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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Profile of Short Line Railroads in High Grain Production States</title>
      <link>https://trid.trb.org/View/1567476</link>
      <description><![CDATA[The Central Plains region leads the nation in many areas of agricultural activity. In terms of total production of corn, wheat, sorghum, and soybeans, Iowa leads the nation followed by Illinois, Nebraska, Minnesota, and Kansas. Because many locations in these states are remote from markets and processing centers they are somewhat dependent on railroads for transport of their grain. After deregulation in 1980 the Class I railroads adopted a cost reduction strategy that involved the sale or lease of their branch lines to short line railroads. Today, in the eight leading states in wheat production, short lines collectively account for about one-third of the total track miles in that region. These short lines provide rail service to many rural shippers whose access to rail service might otherwise have been lost. Abandonment has several potential negative effects on rural areas such as lower grain prices received by farmers, higher transportation costs and reduced profi ts for rail shippers, loss of market options for rural shippers, foreclosed economic development options in rural communities, and higher road maintenance and reconstruction costs. This paper analyzes how changes in the grain logistics system have affected short line railroad viability. For example, how have Class I shuttle trains impacted the role of short lines in the grain logistics system? Alternatively, how has the development of multi-short line holding companies affected the competiveness of short lines relative to motor carriers? Short lines play a critical role in originating and terminating grain transported by rail and promoting economic development along these lines. Particularly important is providing rail service to rural America and its link to the Class I rail network. In the decade following the passage of the Staggers Rail Act in 1980, more than 250 short lines were formed, adding to the approximately 220 short lines that existed as of 1980 (Llorens and Richardson 2014). Today, 562 short lines are operating (AAR 2016).]]></description>
      <pubDate>Tue, 20 Nov 2018 10:11:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1567476</guid>
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      <title>PTC Test Facility Assessment and Laboratory Development: Phase I</title>
      <link>https://trid.trb.org/View/1508679</link>
      <description><![CDATA[From May 1, 2016, through August 31, 2016, the Transportation Technology Center (TTC) assessed Class I Positive Train Control (PTC) test facilities, and held discussions with commuter and short line railroad representatives to recommend a project approach to implement an industry test laboratory for Interoperable Train Control (ITC) at TTC.]]></description>
      <pubDate>Thu, 10 May 2018 17:45:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1508679</guid>
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      <title>Development of Hybrid Cost Functions From Engineering and Statistical Techniques: The Case of Rail - Phase II Final Report</title>
      <link>https://trid.trb.org/View/1497866</link>
      <description><![CDATA[Cost analysis is important in every transportation industry, to the firms or agencies which provide service, to regulatory bodies, and to public policy makers. In the past, railroad cost analyses have been of two types: 1) statistical analyses of aggregate cross-section data from a variety of firms, or 2) very detailed operations-oriented studies. The premise of the work reported here is that a "hybrid" approach, using both economic theory and statistical methods on the one hand, and engineering analysis of operations on the other, can produce superior results. This report covers Phase II of the project, which focused on analysis of a major class I railroad. A short-run variable cost function was estimated econometrically, and used as a basis for deriving the associated long-run function. The authors also developed a simple, but relatively accurate, network model to estimate operating costs. This model may be used to estimate origin-destination specific marginal operating costs. Econometric analysis of the output from the model leads to a theoretically justifiable equation for predicting marginal operating costs, and their sensitivity to changes in flows and input prices.]]></description>
      <pubDate>Sun, 11 Feb 2018 18:33:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1497866</guid>
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      <title>A Demonstration Project for Locomotive Engineer Training</title>
      <link>https://trid.trb.org/View/1493768</link>
