the Integration of HSIS and Emerging Data Sources: Case Study in Charlotte, NC

This report built on a geospatial pilot effort by the Highway Safety Information System (HSIS) using data from Charlotte, NC. The main objective of this study was to spatially integrate HSIS data with multi-jurisdictional and emerging datasets to analyze two measures of pedestrian safety performance: the severity of a pedestrian crash that has occurred, and the probability that a pedestrian crash will occur. The study explored several high-priority research topics in safety data and analysis, including pedestrian crash analysis, probe data integration and analysis, and geospatial HSIS data integration. The project team developed a pedestrian count model to predict pedestrian volumes at locations without pedestrian counts and integrated speed information from probe data to supplement other roadway and contextual transportation data from several agencies. Demographic and socioeconomic characteristics, employment, land use, sidewalk presence, transit access, and roadway and intersection characteristics all significantly contributed to pedestrian volume predictions. The project team identified numerous significant factors that influenced pedestrian crash severity and probability. These factors included those identified in previous research, as well as new relationships between pedestrian volumes and vehicular traffic that have implications for pedestrian safety-in-numbers concepts. Results showed that higher pedestrian volumes resulted in both lower crash severities and probabilities, but the safety benefit was reduced by higher vehicle volumes. Higher speeds, higher traffic volumes, larger vehicles striking the pedestrian, pedestrian impairment, and older pedestrian ages were all indicative of higher probabilities of a pedestrian crash resulting in a fatality or serious injury. By adding a direct measure of speed from probe data (and given the known importance of speed to crash injury severity), the pedestrian crash severity model excluded commonly used speed surrogates without sacrificing model fit. The probability of a pedestrian crash occurring on a road segment was affected by segment length, interactions of pedestrian volumes and traffic volumes, and interactions of posted speed limit, median presence, and number of lanes. This study highlights the applicability of integrating HSIS with emerging safety data resources to inform data-driven and performance-based approaches to road safety management.

• Record URL:
  https://www.fhwa.dot.gov/publications/research/safety/21087/21087.pdf
• Summary URL:
  https://www.fhwa.dot.gov/publications/research/safety/21087/index.cfm
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/57960
• Corporate Authors:

  Vanasse Hangen Brustlin, Incorporated

  Raleigh, NC  United States 

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Hamilton, Ian
  • 0000-0003-0949-5495
  • Kersavage, Kristin
  • 0000-0002-3601-7766
  • Porter, R J
  • 0000-0001-8535-3451
  • Smith, Keith
  • 0000-0003-4520-8473
  • Sanchez, Josie
  • Gayah, Vikash
  • 0000-0002-0648-3360
  • Eccles, Kimberly
  • 0000-0001-7522-9609
• Publication Date: 2021-10

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Report
• Features: Figures; Maps; References; Tables;
• Pagination: 67p

Subject/Index Terms

• TRT Terms: Crash data; Crash risk forecasting; Crash severity; Pedestrian safety; Pedestrian vehicle crashes
• Identifier Terms: Highway Safety Information System
• Geographic Terms: Charlotte (North Carolina)
• Subject Areas: Data and Information Technology; Highways; Pedestrians and Bicyclists; Safety and Human Factors;

Filing Info

• Accession Number: 01782472
• Record Type: Publication
• Report/Paper Numbers: FHWA-HRT-21-087
• Contract Numbers: DTFH61-11-C-00050
• Files: NTL, TRIS, ATRI, USDOT
• Created Date: Sep 22 2021 12:04PM