Crash Risk Assessment Using Intelligent Transportation Systems Data and Real-Time Intervention Strategies to Improve Safety on Freeways

This article provides a comprehensive overview of the novel idea of real-time traffic safety improvement on freeways. Crash prone conditions on the freeway mainline and ramps were identified using loop detector data, then intelligent transportation systems (ITS) strategies to reduce the crash risk in real-time are proposed. Separate logistic regression models for assessing the risk of crashes occurring under two speed regimes were estimated. The results show that the variables in the two models are consistent with probable mechanisms of crashes under the respective regimes (high-to-moderate and low speed). This study also discusses the analysis of parameters and conditions that affect crash occurrence on freeway ramps by type (on-/off-ramp) and configurations (diamond, loop, etc.) using five-minute traffic flow data obtained from the loop detectors upstream and downstream of ramps to reflect actual traffic conditions prior to the time of crashes. Finally, several traffic management strategies are evaluated for the resulting traffic safety improvement in real-time using PARAMICS microscopic traffic simulation and the measures of crash potential determined through the logistic regression models. The results show that, while variable speed limit strategies reduced the crash potential under moderate-to-high speed conditions, ramp metering strategies were effective in reducing the crash potential during the low-speed conditions.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/15472450
• Supplemental Notes:
  • Abstract reprinted with permission from Taylor and Francis
• Authors:
  • Abdel-Aty, Mohamed
  • Pande, Anurag
  • Lee, Chris
  • Gayah, Vikash
  • Dos Santos, Cristina
• Publication Date: 2007-7

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 107-120
• Serial:
  • Journal of Intelligent Transportation Systems
  • Volume: 11
  • Issue Number: 3
  • Publisher: Taylor & Francis
  • ISSN: 1547-2450
  • EISSN: 1547-2442
  • Serial URL: http://www.tandfonline.com/loi/gits20

Subject/Index Terms

• TRT Terms: Freeways; High risk locations; Highway factors in crashes; Intelligent transportation systems; Interchange ramps; Loop detectors; Microscopic traffic flow; Ramp metering; Real time information; Regression analysis; Risk assessment; Speed limits; Traffic; Traffic crashes; Traffic data; Traffic safety; Traffic simulation; Traffic speed; Variable speed limits
• Subject Areas: Data and Information Technology; Design; Highways; Operations and Traffic Management; Safety and Human Factors; I82: Accidents and Transport Infrastructure; I85: Safety Devices used in Transport Infrastructure;

Filing Info

• Accession Number: 01055217
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 23 2007 1:00PM