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

Publication: ResearchConference abstract for conference – Annual report year: 2012

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A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity. / Kaplan, Sigal; Prato, Carlo Giacomo.

2012. Abstract from 10th Transport Engineering Conference, Granada, Spain.

Publication: ResearchConference abstract for conference – Annual report year: 2012

Harvard

Kaplan, S & Prato, CG 2012, 'A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity' 10th Transport Engineering Conference, Granada, Spain, 20/06/12 - 22/06/12,

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Author

Kaplan, Sigal; Prato, Carlo Giacomo / A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity.

2012. Abstract from 10th Transport Engineering Conference, Granada, Spain.

Publication: ResearchConference abstract for conference – Annual report year: 2012

Bibtex

@misc{b73cca10e2f448b4a61e76091624d7b5,
title = "A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity",
author = "Sigal Kaplan and Prato, {Carlo Giacomo}",
year = "2012",
type = "ConferencePaper <importModel: ConferenceImportModel>",

}

RIS

TY - ABST

T1 - A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity

A1 - Kaplan,Sigal

A1 - Prato,Carlo Giacomo

AU - Kaplan,Sigal

AU - Prato,Carlo Giacomo

PY - 2012

Y1 - 2012

N2 - 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 &amp; 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.

AB - 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 &amp; 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.

KW - Crash avoidance maneuvers

KW - MNL-OR

KW - Crash severity

ER -