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Title:Probabilistic risk assessment of railroad train adjacent track accidents
Author(s):Lin, Chen-Yu
Director of Research:Barkan, Christopher P.L.
Doctoral Committee Chair(s):Barkan, Christopher P.L.
Doctoral Committee Member(s):Work, Daniel B.; Mohaghegh, Zahra; Saat, Rapik
Department / Program:Civil & Environmental Eng
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Railroad
Safety
Risk Analysis
Shared-use Rail Corridors
Abstract:Growth in passenger traffic on rail corridors shared with freight trains, and expanded rail transport of hazardous materials have both increased the imperative to understand the factors affecting railway transportation safety and risk. A source of risk that has received relatively little attention are railroad train accidents that may cause collisions with trains operating on adjacent tracks. These adjacent track accidents (ATAs) occur when one train derails in multiple-track territory and its equipment or lading intrudes onto an adjacent track and strikes, or is struck by, another train operating on that track. This dissertation develops data and a formal analytical framework to evaluate the risk of ATAs. Using Probabilistic Risk Assessment methodologies such as Fault Tree Analysis, an ATA is divided into its three principal constituent events: the initial train derailment, the intrusion of derailed rail vehicles onto an adjacent track, and the presence of another train on that track that may collide with the intruding equipment. The probability of each event is assessed, the factors affecting those probabilities are identified, their effects are investigated and discussed, and a formal qualitative and quantitative framework is developed into a comprehensive probability assessment model for ATA occurrences. Particular attention is given to passenger trains because of their expanded operation on shared-use rail corridors (SRCs) with freight train traffic and consequent exposure to ATA risk. Passenger train accidents are analyzed and the important factors contributing to their frequency and consequences investigated. Derailments and collisions were analyzed to identify and quantify accident causes that have higher frequency and/or severity in terms of casualties to onboard passengers and crew. Factors affecting train intrusion probability including track center spacing, track alignment, train speed, adjacent structures, elevation differential, and presence of intrusion barriers or containment systems are identified and their effects on intrusion probability investigated. These factors serve as important elements in developing a comprehensive ATA probability assessment model. A semi-quantitative model is developed as a screening-level risk assessment tool for ATAs, accounting for factors affecting the probabilities of the initial train derailment, the intrusion of derailed vehicles onto an adjacent track, and the presence of another train on the adjacent track. A quantitative model is developed to estimate the probability of train presence on an adjacent track when and where a train intrusion occurs, which is affected by the frequency and operational characteristics of train traffic on both lines. This model also estimates the probability of an adjacent track collision based on traffic control, intrusion prevention or warning systems, point of derailment, train braking capability, and other factors. The ATA probability assessment framework results in the development of the Adjacent Track Accident Probability Assessment Model (ATAPAM). The ATAPAM provides a step-by-step procedure to assess the probability of ATAs in both quantitative and qualitative forms. The probability of an ATA on a multiple-track segment is evaluated with a qualitative risk indicator showing additional intrusion risk. A case study of the application of ATAPAM on a hypothetical SRC is presented. The ATAPAM can be used as a tool in a decision analysis framework in which risk mitigation strategies for ATAs can be evaluated based on their effectiveness, implementation cost, and constraints such as budget and other resources.
Issue Date:2019-04-17
Type:Text
URI:http://hdl.handle.net/2142/105213
Rights Information:Copyright 2019 Chen-Yu Lin
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05


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