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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/64784

    Title: 大專生機車偏差駕駛行為的影響因素 -個人與學校的多層次結構方程模式之應用;Influential Factors of College Motorcyclists Aberrant Driving Behavior- Application of Individual and School Multilevel Structural Equation Modeling
    Authors: 張玉旻;Chang,Yu-min
    Contributors: 土木工程學系
    Keywords: 多層次結構方程模式;偏差駕駛行為;風險感認;駕駛態度;校園機車安全風氣
    Date: 2014-07-22
    Issue Date: 2014-10-15 14:24:03 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 近年來,國內經濟發展促成機動車輛之快速成長,交通運輸需求日益漸增,進而延伸出許多道路交通安全的問題。根據交通部統計資料顯示,台灣地區登記之機車數量近十年內有逐漸增加之趨勢,且依據警政署統計通報可知,A1類交通事故肇事車種歷年主要以機踏車為主,約佔了將近50%,其可視為具有高肇事風險的車種類別。然而,又對於交通事故原因歸類,主要以汽(機、慢)車駕駛人過失為主。換言之,交通肇事的發生多來自於駕駛者本身因素所產生的駕駛偏差行為而導致。
    本研究以台灣地區共159所大專院校,以集群抽樣之方式,分為北中南東部挑選其中80所學校,共有2,639位大專生參與調查,旨以多層次結構方程模式(MSEM) 探討學校與學生間之駕駛者偏差駕駛行為的影響因素,包含:風險感認與駕駛態度,此方法論為目前較新穎之統計分析,其融合了HLM其樣本具有階層之關係,延伸自線性迴歸概念,以及SEM將具有共同性之觀察變數背後的因素潛在變數萃取而來。
    ;In recent years, due to the rapid growth of the demand for transportation, making numbers of cars and motorcycles growing, and resulting into many traffic safety problem. According to Minstry of Transportation and Communcations statistics shows that the number of motorcycles registered in Taiwan has gradually increased the trend the last decade. As stated by Ministry of the Interior, the motorcycles in A1 accident the number of events is the largest and accounts for nearly 50%. Therefore, the motorcycles can be regarded as the types of vehicles having a high accident risk. However, traffic accident was mainly due to driver faults. In other words the traffic accident occurred from the driver factors about aberrant driving behavior.
    This study conducted a survey on 2,639 students from a total of 159 universities from 80 universities in Taiwan. The sample of clusters divided into North, Middle, South, Eastern, and used multilevel structural equation modeling (MSEM) to analysis data. Explore the influencing factors of drivers’ aberrant driving behavior (ADB) between schools and students including risk perceptions and attitudes. MSEM is the currently newest statistical analysis, which combines hierarchical liner model (HLM) has related hierarchical sample data and extended from the concept of linear regression, and structural equation modeling (SEM) has extracted from the commonality of observed variable factors behind the latent variable.
    The results show that aberrant driving behaviors, risk perceptions, and attitudes, are correlated with each other; in both individual and group level, risk perceptions and attitudes have a significant negative influence on ABD. It namely the extents of students’ drivers and each school ethos to have a higher risk perceptions and attitudes of a large traffic safety, which means that frequency of aberrant driving behavior to become smaller. According the results, this study proposes some discussions about safety policy and recommendations of the research issues for the future.
    Appears in Collections:[土木工程研究所] 博碩士論文

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