Improving the Content of Crash Records: The Case for a Data Fusion Approach

Understanding factors contributing to crashes requires reliable records and detailed highway characteristics information. However, too often the information required for safety evaluations is not part of the crash records. Even when the technology exists to enable crash records to be supplemented with detailed highway information existing practices often fail to utilize the available technology. Due to the manual, semi-automated, nature of the crash reporting process, even when electronic forms are used, information included in the records is often incomplete or inaccurate. For example, contributing factors and highway characteristics entered into the crash report form are often the result of the interpretation of the police officer which can vary across the state. Supplementing crash records with highway information often involves the use of manual to semi-automated steps. These steps result in an unnecessary slow process given that the data required is often available in databases owned by transportation agencies. In this paper the use of an automated data fusion approach to supplement existing crash records with detailed highway information is presented. The data fusion approach presented relies on a photographic highway log, a data source traditionally owned by transportation agencies. Procedures presented enable the identification of horizontal and vertical roadway alignment characteristics such as curve radii, vertical curve characteristics, and vertical grade along with photographs of the roadway cross section upstream of the crash location. The supplemental roadway data identified is added to the crash record thus improving the amount of data available for safety evaluations.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ20 Standing Committee on Statewide Transportation Data and Information Systems.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Santiago-Chaparro, Kelvin R
  • Brose, Kirsten
  • Bill, Andrea
  • Noyce, David A
• Conference:
  • Transportation Research Board 95th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2016-1-10 to 2016-1-14
• Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: 15p
• Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Crash causes; Crash data; Data collection; Data fusion; Image processing; Photologging
• Geographic Terms: Wisconsin
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I72: Traffic and Transport Planning; I80: Accident Studies;

Filing Info

• Accession Number: 01590306
• Record Type: Publication
• Report/Paper Numbers: 16-1746
• Files: TRIS, TRB, ATRI
• Created Date: Feb 16 2016 3:31PM