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研究生:蘇建誌
研究生(外文):Chien-Chih Su
論文名稱:台灣地區貨車安全風險分析之研究
論文名稱(外文):The Study of Freight Vehicle Safety Risks in Taiwan
指導教授:蔡明志蔡明志引用關係
指導教授(外文):Ming-Chih Tsai
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:運輸與倉儲營運系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:117
中文關鍵詞:量化風險評估肇事情境貨運車輛一般化線性交互模式
外文關鍵詞:Quantitative Risk AssessmentQRAAccident ScenarioFreight VehiclesGeneralized Linear Interactive ModelGLIM
相關次數:
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  • 收藏至我的研究室書目清單書目收藏:5
貨物運輸業對經濟發展扮演著重要角色,然而貨運車輛事故卻是在許多地方的生活威脅,因此,國內外以往從事貨車肇事風險分析研究者不在少數。綜觀以往的肇事研究相關文獻,在校估具有可靠度之風險分析模式時,常遭遇到三個問題:(1) 缺乏正確的風險描述:以往相關於交通肇事風險的研究中,大部分對於肇事風險之定義並不完整。一般而言,肇事風險被定義為肇事發生次數或發生率,少部分定義為肇事發生後果或發生嚴重度。完整的肇事風險的定義應為肇事發生與肇事發生規模之組合。(2) 缺乏量化肇事情境比較:交通肇事情境是描述肇事會在何種狀況下發生或肇事在何種狀況下發生之規模。這些交通肇事情境通常以人員、車輛、道路及環境因子所組成。傳統的相關研究大部分只針對上述一或兩項肇事因子進行肇事分析,因此肇事因子間的變動所產生的肇事情境並無法被完整地衡量出來。(3) 不相容的曝光量資訊:曝光量資訊對肇事風險分析之設計有莫大的影響,然而曝光量資訊的取得卻經常缺乏,或缺乏可靠性。以往相關肇事研究指出,由於連續曝光量資訊與類目型肇事資料並沒有相容性,此將使得肇事分析發生困難。因此對於肇事風險分析而言,曝光量資訊之問題需要被重新探討。
有鑑於這些問題,本研究旨在應用量化風險評估的概念,發展一量化貨車肇事風險情境分析模式,並對於國內營業貨車安全肇事風險進行衡量。研究結果顯示國內營業貨車的高肇事率與高肇事風險情境為大貨車行駛於非高速公路系統上;而高肇事規模情境則為包含成年駕駛人或在非高速公路系統上。此外,本研究之風險衡量結果亦可提供政府與業者進行安全管制措施,並提供保險業者之實際應用。
Freight transport plays an important role in economics development. However, the freight vehicle accidents are life threatening in many areas. So there have been innumerable studies on freight vehicle risk analysis. However, it is observed that attempts to calibrate reliable risk analysis models were hampered by three basic concerns: (1) Lack of accurate risk descriptions: previous accident studies were found to be devoid of complete risk implication. In many cases, risk was merely perceived as accident occurrences, rather than as the combination of accident occurrences and accident consequences by risk definition. (2) Lack of quantitative scenario comparisons: accident scenarios describe the circumstances where accidents occur. They are in general constituted by human, vehicle, road and weather factors. Previous studies on scenario analysis were mostly focused on one or two factors. Impacts of the varied scenarios have not been satisfactorily quantified. (3) Incompatible exposure information: exposure is vital but frequently unavailable for or incommensurate with the risk analysis designed. Previous studies indicated that incompatibility between continuous exposure information and categorical accident data, and the absence of comprehensive exposure information always obstructed the accident analysis. Exposure alternatives thus need to be explored.
Taking these concerns into account, this study aims to develop a quantitative risk model for scenario analysis of major freight vehicle accidents and conduct an empirical study of the issue in Taiwan. The empirical results indicate that accident rates and accident risks of freight vehicles in Taiwan were high in the scenarios involving trucks and non-freeway systems, while; accident consequences were severe in the scenarios involving mature drivers or non-freeway systems. The results could provide the government for safety regulations and the insurance for practices.
第一章 緒論 1
1.1 研究動機與目的 1
1.2 研究範圍與對象 2
1.3 研究內容 3
1.4 研究方法 4
1.5 研究流程 5
第二章 文獻回顧 7
2.1 貨運營運安全問題之相關文獻 7
2.1.1 國內貨物運輸安全環境 7
2.1.2 影響行車安全之因素 9
2.1.3 小結 16
2.2 肇事分析之相關文獻 17
2.2.1肇事趨勢分析之相關文獻 17
2.2.2 肇事因果分析之相關文獻 19
2.2.3小結 28
2.3 量化風險評估之相關回顧 29
2.3.1 風險的定義 29
2.3.2 風險管理的定位與內容 30
2.3.3 量化風險評估架構 35
2.3.4 風險管理在運輸業之應用 41
第三章 肇事風險模式建立----一般化線性模式(GLM) 45
3.1 一般化線性模式之適用性 45
3.2 一般化線性模式之理論基礎 47
3.2.1 一般化線性模式之數學模式 47
3.2.2 一般化線性模式之參數校估 50
3.2.3 一般化線性模式之逐步模式檢定 51
3.3 量化肇事風險情境模式之建立 54
3.3.1 量化肇事率與肇事規模模式描述 54
3.3.2 肇事風險情境描述 56
3.3.2 貨車肇事風險情境模式之建立 58
第四章 營業貨車肇事資料庫之建立 60
4.1 營業貨車肇事資料 60
4.2 貨車肇事資料處理 62
4.3 貨車肇事資料庫建立 68
第五章 營業貨車肇事風險衡量 72
5.1 營業貨車肇事率衡量 72
5.1.1 肇事率模式設定 72
5.1.2 肇事率模式之校估與檢定 73
5.2 營業貨車肇事規模衡量 77
5.2.1 肇事規模模式設定 77
5.2.2 肇事規模模式之校估與檢定 78
5.3 營業貨車肇事風險衡量 82
第六章 貨車肇事風險情境分析與應用 83
6.1 營業貨車肇事率情境分析 84
6.2 營業貨車肇事規模情境分析 86
6.3 營業貨車肇事風險情境分析 88
6.4 貨車肇事風險應用 89
第七章 結論與建議 94
7.1 結論 94
7.2 建議 95
參考文獻 97
附錄1 104
附錄2 106
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