Using Emerging and Extraordinary Data Sources to Improve Traffic Safety

The current safety management program in Indiana uses a method based on aggregate crash data for conditions averaged over several-year periods with consideration of only major roadway features. This approach does not analyze the risk of crashes potentially affected by time-dependent conditions such as traffic control, operations, weather and their interaction with road geometry. With the rapid development of data collection techniques, time-dependent data have emerged, some of which have become available for safety management. This project investigated the feasibility of using emerging and existing data sources to supplement the current safety management practices in Indiana and performed a comprehensive evaluation of the quality of the new data sources and their relevance to traffic safety analysis. In two case studies, time-dependent data were acquired and integrated to estimate their effects on the hourly probability of crash and its severity on two selected types of roads: (1) rural freeways and (2) signalized intersections. The results indicate a considerable connection between hourly traffic volume, average speeds, and weather conditions on the hourly probability of crash and its severity. Although some roadway geometric features were found to affect safety, the lack of turning volume data at intersections led to some counterintuitive results. Improvements have been identified to be implemented in the next phase of the project to eliminate these undesirable results.

• Record URL:
  https://doi.org/10.5703/1288284317283
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/56470
• Corporate Authors:

  Purdue University

  Joint Transportation Research Program
  West Lafayette, IN  United States  47907-2051

  Indiana Department of Transportation

  100 N Senate Avenue
  Indianapolis, IN  United States  46204

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Tarko, Andrew P
  • Guo, Qiming
  • Pineda-Mendez, Raul
• Publication Date: 2021-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 78p

Subject/Index Terms

• TRT Terms: Case studies; Crash risk forecasting; Crash severity; Data analysis; Data fusion; Feasibility analysis; Rural highways; Safety management; Signalized intersections; Traffic data; Traffic safety
• Geographic Terms: Indiana
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01776521
• Record Type: Publication
• Report/Paper Numbers: FHWA/IN/JTRP-2021/04
• Contract Numbers: SPR-4302
• Files: NTL, TRIS, ATRI, USDOT, STATEDOT
• Created Date: Jul 14 2021 1:43PM