Crash risk assessment using intelligent transportation systems data and real-time intervention strategies to improve safety on freeways

Mohamed Abdel-Aty, Anurag Pande, Chris Lee, Vikash Varun Gayah, Cristina Dos Santos

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)107-120
Number of pages14
JournalJournal of Intelligent Transportation Systems: Technology, Planning, and Operations
Volume11
Issue number3
DOIs
StatePublished - Jul 1 2007

Fingerprint

Intelligent Transportation Systems
Highway systems
Crash
Risk Assessment
Risk assessment
Safety
Real-time
Logistics
Detectors
Logistic Regression Model
Traffic
Diamonds
Detector
Strategy
Traffic Simulation
Traffic Management
Probable
Strombus or kite or diamond
Traffic Flow
High Speed

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Automotive Engineering
  • Aerospace Engineering
  • Computer Science Applications
  • Applied Mathematics

Cite this

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Crash risk assessment using intelligent transportation systems data and real-time intervention strategies to improve safety on freeways. / Abdel-Aty, Mohamed; Pande, Anurag; Lee, Chris; Gayah, Vikash Varun; Santos, Cristina Dos.

In: Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, Vol. 11, No. 3, 01.07.2007, p. 107-120.

Research output: Contribution to journalArticle

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