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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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    <item>
      <title>Interactive Simulation to Explore Urban Distribution Schemes</title>
      <link>https://trid.trb.org/View/1581367</link>
      <description><![CDATA[The goal of building a shared vision about city logistics is often obstructed by the diversity of its actors (authorities, carriers, shippers, etc.). As an example, urban deliveries are sometimes not taken into account in the urban planning of cities or are simply misunderstood. This reality highlights the need for accessible and straightforward decision support tools in this field. In this work an interactive simulation is proposed as a playful tool to disseminate theoretical results from academia and lessons learned towards non-experts, who can easily interact with a model. The proposed interactive simulator aims at helping actors to broadly share and enlarge their perspective about a specific problem. That is, identifying the different objectives and constraints of other actors and converging towards a collective solution to the problem at hand. A trial was performed with 28 participants that explored and compared two different distribution schemes using interactive simulation. Positive feedback from the participants shows promising perspectives for this type of tool.]]></description>
      <pubDate>Mon, 06 May 2019 15:20:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/1581367</guid>
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    <item>
      <title>Dynamic freight flow modelling for risk evaluation in food supply</title>
      <link>https://trid.trb.org/View/1581865</link>
      <description><![CDATA[This paper presents a calibrated dynamic multi-scale multi-regional input–output (MSMRIO) model of the German food supply system based on real data. The model comprises 51 commodity groups from farm to fork differentiating three different temperature ranges as well as living animals. Spatially, it works on an aggregate level of 402 regions within Germany as well as its 50 most important trading nations. It determines the commodity flows and the additionally needed transport capacity in case of disruptions. Showing how changes in production, inventories, sourcing, and consumption affect commodity flows, the model uncovers vulnerabilities and makes risk evaluation possible.]]></description>
      <pubDate>Fri, 22 Mar 2019 16:16:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1581865</guid>
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      <title>Increasing effectiveness of the transportation network by using the automation of a Voronoi diagram</title>
      <link>https://trid.trb.org/View/1577568</link>
      <description><![CDATA[The present article covers the problem of optimization of transport terminal service area zones of city districts and freight delivery from the logistics centres, which is a priority task at the present time. To solve this problem, it is suggested to apply the Voronoi model adapted for transportation network. The model is developed with the geometrical instrumentation applied to find the map of the shortest distances. The development includes the space being subdivided into clusters. Mathematical formulation of the cluster model can vary depending on the city size. The larger the city is, the bigger the number and sizes of the clusters are. Standard Voronoi model satisfies some properties that are given in this article. To solve this problem, a module of the MATLAB software suite was used, in particular, the algorithm of constructing of Voronoi polygons. The capabilities of the software allowed carrying out the cluster analysis, and, on the basis of the comparative analysis, calculating a number of values that reflect the spatial arrangement. To arrange the effective operation of the transportation corridors, a direct interaction with logistics centers is necessary. They ensure the prompt delivery of the freight in the quantity required, without creating any obstructions in the network. Moreover, it is necessary to take into consideration economic factors, in particular, the decrease of: the fuel consumption rate, the average distance run of the rolling stock, and the number of loading and unloading stations for the service activities of certain zones. To provide a complex solution of the designated problem, it is necessary to create systems of prompt management of operation of freight transportation, systems of forwarding services and implementation of methods that are able to reduce the load of the street and road network by means of the expert distribution of the freight traffic flows, to ensure reduction of ecological pressure, to find the more economic transportation variants.]]></description>
      <pubDate>Sat, 23 Feb 2019 17:25:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/1577568</guid>
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    <item>
      <title>Minimization of urban freight distribution lifecycle CO2e emissions: Results from an optimization model and a real-world case study</title>
      <link>https://trid.trb.org/View/1529153</link>
      <description><![CDATA[This research models urban freight distribution services lifecycle CO2e emissions. A lifecycle emissions minimization model for the fleet size and composition problem is presented and applied to a real-world case study. The model explicitly incorporates parking and idling emissions which are significant in multi-stop urban distribution routes. Lifecycle emission elasticities as well as the impact of logistics constraints such as route duration and vehicle cargo capacity are estimated and analyzed. Policy implications and tradeoffs between electric tricycles and conventional diesel vans are discussed.]]></description>
      <pubDate>Thu, 30 Aug 2018 12:20:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1529153</guid>
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    <item>
      <title>How Will Millennials Impact Freight Flows in Texas?</title>
      <link>https://trid.trb.org/View/1481077</link>
      <description><![CDATA[Millennials (born between 1983 and 2000) represent approximately 25 percent of the population in the United States and already outnumber baby boomers (born between 1946 and 1964) in the current population. As young adults, millennials are becoming an important consumer demographic. Purchasing drives much of freight—people demand goods, and those goods are shipped to a store where they can be purchased, or goods are shipped directly to a home in the case of online shopping. Because purchasing drives freight, millennials’ consumer behavior and expectations will impact the future of the freight transportation system in Texas. This research attempts to understand how millennials differ from baby boomers when they were young adults. Specifically, this research attempts to provide insight into millennial spending (e.g., types of purchases), purchasing behavior (e.g., frequency and online), and millennials’ expectations for the delivery of purchases.]]></description>