      <description><![CDATA[This report presents the findings of the joint venture demonstration training project conducted by the Louisville and Nashville (L&N) Railroad and the Brotherhood of Locomotive Engineers. Volume I contains a survey of the literature, a job task inventory and a set of guidelines for instructional systems design. The report also describes the training practices, techniques and materials of formal Locomotive Engineer Training (L.E.T.) programs at six class-one railroads. Volume II presents suggested short term additions to the L&N's L.E.T. program; three model L.E.T. programs of low, middle and high costs (implementation and operation) and a cost-benefit analysis plan for the models.]]></description>
      <pubDate>Tue, 23 Jan 2018 15:19:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1493768</guid>
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      <title>Final Standards, Classification, and Designation of Lines of Class I Railroads in the United States Volume I</title>
      <link>https://trid.trb.org/View/1470028</link>
      <description><![CDATA[The Railroad Revitalization and Regulatory Reform Act of 1976 ("the Act") was enacted to avert the continuing deterioration financially and physically of railroads by revitalizing the industry within a private sector framework. Title V of the Act establishes a short-term program of financial assistance for railroads (Sections 505 and 511) and requires the Secretary of Transportation ("the Secretary") to conduct two studies. The first study -- required under Section 503 and the subject of this report -- is intended to develop a framework for classifying the lines of U.S. Class I railroads into categories of mainlines and branchlines and to designate each line segment of the Class I system into its appropriate category within that framework. The second study, a study of rail industry capital needs over the period 1976-1985, is required under Section 504 of the Act. It is due for release at a later date. This final report under Section 503 completes a statutorily-prescribed process with three principal steps. This Report is the third step in the process. Volume I is being published now and Volume II  will be issued shortly. The contents of this Volume 1 final report are presented in the following chapters: (1) Introduction; (2) Analysis and Response to the Principal Public Commentary on the Preliminary Report; (3) Final Standards for the Classification of Rail Lines; and (4) Final Classification of the Rail System and Designation of Rail Lines.]]></description>
      <pubDate>Wed, 21 Jun 2017 12:22:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/1470028</guid>
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      <title>Exploring the predictive potential of artificial neural networks in conjunction with DEA in railroad performance modeling</title>
      <link>https://trid.trb.org/View/1439973</link>
      <description><![CDATA[This paper is an investigation into the feasibility of using artificial neural networks (ANN) in conjunction with data envelopment analysis (DEA) for performance measurement and prediction modeling of Class I railroads in the United States. For this exploratory study, DEA-ANN are combined into a two-stage modeling approach. While it is frequently used as a benchmarking tool, DEA lacks predictive capabilities. However, ANN has strong nonlinear mapping and adaptive prediction functionality. In this study, the advantages of combining these complementary methods into an integrated performance measurement and prediction model are explored. For this combined approach, a Charnes, Cooper and Rhodes (CCR) DEA model is used to evaluate the efficiency of each decision making unit (DMU) and to capture the efficiency trend of each railroad. Based upon those DEA results, the follow-on backpropagation neural network (BPNN) model predicts an efficiency score and target output for each DMU. This is a new attempt to extend the BPNN model for purposes of best performance prediction. The resulting framework is an effective benchmarking and decision support system which adds adaptive prediction capabilities to current benchmarking practices.]]></description>
      <pubDate>Tue, 24 Jan 2017 15:15:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/1439973</guid>
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    <item>
      <title>Muscular Metrics</title>
      <link>https://trid.trb.org/View/1429447</link>
      <description><![CDATA[In this article, the author explores the successful operations of CN, which continues to be one of North America's best run railroads despite challenging economic times. The article highlights CN's investments in infrastructure, equipment and customer service; the company's financial outlook; and the leadership responsible for the company's success.]]></description>
      <pubDate>Mon, 21 Nov 2016 13:23:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1429447</guid>
    </item>
    <item>
      <title>There is life after coal</title>
      <link>https://trid.trb.org/View/1423251</link>
      <description><![CDATA[As a drop in coal traffic coincide with a cyclical downturn in global freight, Class I railroads are looking for new sources of business. However, this article demonstrates that long-term prospects remain good. In fact, record financial results in terms of both earnings and return on investment were reported by the Class I's collectively in the last full year, in addition to producing the best safety numbers ever.]]></description>
