DREDGE (Disaggregate Realistic Artificial Data Generator)—Design, Development, and Application for Crash Safety Analysis, Volume I

Safety analysis primarily focuses on identifying and quantifying the influences of contributing factors to traffic collisions and the consequences of these factors. A practice of relying on observed data only allows relative comparisons between analysis methods and may not lead to determining how well the methods mimic the true underlying crash-generation process, which is often unobserved or known only partially, with varying degrees of certainty. This report describes a study, performed by researchers working under the Federal Highway Administration, to help address this data limitation. Researchers used two approaches to generate realistic artificial data (RAD): In the macroscopic approach, researchers generated RAD at site level by segment or intersection after generating traffic and roadway characteristics by segment or intersection for various facility types. Crashes were then generated using known model structures, based on these characteristics. The microscopic approach built a high-resolution, disaggregate data-generation process that mimics crash occurrences on road facilities at the trip level and accommodates the influence of a full range of crash-contributing factors to generate crashes. This crash generation employs data describing the generated trips and involves identifying the vehicles involved in the crash, crash location, severity of occupant injuries, and crash type. These generated crashes can be aggregated at any spatial or temporal resolution to estimate and evaluate safety models. The researchers thus developed a RAD generator as a standalone, customizable software application tool that can prepare multiple realizations of RAD. The tool was evaluated using two case studies involving segment crashes and intersection crashes. This volume is the first in a series. Volume Ⅱ in the series is FHWA-HRT-23-122.

• Record URL:
  • https://highways.dot.gov/sites/fhwa.dot.gov/files/FHWA_HRT_23_121.pdf
• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/73510
• Corporate Authors:

  University of Connecticut, Storrs

  Connecticut Transportation Institute
  270 Middle Turnpike, Unit 5202
  Storrs, CT  United States  06269-5202

  Federal Highway Administration

  Turner-Fairbank Highway Research Center, 6300 Georgetown Pike
  McLean, VA  United States  22101
• Authors:
  • Ivan, John
  • 0000-0002-8517-4354
  • Zhao, Shanshan
  • 0000-0001-5476-6894
  • Wang, Kai
  • 0000-0003-1452-4000
  • Olufowobi, Oluwaseun
  • 0009-0001-1339-9095
  • Eluru, Naveen
  • 0000-0003-1221-4113
  • Bhowmik, Tanmoy
  • 0000-0002-0258-1692
  • Hoover, Lauren
  • 0009-0004-2431-0860
  • Jahan, Md I
  • 0000-0002-4056-7816
  • Tirtha, Sudipta
  • 0000-0002-6228-0904
  • Abdel-Aty, Mohamad
  • 0000-0002-4838-1573
• Publication Date: 2024-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Bibliography; Figures; Photos; References; Tables;
• Pagination: 136p

Subject/Index Terms

• TRT Terms: Crash analysis; Crash data; Data collection; Data quality; Traffic crashes; Virtual reality
• Identifier Terms: U.S. Federal Highway Administration
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01914072
• Record Type: Publication
• Report/Paper Numbers: FHWA-HRT-23-121
• Contract Numbers: 693JJ31950017
• Files: NTL, TRIS, USDOT
• Created Date: Apr 8 2024 9:16AM