A stochastic catastrophe model using two-fluid model parameters to investigate traffic safety on urban arterials

    Authors

    P. Y. Park;M. Abdel-Aty

    Comments

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    Abbreviated Journal Title

    Accid. Anal. Prev.

    Keywords

    Catastrophe model; Urban arterials; Two-fluid model; Pro-active safety; ACCIDENT PROCESS; POISSON; FLOW; VARIABLES; Ergonomics; Public, Environmental & Occupational Health; Social; Sciences, Interdisciplinary; Transportation

    Abstract

    During the last few decades, the two-fluid model and its two parameters have been widely used in transportation engineering to represent the quality of operational traffic service on urban arterials. Catastrophe models have also often been used to describe traffic flow on freeway sections. This paper demonstrates the possibility of developing a pro-active network screening tool that estimates the crash rate using a stochastic cusp catastrophe model with the two-fluid model's parameters as inputs. The paper investigates the analogy in logic behind the two-fluid model and the catastrophe model using straightforward graphical illustrations. The paper then demonstrates the application of two-fluid model parameters to a stochastic catastrophe model designed to estimate the level of safety on urban arterials. Current road safety management, including network safety screening, is post-active rather than pro-active in the sense that an existing hotspot must be identified before a safety improvement program can be implemented. This paper suggests that a stochastic catastrophe model can help us to become more pro-active by helping us to identify urban arterials that currently show an acceptable level of safety, but which are vulnerable to turning into crash hotspots. We would then be able to implement remedial actions before hotspots develop. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.

    Journal Title

    Accident Analysis and Prevention

    Volume

    43

    Issue/Number

    3

    Publication Date

    1-1-2011

    Document Type

    Article

    Language

    English

    First Page

    1267

    Last Page

    1278

    WOS Identifier

    WOS:000288971200084

    ISSN

    0001-4575

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