      <pubDate>Sun, 03 Sep 2017 20:11:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1481077</guid>
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    <item>
      <title>Impacts of Freight Parking Policies in Urban Areas: The Case of New York City</title>
      <link>https://trid.trb.org/View/1362120</link>
      <description><![CDATA[Freight flows are a physical expression of the economy, so fostering efficiency in the movement of freight from producers to consumers will spur growth for the economy and employment. However, the transportation of freight generates a large amount of traffic, with resultant congestion, pollution, noise, infrastructure damage, and threats to the quality of life. The main goal of transportation policy should therefore be to maximize the net social benefits of freight activity by ensuring efficient freight flows, while mitigating the negative impacts associated with freight activity. Achieving a proper balance is always a challenge, as it is in the case of urban parking and curb allocation. In most city centers and business districts (CBDs), parking is very limited, translating into trucks double parking, idling, circling blocks, or extending into sidewalks and roadways while using undersized loading areas. This is not only an enforcement issue; frequently, the number of available parking spaces is not enough to satisfy the needs of delivery trucks. In Manhattan for instance, there are ten ZIP codes where the linear capacity of the streets is insufficient to accommodate the trucks needed to make deliveries (Jaller et al., 2013). As a result, carriers are in most cases, forced to park illegally and pay large amounts of money in parking fines ($500 to $1000 per truck per month) (Holguín-Veras et al., 2008). Freight vehicles need to park close to their customers, as the cost of walking from a parking facility to their destinations is very high; parking further away reduces the size of the loads drivers can carry, all of which increases delivery and parking times. As demand for parking increases in CBDs, there is an increasing need for analysis tools to support decisions that will strike a viable balance between supply and demand. Policy makers need these tools to identify and analyze the impacts of potential policies. Traffic simulation tools have been developed to support efforts devoted to modeling passenger car traffic, but most of these pay almost no attention to the effects of the parking allocations, travel times and congestion generated by delivery trucks. There is a lack of data, and knowledge about how the whole system works, and how best to influence it to achieve policy goals. The development of tools aimed at a fuller understanding of parking conditions in urban areas will help to fill this void, and allow public agencies to manage and regulate parking--for passenger and freight traffic--more effectively.]]></description>
      <pubDate>Wed, 22 Jul 2015 01:01:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1362120</guid>
    </item>
    <item>
      <title>Improving Freight System Performance in Metropolitan Areas</title>
      <link>https://trid.trb.org/View/1356804</link>
      <description><![CDATA[Freight flows are a physical manifestation of the manufacturing and consumption activities that are pillars of modern life. For that reason, transportation policy should ensure that freight is moved as efficiently as possible, as hampering the flow of cargo is bound to have a negative effect on the economy. At the same time, it is important to minimize the negative impacts produced by freight traffic such as congestion, pollution, noise, infrastructure damage, and deterioration of quality of life. The goal of public policy must be to maximize the benefits of the freight flows while minimizing the negative externalities of the freight vehicle traffic.]]></description>
      <pubDate>Sat, 06 Jun 2015 01:00:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1356804</guid>
    </item>
    <item>
      <title>A cooperative framework for freight distribution in multimodal corridors</title>
      <link>https://trid.trb.org/View/1352595</link>
      <description><![CDATA[Nowadays, there is a growing agreement that sustainable mobility is about effectively interconnecting transport systems which have to provide a door-to-door service. Intermodal transportation of freights is an important issue in this context, due to the increasing amount of freight movements all over the world. The current study proposes and examines an approach for optimizing such transport chains. In this approach, the freight distribution corridor is decomposed into the different elements with individual functions that interact two-by-two based on a cooperative scheme relying on information flow in the corridor. The methodology is evaluated by means of an example corridor and the results are presented.]]></description>
      <pubDate>Tue, 19 May 2015 11:06:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/1352595</guid>
    </item>
    <item>
      <title>Dynamic Vehicle Routing Optimization on Urban Distribution with Real-Time Information</title>
      <link>https://trid.trb.org/View/1326776</link>
      <description><![CDATA[In view of the situation of urban distribution, the dynamic vehicle routing problem - in which the information keeps changing during the distribution process - is studied. Various kinds of real-time factors are analyzed. By introducing virtual customers, the paper converts the dynamic vehicle routing problem into the classic single-type static vehicle routing problem and proposes a model based on natural description. A two-stage solving strategy is put forward, and a hybrid genetic algorithm is constructed. Numerical experiment results show that the model and algorithm can effectively reduce the distribution cost.]]></description>
      <pubDate>Tue, 21 Oct 2014 09:57:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326776</guid>
    </item>
    <item>
      <title>Intelligent Logistics Distribution Based on ITS and EC</title>
      <link>https://trid.trb.org/View/1274847</link>
