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dc.contributorVirginia Polytechnic Institute and State University. Transportation Instituteen
dc.contributorNational Surface Transportation Safety Center for Excellenceen
dc.contributor.authorSoccolich, Susan A.en
dc.contributor.authorHickman, Jeffrey S.en
dc.contributor.authorHanowski, Richard J.en
dc.description.abstractThe current report investigated the 'high-risk' driver concept, and predictors associated with group membership, in a sample of 200 CMV drivers using naturalistic data from the Drowsy Driver Warning System Field Operational Test and the Naturalistic Truck Driving Study. A cluster analysis revealed three distinct groups of drivers (safe, average, and risky) based on the rate of safety-critical events per mile traveled. The risky group accounted for 50.3% of the total safety-critical events, but only 7.1% of the total miles traveled. Various anthropometric and demographic variables were found to have an association to group membership; however, these relationships were weak (mainly due to the small sample size). The current study found support for the high-risk driver concept; future research should focus on identifying risky drivers so that targeted safety management techniques can be used to improve driving behavior. -- Report website.en
dc.description.statementofresponsibilitySusan Soccolich, Jeffrey Hickman and Richard Hanowskien
dc.format.extentix, 29 pagesen
dc.publisherVirginia Tech. Virginia Tech Transportation Instituteen
dc.rightsCreative Commons CC0 1.0 Universal Public Domain Dedicationen
dc.subject.lccTL230.3 .S63 2011eben
dc.subject.lcshTruck drivers -- Rating ofen
dc.subject.lcshTruck driving -- Evaluationen
dc.subject.lcshTruck accidents -- Preventionen
dc.subject.lcshCommercial vehicle industry -- Accidents -- Preventionen
dc.titleIdentifying high-risk commercial truck drivers using a naturalistic approachen

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Creative Commons CC0 1.0 Universal Public Domain Dedication
License: Creative Commons CC0 1.0 Universal Public Domain Dedication