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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>A Study of Optimization of Dynamic Freight Train Diagrams Based on Market-Orientation</title>
      <link>https://trid.trb.org/View/2407921</link>
      <description><![CDATA[The dynamic freight train diagram is the key link to realize the whole-process integrated transportation of goods and the key to realize the “According to the Timetable”. This paper studies the optimization of freight train diagram based on the basic diagram for dynamic route selection with market orientation as the core. Firstly, considering the quality of freight service and the satisfaction of cargo owners, taking the minimum transportation time consumption of each freight train as the optimization goal, starting from the characteristics of dynamic traffic flow, considering the connection time of traffic flow with the train at the station and the arrival period of the loaded goods, the dynamic route selection optimization model based on the basic diagram of the train diagram is established, and the solution strategy of the improved particle swarm algorithm based on binary coding is designed. Finally, a small road network case is constructed to verify the feasibility of the model and algorithm.]]></description>
      <pubDate>Tue, 18 Mar 2025 15:48:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407921</guid>
    </item>
    <item>
      <title>Intermodal Transportation and Optimum Depot Selection</title>
      <link>https://trid.trb.org/View/2148830</link>
      <description><![CDATA[Intermodal transportation activities have seen fundamental changes in technology, operation, management and organization in the past three decades. A transportation carrier delivers products to its clients using containers in various transportation modes such as railcars and trucks. After delivery and unloading by the customers, the empty containers are shipped back to a depot or warehouse designated by the carrier for subsequent shipment to other customers. After loading the new customer's products, the containers are transported directly to their destinations or through some intermediate depots. Under this type of logistic networks, containers spend a significant amount of time in empty movements. For example, in the US rail system it is estimated that a railcar is empty during 40% of its average car cycle. The importance of empty container movement in carriers cost structure has inspired a number of studies directed at managing empty container fleets for railroad, liner shipping operators, and truckers. A fundamental question these studies address is: Given an inland logistic network, how should the carrier dispatch empty containers to meet shippers' demand, to relocate empty containers among depots and warehouses, and to lease on/off containers in preparation for future demand. While these studies have achieved some degree of success in reducing empty container related operational costs, a more fundamental and strategic question is how to design the underlying logistics network; namely, how to determine the location and capacity of depots and warehouses in order to achieve a broader and more significant cost reduction. This paper addresses the above question by developing a decision support tool to assist transportation carriers in determining their inland logistic network, the location and the capacity of each depot.]]></description>
      <pubDate>Wed, 15 Nov 2023 09:19:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2148830</guid>
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    <item>
      <title>Freight transport using additional railcars attached to intercity passenger trains with transshipment and railcar circulation: Tabu-search-based Lagrangian heuristic</title>
      <link>https://trid.trb.org/View/2254989</link>
      <description><![CDATA[Developing under-exploited passenger rail networks is emerging as an alternative for freight transport. In light of this, the authors investigate a long-haul freight mode in which additional railcars for carrying shipments are attached to passenger trains, and the shipments can transfer among the trains at intermediate stops. To coordinate space–time schedules of shipments and railcars, they construct a two-level space–time network: one level captures the departure, transshipment, and arrival of shipments; whereas the other level depicts the holding, reshuffling, and repositioning of railcars. Incorporating variables of space–time arc selection and constraints concerning shipment (un-) loading, locomotive pulling capacity, supply–demand coupling, and flow conservation on networks, a binary integer model is established to minimize the total travel cost of both railcars and shipments. The primal problem is decomposed using Lagrangian relaxation. Lagrangian multipliers and dual bounds are approximated by solving the Lagrangian dual. They devise a primal heuristic based on tabu search for expediting high-quality solutions. Numerical experiments demonstrate computational performance and managerial insights.]]></description>