      <pubDate>Fri, 23 Sep 2016 11:17:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1423251</guid>
    </item>
    <item>
      <title>Lumbering Along</title>
      <link>https://trid.trb.org/View/1256634</link>
      <description><![CDATA[Lumber and paper generate the majority of the Class I forest products business. The reduction in housing starts along with the declining number of newspapers and magazines in 2009 had a negative impact on products volume and revenue gains and it appears now that things are taking a positive turn. The housing market is improving and lumber exports to Asia are rising to accommodate home and commercial construction markets. Consequently, several Class Is have reported that forest product volume, as well as revenue gains, have increased. As the economy recovers, there is growing optimism that the demand for lumber and plywood for the housing market will continue to improve. However, although forest products volume will likely benefit from a healthier housing market, it is uncertain that there will be enough housing starts by year's end to meet Class Is' expectations for a major increase in lumber-driven business. However, paper traffic figures are expected to remain sluggish. The major concerns are the strong competition faced by those in the industry and competition among the transportation suppliers to the paper mills. Graphic paper has struggled and will probably continue to struggle due to the electronic age and the reduced demand for newspapers. Many closed lumber mills will need to reopen, expand operations, and develop a large enough market to warrant rail shipment. Overall there continues to be optimism about the industry's prospects for providing packaging materials for consumer goods, as well as lumber and plywood for the improving housing market.]]></description>
      <pubDate>Tue, 23 Jul 2013 11:39:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1256634</guid>
    </item>
    <item>
      <title>Productivity Improvements in the U.S. Rail Freight Industry, 1980-2010</title>
      <link>https://trid.trb.org/View/1253245</link>
      <description><![CDATA[Between 1980 and 2008, extensive productivity improvements and changes in traffic mix allowed railroads to become more profitable despite declining prices and stronger competition from motor carriers. These productivity improvements enabled the Class I railroads to halve their real costs per ton-mile, even though costs for fuel and other resources rose faster than inflation. Productivity improvements were greatest for bulk traffic moving in unit trains, containers moving in double-stack trains, and high-volume shipments moving long-distances in specialized equipment. While the rail industry indeed achieved tremendous improvements in productivity following passage of the Staggers Act in 1980, it is incorrect to point to deregulation as the primary reason for these gains. Other factors that were even more critical to productivity growth included technological advances, new labor agreements,improved management, and public policy responses to the Northeast Rail Crisis.]]></description>
      <pubDate>Fri, 28 Jun 2013 14:05:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1253245</guid>
    </item>
    <item>
      <title>PTC: A Crucial Year for Class Is</title>
      <link>https://trid.trb.org/View/1247794</link>
      <description><![CDATA[There is still a lot of work that needs to be accomplished by U.S. Class I railroads in order to implement positive train control (PTC) systems by the federally mandated deadline of Dec. 31, 2015. There is one thing that executives who head PTC implementation are fairly certain won't be finished by then: that is getting all systems in place and functioning as intended, and ensuring that they are fully interoperable. From an industry perspective, 2015 is really not achievable. Class I railroads are doing as much as they can to try to achieve meeting the date. The primary reasons for this delay are considered to be significant technical and programmatic issues that are associated with the design, development, testing, integration and deployment of PTC systems. Given the current state of development and availability of the required hardware and software, along with deployment considerations, most railroads will likely not be able to complete full implementation of PTC by Dec. 31, 2015. The technical obstacles cited by railroads include the availability of communications spectrum; radios; design specifications; back office servers and dispatch systems; track database verifications; installation engineering; and system reliability. Programmatic issues include budgeting and contracting, and stakeholder availability. PTC isn't one complete system, it's a system of systems. In addition, PTC is a complex and developing technology, not an off-the-shelf system or software. Moreover, because so much rail traffic is interchanged, all PTC systems must be interoperable, and achieving interoperability is a huge task.]]></description>
      <pubDate>Wed, 17 Apr 2013 08:55:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1247794</guid>
