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Alcohol-impaired motorcycle crashes in Hawaii, 1986 to 1995 : An alysis Kim, Karl ; Kim, Sungyop ; Yamashita, Eric

By: Kim, KarlContributor(s): Kim, Sungyop | Yamashita, EricPublication details: Transportation Research Record, 2000Description: nr 1734, s. 77-85Subject(s): USA | Drunken driving | Accident | Motorcyclist | Statistical analysis | Demography | Crash helmet | Driving licence | Time | Layout | Injury | | 842Bibl.nr: VTI P8167:1734Location: Abstract: The purpose of this research is to review and describe data on the nature and extent of alcohol-impaired motorcycle-riding crashes in Hawaii. Using comprehensive police crash data, the differences between impaired and nonimpaired riders involved in crashes, in terms of various demographic characteristics, helmet use, license status, roadway environments, and injury outcomes, are described. In addition to various demographic and behavioral factors associated with impaired rider crashes, clear temporal patterns also have been detected. After summarizing these effects, a logistic regression model is built to explain the likelihood of an impaired motorcycle crash as a function of rider characteristics as well as environmental and temporal factors. In addition to age-specific determinants of impaired crash involvement, time factors such as weekends and nighttime, and licensing (out-of-state or no licenses) are strongly associated with impaired rider crashes. These findings could be used to enhance enforcement efforts as well as public information and safety education programs.
Item type: Reports, conferences, monographs
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The purpose of this research is to review and describe data on the nature and extent of alcohol-impaired motorcycle-riding crashes in Hawaii. Using comprehensive police crash data, the differences between impaired and nonimpaired riders involved in crashes, in terms of various demographic characteristics, helmet use, license status, roadway environments, and injury outcomes, are described. In addition to various demographic and behavioral factors associated with impaired rider crashes, clear temporal patterns also have been detected. After summarizing these effects, a logistic regression model is built to explain the likelihood of an impaired motorcycle crash as a function of rider characteristics as well as environmental and temporal factors. In addition to age-specific determinants of impaired crash involvement, time factors such as weekends and nighttime, and licensing (out-of-state or no licenses) are strongly associated with impaired rider crashes. These findings could be used to enhance enforcement efforts as well as public information and safety education programs.

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