      <pubDate>Fri, 29 Sep 2023 13:38:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2254989</guid>
    </item>
    <item>
      <title>Study of Suburban Railway and the Usage of Single-Car Trains for Solving Railway Management Problems in China</title>
      <link>https://trid.trb.org/View/1728606</link>
      <description><![CDATA[The suburban railway system is an essential component of the rail transit system. However, the construction of a suburban railway system in China has been suffering from notably slow development and low operation revenue. Under these circumstances, the single-car train system, with lots of operation experience in many developed countries as well as the advantages of flexible marshalling easy maintenance, etc., gives rise to a possible solution to the problems aforementioned. The authors start by clarifying the definition of the suburban railway system and the single-car train system. Then the authors summarize the history of the suburban railway system in China and analyze the problems in existing suburban railways. The authors then introduce examples as well as advanced experiences in suburban railway systems abroad. After that, the authors analyze the feasibility of using the single-car train system in China’s suburban railway lines and potential advantages. Lastly, the authors give suggestions on China’s transportation infrastructure.]]></description>
      <pubDate>Fri, 28 Aug 2020 17:40:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/1728606</guid>
    </item>
    <item>
      <title>Quantitative Analysis of the Derailment Characteristics of Loaded and Empty Unit Trains</title>
      <link>https://trid.trb.org/View/1493148</link>
      <description><![CDATA[Operation of unit trains has grown substantially over the past half century owing to their ability to provide economic and efficient transportation of bulk products. Although various aspects of train safety have been studied, there has been limited research examining the effect of train loading conditions on derailment occurrence, cause and severity. An algorithm was developed to identify derailments of loaded and empty unit trains on mainlines and sidings recorded in the Federal Railroad Administration database. A dataset of these accidents for the 15-year period of 2001–2015 was developed and analyzed. The frequency of derailments for both loaded and empty unit trains declined by more than 50%. The average number of cars derailed per accident fluctuated for both loading conditions, but showed no particular trend. Approximately five times more loaded unit train derailments were recorded in the database than empty unit trains, but in the absence of specific unit train traffic data, inferences about rates are not possible. Loaded unit trains were more than four times heavier than empty unit trains and loaded train derailments tended to involve more cars than empty trains. The distribution of derailment causes differed for loaded and empty unit trains. Loaded trains most frequently derailed because of broken rails and welds, while the leading cause of empty train derailments was obstructions, in particular severe weather. Over 90% of the derailments of loaded and empty unit trains considered in this study occurred on mainline tracks, and the distribution of causes differed between mainline and siding tracks.]]></description>
      <pubDate>Thu, 10 May 2018 09:21:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1493148</guid>
    </item>
    <item>
      <title>The Short-term Car Flow Planning Model in Rail Freight Company – Case Study</title>
      <link>https://trid.trb.org/View/1370536</link>
      <description><![CDATA[With the promotion of the environmentally friendly transportation modes (the European Commission supports the freight transport operations in the rail sector), an increase in the diversification of the demand is observed. While most rail freight companies tend to apply fixed schedules, this approach is not effective. It turns out to be ineffective due to the need to meet the customer's specific requirements. The purpose of this paper is to present a case study of empty wagon flow planning over a medium term horizon and to discuss the opportunities of improvement of this plan by discrete optimization. In order to increase the utilization and availability of wagons, the planning procedure with a rolling horizon has to be implemented. Unfortunately, since the plan has to be updated ca. every 4 hours, this planning approach needs effective optimization tools. The authors' hybrid two-stage approach is designed to be implemented in such a business environment. This formulation allows the solving of real life instances even for a 7-day time horizon.]]></description>
      <pubDate>Thu, 22 Oct 2015 18:02:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/1370536</guid>
    </item>
    <item>
      <title>General Model of Multirailroad Freight Car Management</title>
      <link>https://trid.trb.org/View/1265031</link>
      <description><![CDATA[No abstract]]></description>
      <pubDate>Thu, 24 Oct 2013 06:44:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1265031</guid>