    </item>
    <item>
      <title>A Refined Crude Strategy</title>
      <link>https://trid.trb.org/View/1247792</link>
      <description><![CDATA[This article describes how Canadian Pacific (CP) is riding the wave of North American oil producers' because these producers are increasingly relying on rail to transport their crude oil to the U.S. Gulf Coast and Northeast refineries. In order to get a sense of how quickly the crude-by-rail business has grown for the Class I, consider this: CP moved 500 carloads of crude oil in 2009, 13,000 in 2011 and more than 53,000 in 2012. In January, the railroad reached a 70,000 annual carload run rate for crude oil, a rate met much earlier than expected. With each car holding about 650 barrels, that's a lot of crude. The Class I is expecting the growth to continue throughout this year. Beyond 2013, the railway has a line of sight that is two to three times the present volume going forward. This is a very positive story for the company. CP executives reported during the Class I's fourth-quarter 2012 earnings teleconference that crude by rail represents the Class I's strongest opportunity for traffic and revenue growth.]]></description>
      <pubDate>Wed, 17 Apr 2013 08:55:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1247792</guid>
    </item>
    <item>
      <title>Change Agent for the Small-road Crowd</title>
      <link>https://trid.trb.org/View/1245871</link>
      <description><![CDATA[The article describes how the short-line association has helped hundreds of small U.S. railroads adapt to business and regulatory changes for the past 100 years. In the early 1800s, all U.S. railroads were short lines that were formed in many cities to move freight and passengers. By the early 1900s, short lines remained an important economic factor in their local communities, but not a strategic component of the larger rail systems that developed nationwide. As highways were built, trucking competition increased and manufacturing patterns changed from the 1930s to 1970s, the number of U.S. short lines declined. After the Staggers Act was enacted in 1980, Class I railroads began to market or sell unproductive branch lines to short-line operators, which forged a rebirth of small railroads. Today, there are more than 550 U.S. short lines and regionals, which is more than peak number before the decline.]]></description>
      <pubDate>Mon, 18 Mar 2013 09:11:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1245871</guid>
    </item>
    <item>
      <title>Optimal Clustering of Railroad Track Maintenance Jobs</title>
      <link>https://trid.trb.org/View/1240665</link>
      <description><![CDATA[Freight railroads in North America spend billions of dollars every year on track maintenance. Track maintenance activities not only incur high capital costs, but also have a significant impact on railroad safety and operational efficiency. Job clustering is an important part of railroad track maintenance planning. It focuses on clustering track maintenance jobs into projects, so that the projects can be assigned to the production teams and scheduled in the planning horizon. The real world instances of job clustering problem usually have a very large scale, involving thousands of jobs per year. Various difficult side constraints such as mutual exclusion constraints and rounding constraints further increase the difficulty in solving the problem. Therefore, the railroad mainly relies on the experience and knowledge of experts to solve this problem manually. In this paper, the authors develop a mixed-integer mathematical programming model in the form of vehicle routing problem with side constraints, and propose a set of integrated heuristic algorithms to solve the problem. The proposed model and algorithms have been adopted by a Class-I railroad to help their practical operations for a few years.]]></description>
      <pubDate>Thu, 14 Mar 2013 12:46:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/1240665</guid>
    </item>
    <item>
      <title>A Vision Quest for KCS</title>
      <link>https://trid.trb.org/View/1223086</link>
      <description><![CDATA[This article describes how Kansas City Southern (KCS) leaders have made a number of important decisions that helped the Class I survive and thrive over the past 125 years. The article shows how there would be no “GO” in KCS development as a Class I and international intermodal player if the company’s leaders, past and present, hadn’t made bold moves or taken several risks along the way. The KCS Class I marks its 125th anniversary this year and the current railroad’s leadership team is acknowledging the past developments that helped forge the railroad today. The leaders are also discerning the opportunities that lie ahead for what is now an established north-south international railroad. Prospects abound in Mexico and are plentiful in the United States, a nation where KCS is thriving among predominantly large east-west railroads.]]></description>
      <pubDate>Tue, 27 Nov 2012 09:44:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/1223086</guid>
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