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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/95924


    題名: 鐵路機構可歸責於司機員之行車事故事件原因分析 (以臺鐵公司為例);Analysis of the Causes of Train Accidents Attributable to Train Operators (A Case Study of the Taiwan Railway Corporation)
    作者: 林育昶;Lin, Yu-Chang
    貢獻者: 土木系營建管理碩士在職專班
    關鍵詞: 鐵路事故事件;交叉分析;SPSS;pearson相關分析;pearson卡方檢定;Railway accidents;Cross-analysis;SPSS;Pearson correlation analysis;Pearson chi-square test
    日期: 2024-07-10
    上傳時間: 2024-10-09 17:24:23 (UTC+8)
    出版者: 國立中央大學
    摘要: 臺灣鐵路自清領時期建設路線僅100多公里,歷經日治時期規劃及建置東、西部鐵路幹線,並於民國109年完成全線鐵路電氣化,而臺灣鐵路管理局也為符合時代潮流及解決內部積累已久問題,於113年1月1日正式掛牌為國營臺灣鐵路股份有限公司,長達136年的臺鐵局時代正式邁入歷史。
    回顧近年鐵路運輸重大事故案例,2018年普悠瑪列車出軌事故及2021年太魯閣號列車出軌事故均造成重大生命財產損失。綜觀我國針對臺灣鐵路進行之研究,多數以該鐵路機構之服務、營運、運量、行銷、文化保存及遊憩等主題進行探討,少數對鐵路之事故因子、風險等級及單一事件分析或鐵路犯罪預防等研究。
    為瞭解臺鐵公司事故事件發生原因,本研究蒐集該公司自2012年至2023年8月間發生可歸責於司機員之鐵路事故事件資料,除就特定因子中2連續變項進行相關係數分析外,亦就各事故事件之車種、時間、年月、路線、轄區、發生原因、導致結果及改進事項等8項因子進行個別與交叉分析。其中單因子分析結果以敘述性統計方式呈現;兩因子間交叉分析則利用統計軟體SPSS執行卡方檢定,並就分析結果觀察是否達到顯著,若為顯著則進ㄧ步查看兩變項間之關聯性強度。
    本研究期能藉由前揭各變項單因子或兩因子之分析成果,提供鐵路機構做後續營運參考,並據以制定精進措施,減少鐵路事故事件發生率,提升鐵路運輸安全。
    ;During the Qing Dynasty, Taiwan Railways had only over 100 kilometers of constructed lines. Through planning and construction of the eastern and western main lines during the Japanese colonial period, and the completion of full railway electrification in 2020 (Republic of China year 109), the Taiwan Railways Administration adapted to modern trends and addressed long-standing internal issues. On January 1, 2024 (Republic of China year 113), it was officially restructured into the state-owned Taiwan Railway Company Limited, marking the end of the 136-year era of the Taiwan Railways Administration.

    Reviewing recent major railway transportation accidents, the Puyuma Express derailment in 2018 and the Taroko Express derailment in 2021 both resulted in significant loss of life and property. Research on Taiwan Railways has mostly focused on the service, operations, traffic volume, marketing, cultural preservation, and recreation aspects of the railway institution. Few studies have delved into accident factors, risk levels, individual event analyses, or railway crime prevention.

    To understand the causes of accidents involving the Taiwan Railway Company, this study collected data on railway accidents attributable to drivers from 2012 to August 2023. Besides conducting Pearson correlation analysis on two continuous variables of specific factors, the study also individually or cross-analyzed eight factors related to each accident: train type, time, year and month, route, jurisdiction, cause of occurrence, resulting outcome, and improvement measures. Univariate analysis results are presented using descriptive statistics, while bivariate cross-analysis employed Pearson’s chi-square test with SPSS statistical software to observe if the results were significant. If significant, the strength of the correlation between the two variables was further examined.

    This study aims to provide Taiwan Railway institutions with operational reference through the analysis results of these variables, helping to formulate improvement measures to reduce the incidence of railway accidents and enhance railway transportation safety.
    顯示於類別:[營建管理研究所碩士在職專班] 博碩士論文

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