    </item>
    <item>
      <title>A fuzzy random model for rail freight car fleet sizing problem</title>
      <link>https://trid.trb.org/View/1256912</link>
      <description><![CDATA[In the area of freight transport, the railroads of almost all countries are faced with strong competition and a prominent trend of market reduction. It has become imperative for rail systems to develop better planned instruments for more rational and efficient utilization of freight cars that represent a great amount of total investments. In this paper a new formulation and a solution procedure is proposed for optimizing the fleet size and freight car allocation in the presence of uncertainty. The uncertainty of the rail freight car demand is often tackled from the traditional probability theory. However, various types of uncertainties and fuzziness are inherent in real rail freight transport operating environment. In this paper, the issue of rail freight car fleet sizing and allocation problem will be addressed under such circumstances. Specifically, an approach based on optimal control theory by considering the fuzziness and randomness for rail freight car demand is developed here. The problem is formulated as the problem of finding an optimal fuzzy regulator for a fuzzy linear system with fuzzy quadratic performance index and fuzzy random initial conditions. Numerical example is given to illustrate the model and solution methodology.]]></description>
      <pubDate>Mon, 12 Aug 2013 16:45:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1256912</guid>
    </item>
    <item>
      <title>Data Mining on Index of Static Load of Freight Cars</title>
      <link>https://trid.trb.org/View/1238561</link>
      <description><![CDATA[Static load of freight vehicles is one of the important indices to evaluate the efficiency of railway wagon usage, as well an important basis for predicting coefficient of static load in railway line design. Based on sorting out the data structure of static load, clustering algorithm of K-medorids is employed for data mining to find the significant and relatively stable classification characteristics between static load of railway administrations. It is different delivery proportions of heavy goods that are indicated by index factor analysis to cause the static load classification of railway administrations. The data-mining also indicates the differences of static load between different grading railway administrations which cannot be ignored, therefore determining the coefficient of static load in railway design based on divided region is recommended.]]></description>
      <pubDate>Wed, 30 Jan 2013 09:04:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1238561</guid>
    </item>
    <item>
      <title>Interval Estimating the Carrying Capacity of Railway Stations</title>
      <link>https://trid.trb.org/View/1113621</link>
      <description><![CDATA[It is the statistical inference method that is the current calculating method of carrying capacity of railway stations, and the result of this method is a point estimation. Based on the Utilization Rate calculation method, this paper analyzes the characteristics of the sampled-data of the Occupation Time and Times, and estimates the confidence interval of the sampled-data, then synthesizes the intervals of the Time Standard and the Utilization Rate by Synthesis of Uncertainty, and last puts forward the interval estimating method for carrying capacity of the railway station.]]></description>
      <pubDate>Fri, 21 Sep 2012 09:39:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1113621</guid>
    </item>
    <item>
      <title>Period Operating Method: A New Method of Transport Organization in Carrying Capacity-Restricted District for Railway Speed-Raising Lines</title>
      <link>https://trid.trb.org/View/1113629</link>
      <description><![CDATA[Period Operating Method (POM), one way of train untwining in overcapacity section for speed-raising lines, is proposed. The basic principles of the period operating and the calculation method of carrying capacity utilization rate are enumerated. After that the general of period operating method is designed. The example analyzed indicates that under given number of trains, the utilization rate of carrying capacity goes down with the reduction of operating periods for freight trains and increase with the number of same type tracking passenger trains, which effectively alleviates the intense situation of the carrying capacity. Compared with group tracking method, this method has the advantages of higher travelling speed of passenger and freight trains, less interference and fewer arrival and departure tracks.]]></description>
      <pubDate>Fri, 21 Sep 2012 09:39:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1113629</guid>
    </item>
    <item>
      <title>Mind the Gap: Why The Current Case Law on Demurrage Makes Little Sense and Undermines the Federal Statute</title>
      <link>https://trid.trb.org/View/1146670</link>