      <description><![CDATA[With economic development, the intelligent logistics system is well known. This paper proposes Intelligent logistics distribution along with a brief introduction of the intelligent logistics system. After a detailed introduction of the applications of intelligent transportation systems (ITS) and electronic commerce (EC) in intelligent logistics distribution, this paper presents the intelligent logistics distribution model and algorithms, and puts forward the combination of ITS and EC which could become the development trend for smart logistics distribution.]]></description>
      <pubDate>Tue, 08 Apr 2014 12:20:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/1274847</guid>
    </item>
    <item>
      <title>Freight Flow Distribution Optimization Model under Transportation Corridor</title>
      <link>https://trid.trb.org/View/1274799</link>
      <description><![CDATA[Flow distribution is one of the classic areas of transportation. With the vigorous development of the transportation corridor, the traditional flow distribution algorithm based on the shortest path no longer meets the current transport situation. This paper is based on the model of freight flow distribution by various transportation modes of the regional transportation corridor, combined with characteristics and advantages of each transport mode, so as to reduce the complexity of the model solution. Then this paper will present an actual optimal solution which predicts the burden with different modes of transport freight within transport channels. Data will be offered for regional transport channel construction.]]></description>
      <pubDate>Tue, 08 Apr 2014 12:20:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/1274799</guid>
    </item>
    <item>
      <title>Novel Supply Chain Network Equilibrium Model with Consideration of Service Decay Over Delivery Time</title>
      <link>https://trid.trb.org/View/1276413</link>
      <description><![CDATA[In this paper, a network equilibrium model for a four-layer tactical supply chain network is developed. Such supply chain networks involve raw material supplier, manufacturer, retailer/DC, and final customer. The service decay over delivery time of retailer/DC to final customer is considered. After analysis of logistics flow and economics equilibrium layer in supply chain, a supernetwork topology frame is proposed. Finally, a modified projection algorithm is employed to solve the novel equilibrium models. Such a model is more realistic to the real world.]]></description>
      <pubDate>Mon, 03 Mar 2014 10:52:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1276413</guid>
    </item>
    <item>
      <title>Development of a Statewide Commodity Flow Distribution Model Using Composite Friction Factors</title>
      <link>https://trid.trb.org/View/1267574</link>
      <description><![CDATA[In a traditional four-step urban transportation demand forecasting modeling, passenger trips in a zone generated in the trip generation step are distributed to other zones using various algorithms, such as a gravity model. However, this method does not apply well to commodity flow distribution because commodities are transported by various types of trucks depending on types of commodities, which eventually affect the number of trips generated. A new concept for distributing commodity flows to zones using an enhanced gravity model with composite friction factors was developed and the concept was applied to commodity flow distribution in the state of Utah.]]></description>
      <pubDate>Tue, 19 Nov 2013 14:29:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1267574</guid>
    </item>
    <item>
      <title>15th Annual Freight and Logistics Symposium: The Future is Front and Center: The Impacts of
Economic Change on Freight Transportation, A Summary Report</title>
      <link>https://trid.trb.org/View/1263948</link>
      <description><![CDATA[The U.S. transportation system stands at the center of virtually all economic activity in the country today. Effects of a lengthy global recession are radically and rapidly reshaping transportation priorities and needs. Now more than ever, freight transportation, logistics, and manufacturing industries must critically analyze the driving forces behind these high-impact changes, future freight patterns, and critical dependencies to shape appropriate freight policy and system investment priorities. During the 15th Annual Freight and Logistics Symposium, representatives from the business, academic, and public sectors gathered to discuss trends and the effects of these economic changes on freight and logistics providers. Presentations included:  Future Freight Flows, Christopher Caplice; Implications to Minnesota: Panel Discussion, panelists included Wil Kratz, Judy Mitchell, Todd Feltes, and Chip Smith; and Intersection of Transportation and Economic Development: Panel Discussion, panelists included Steve Elmer, Dan Dorman, and Vann Cunningham.]]></description>
      <pubDate>Tue, 01 Oct 2013 14:05:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1263948</guid>
    </item>
    <item>
      <title>Development of a Motorways of the Sea Multicountry Transportation Network</title>
      <link>https://trid.trb.org/View/1261519</link>
      <description><![CDATA[The continuous increase in freight transportation demand necessitates the promotion of nonroad mode alternatives. In this context, the motorways of the sea (MoS) initiative is intended to establish more efficient, frequent, and high-quality maritime-based logistics services between countries. Although the benefits of MoS development, which include economic development, territorial cohesion, environmental protection, and relief of road transportation congestion, are apparent, realization requires further investigation. A methodology was devised for the development of a MoS network that would connect several countries. The network would consist of market-attractive intermodal international corridors that would serve the freight demand of a multicountry region. Three main phases were proposed as part of the methodology: (a) the definition of zones, transportation network, and trade characteristics of a study area that included several countries; (b) forecasts of freight flows; and (c) assignment of freight flows network and development of a MoS multicountry transportation network. The methodology was applied in the Adriatic region to develop a MoS network between six countries: Italy, Greece, Slovenia, Croatia, Albania, and Montenegro. Interaction between the established MoS international corridors and their potential performance for freight attraction was analyzed. Interested stakeholders can use the proposed methodology to evaluate the establishment of new MoS links within the framework of a wider intermodal multicountry transportation network.]]></description>
      <pubDate>Fri, 06 Sep 2013 10:48:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/1261519</guid>
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