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Title:Simulations of mixed use rail corridors: how infrastructure affects interactions among train types
Author(s):Sogin, Samuel
Advisor(s):Barkan, Christopher P.L.; Dick, C. Tyler
Department / Program:Civil & Environmental Eng
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Abstract:Freight traffic on North American railroads has undergone dramatic growth over the past several decades and this trend is projected to continue for the foreseeable future. Meanwhile, there is widespread interest in use of existing freight railway infrastructure to provide higher-speed passenger rail service. The growth in these two types of traffic, both alone, and particularly in combination, is increasingly straining the capacity of the rail network. In many locations, new railway infrastructure construction will expand capacity to accommodate this growth. In others, new efficiencies may be gained through advances in operational practices and investment in new traffic control technologies that can extract additional capacity from existing infrastructure. Railroads are highly capital intensive so careful consideration must be given to maximizing the benefit from these investment decisions. Defining railway line capacity is non-trivial. Characteristics of rail infrastructure such as the number of tracks, spacing and length of passing sidings on single track, the location of crossovers in double track, the traffic control system and other factors all affect the number, speed and performance of trains on a rail line. These interact with individual train operating characteristics and heterogeneity among train types to have major effects on throughput and service quality. These interactive effects can be quite complex and there is no fundamental understanding of many important relationships. Rail Traffic Controller (RTC), a railroad infrastructure and dispatching simulation software was used to conduct an extensive series of experiments investigating interrelationships between infrastructure configuration, traffic volume and mix, train speeds and delay. Design of experiments and non-linear regression statistical tools were used to maximize the information gained from the simulated data. Potential delay-based methods were investigated, as well as key highway capacity relationships that have railroad corollaries. A framework from failure analysis was adapted to evaluate train delay distributions. A number of factors have the potential to affect railway performance; this research identified the most important affecting railway capacity, train delay and reliability. It presents investigations and results that enable comparison of their relative importance and effects thereby enhancing our understanding of several fundamental relationships between infrastructure, train characteristics and operations that affect railway performance.
Issue Date:2014-01-16
Rights Information:Copyright 2013 Samuel Sogin
Date Available in IDEALS:2014-01-16
Date Deposited:2013-12

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