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

    Authors

    M. Abdel-Aty; A. Pande; C. Lee; V. Gayah;C. Dos Santos

    Comments

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    Abbreviated Journal Title

    J. Intell. Transport. Syst.

    Keywords

    real-time crash prediction; ITS data; proactive traffic management; variable speed limit; ramp metering; microscopic simulation; TRAFFIC FLOW; Transportation Science & Technology

    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.

    Journal Title

    Journal of Intelligent Transportation Systems

    Volume

    11

    Issue/Number

    3

    Publication Date

    1-1-2007

    Document Type

    Article

    Language

    English

    First Page

    107

    Last Page

    120

    WOS Identifier

    WOS:000248105000002

    ISSN

    1547-2450

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