A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity

Sigal Kaplan, Carlo Giacomo Prato

    Research output: Contribution to conferenceConference abstract for conferenceResearch

    Abstract

    Effective crash avoidance maneuvers in response to critical unexpected traffic events provide the opportunity to avoid crash occurrence and to minimize crash severity. The current study employs a joint multinomial-logit ordered-probit model (MNL-OR) for associating crash severity with drivers' propensity to engage in various corrective maneuvers in the case of the critical event of vehicle travelling. Five lateral and speed control maneuvers are considered: “braking”, “steering”, “braking & steering”, and “other maneuvers”, in addition to a “no action” option. The analyzed data are retrieved from the United States National Automotive Sampling System General Estimates System (GES) crash database for the years 2005-2009. Results show (i) the correlation between crash avoidance maneuvers and crash severity, and (ii) the link between drivers' attributes, risky driving behavior, road characteristics and environmental conditions, with the propensity to engage in crash avoidance maneuvers and crash severity.
    Original languageEnglish
    Publication date2012
    Number of pages1
    Publication statusPublished - 2012
    Event10th Transport Engineering Conference - Granada, Spain
    Duration: 20 Jun 201222 Jun 2012

    Conference

    Conference10th Transport Engineering Conference
    CountrySpain
    CityGranada
    Period20/06/201222/06/2012

    Keywords

    • Crash avoidance maneuvers
    • MNL-OR
    • Crash severity

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