鐵路高風險駕駛行為與路段辨識模組開發

Development of High-Risk Driving Behavior and Section Identification Modules for Railway System

陳昱甫(Yu-Fu Chen)

指導教授 ： 賴勇成

國立臺灣大學/工學院/土木工程學研究所/碩士(2020年)

https://doi.org/10.6342/NTU202001876

摘要

普悠瑪事故發生後，鐵路安全的議題再次浮上檯面，其中風險評估對鐵路安全至關重要。本研究提出了一個自動化程序，讀取列車自動保護系統（Automatic Train Protection，ATP）之行車記錄以辨識六種高風險駕駛行為。所提出的模組不僅能應用於司機員安全表現評估，亦能針對高風險行為發生之路段進行分析。除此之外，更提出一高風險駕駛行為綜合風險指標，整合六種高風險行為表現以分析並比較不同司機員與路段之間的風險高低程度。在案例分析中，本研究利用實際的行車資料，分別對司機員與路段進行分析，結果顯示若以高風險駕駛行為而言，高達74%的總體風險來自於20%的司機員；又以路段而言，高達80%的總體風險來自於15%的高風險路段。本研究的模組成功的根據ATP行車記錄辨識高風險駕駛以及路段，可便於營運單位對症下藥，有效地提升鐵路系統安全性。

關鍵字

鐵路運輸 ； 鐵路安全 ； 自動列車保護 ； 駕駛行為 ； 司機員評估 ； 路段評估 ； 風險指標

並列摘要

Risk assessment is an important process for railway safety. This research proposes an automatic process to access operational record from Automatic Train Protection (ATP) system, and identifies six high-risk driving behaviors. With the integrated risk index for driving behaviors (IRIDB), the proposed modules can successfully identify high-risk drivers and sections in the railway system. Empirical study demonstrates that 20% of high-risk drivers contribute to 74% of the total risk, while 15% of high-risk sections contribute to 80% of the total risk. The proposed modules identify the drivers and sections with high risk to enable the operators of railway systems to take countermeasures, thereby enabling them to efficiently improve the safety of railway systems.

並列關鍵字

Rail Transportation ； Railway Safety ； Automatic Train Protection ； Driving Behavior ； Driver Assessment ； Section Assessment ； Risk Index

參考文獻

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