      <description><![CDATA[Section 1074 of U.S. Code Title 49 gives railroad the statutory responsibility to establish and collect demurrage charges in order to fulfill national needs related to (1) freight car use and distribution, and (2) maintenance of an adequate supply of freight cars.  However, in 2010, the United States Supreme Court declined to hear argument in Norfolk Southern Ry. Co. v. Groves, a case that created a circuit split as to the application of demurrage rules to warehouses and other intermediaries in rail transportation. The author of the current paper contends that by declining to hear argument in this case, a lower court ruling that highlighted and expanded a regulatory gap that undermines the purpose of 49 U.S.C. 10746 was permitted to stand. This regulatory gap relies on designations such as "consignee" and "in care of" that railroads do not use. The courts' continued reliance on these terms and the common law of contracts allow parties who bear responsibility for the inefficient handling of freight cars to avoid responsibility for demurrage charges. The author calls for the United States Surface Transportation Board to act aggressively to fill the demurrage gap by making the statute paramount and providing guidance to the courts so that the statute is not impeded by common law.]]></description>
      <pubDate>Mon, 30 Jul 2012 09:50:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/1146670</guid>
    </item>
    <item>
      <title>Freight Cars: A Red-hot Market</title>
      <link>https://trid.trb.org/View/1114439</link>
      <description><![CDATA[This article describes how a huge bulge in freight car orders in this year’s first quarter sent waves of optimism through an industry that is the bedrock of the railway supply business. However, there were also undercurrents of concern. Hope that the freight car industry was coming out its recession slump was tempered by fears that the sudden feast of orders might produce a shortage of castings and other components. This new surge in orders caused some manufacturers to wonder if this would cause the same problem that overtook the industry in 1978-1979. That was when buyers, spurred by newly created per-diem incentives, flooded the marketplace with order for 127,000 cars in a single year. At that time, there were nearly 20 carbuilders versus today’s six and they had to scramble to find scarce parts to keep the assembly lines moving. The article attempts to balance demand with the production of new cars.]]></description>
      <pubDate>Mon, 29 Aug 2011 07:43:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/1114439</guid>
    </item>
    <item>
      <title>Effectiveness of Mobility Management in a Transportation Policy Aimed at Achieving the Kyoto Protocol – Kyoto Project for Studying an Efficient Car Utilization</title>
      <link>https://trid.trb.org/View/919308</link>
      <description><![CDATA[This paper will discuss that as the first commitment period of the Kyoto Protocol comes to a start, the reduction of greenhouse gas emissions becomes an urgent topic in the transport sector. Although the share of car use in terms of a modal split in Kyoto, where the Kyoto Protocol was born, is rather low compared with other similar scale metropolitan areas around the world, activities concerning all citizens aimed at reducing their car use have become very popular. In particular, Mobility Management, a transportation policy which controls excessive car use by using communication skills, is producing good results. In this paper, the authors will show the successful results of the “Kyoto Project for Studying an Efficient Car Utilization” by introducing two specific projects. One of these is an example of how ridership for railways has dramatically increased as a result of the widespread execution of Workplace Mobility Management, and the other is an example that the ridership of buses has increased because of integration with commuter buses in industrial areas. Based on these results, and paying attention to the execution process of these projects, the authors analyze the factors leading to the successful results. Finally, the authors propose ideas for use in other areas with similar characteristics.]]></description>
      <pubDate>Fri, 11 Jun 2010 12:05:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/919308</guid>
    </item>
    <item>
      <title>Key Transportation Indicators. November 2008</title>
      <link>https://trid.trb.org/View/892809</link>
      <description><![CDATA[This report contains: Transportation Services Index; Air Travel Price Index; Domestic Airline Jet Fuel; Major U.S. Air Carriers On-Time Performance; Motor Fuel Prices: Retail Diesel Prices; Motor Fuel Prices: Retail Gasoline; U.S. Highway Vehicle Miles Traveled; Amtrak Ridership; Index of Railroad Fuel Prices; Rail Capacity Utilization: Rail Passenger Load Factor; Rail Freight: Revenue Ton-Miles; Rail On-Time Performance; Use of Passenger Rail: Revenue Passenger Miles; U.S. Surface Trade with Canada and Mexico.]]></description>
      <pubDate>Tue, 21 Jul 2009 08:11:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/892809</guid>
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