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Title:

Individual Driver Risk Analysis Using Naturalistic Driving Data
Cover of Individual Driver Risk Analysis Using Naturalistic Driving Data

Accession Number:

01504377

Record Type:

Component

Abstract:

Individual driver risk varies substantially and a small percentage of drivers often contribute to a disproportionate large number of safety events. Identifying factors associated with individual drivers and predicting high-risk drivers will benefit the development of driver education programs and safety counter-measures. The goal of this study is twofold 1) to assess risk factors associated individual drivers and 2) to predict high-risk drivers. The 100-Car Naturalistic Driving Study data was used for methodology development. A negative binomial regression analysis indicated that driver age, extroversion of the NEO 5 personality trait, and critical incidents, as a measure of aggressive driving behavior, had significant impacts on crash and near-crash risk. For the second objective, drivers were classified into three risk groups based on crash and near-crash rate using a k-mean cluster method. Approximately 6% of drivers were identified as high-risk and 18% of driver as high/moderate risk drivers. A logistic regression model was developed to predict high risk drivers as well as high/moderate risk drivers. The predictive models showed high predicting power with area under the curve value of 0.917 and 0.9351 for the receiver operating characteristic curves. This study concluded that age, personality, and driving behavior is closely related to individual driving risk and aggressive driving is a powerful predictor for high risky drivers.

Supplemental Notes:

Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved

Monograph Accession #:

01501394

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Guo, Feng
Fang, Youjia

Pagination:

20p

Publication Date:

2011

Conference:

3rd International Conference on Road Safety and Simulation

Location: Indianapolis Indiana, United States
Date: 2011-9-14 to 2011-9-16
Sponsors: Purdue University; Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Candidate Terms:

Aggressive driving

Subject Areas:

Highways; Safety and Human Factors; I83: Accidents and the Human Factor

Files:

TRIS, TRB, ATRI

Created Date:

Jan 23 2014 11:45AM