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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>Empirical assessment of land use and other policy impacts on freight facility location choices in California</title>
      <link>https://rip.trb.org/View/2702676</link>
      <description><![CDATA[The rapid expansion of warehousing and logistics activities in California has reshaped land-use patterns and placed substantial pressure on transportation systems and nearby communities. Growth in e-commerce, supply chain restructuring, and regional economic development incentives have contributed to an uneven and largely uncoordinated proliferation of freight facilities. Although these facilities support regional economies, their concentration heightens concerns about congestion, safety, air quality, and the availability of quality job opportunities. Local and regional governments struggle to anticipate these impacts because they lack empirical tools to link policy actions to freight facility siting decisions. 

This project develops an integrated framework to evaluate how land-use (LU), transportation, and economic development policies influence the location of freight facilities in California, and how these patterns relate to economic and social outcomes. The research compares three regional case studies spanning 20 years, integrating semi-quantitative policy analysis, satellite imagery-based LU classification, and spatial econometric modeling. Expected results include a geospatial database linking freight facility development with LU and policy environments, empirical evidence of policy-driven LU and logistics trends, and indicators describing the social and economic impacts of freight facility proximity. The findings will support state, regional, and local agencies in designing policies that improve goods movement efficiency while minimizing local impacts, thereby contributing to California's economy.]]></description>
      <pubDate>Thu, 14 May 2026 16:42:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2702676</guid>
    </item>
    <item>
      <title>A Guide for Developing Airport Cargo Handling and Warehouse Infrastructure Through Public-Private Partnerships</title>
      <link>https://rip.trb.org/View/2588322</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Tue, 12 Aug 2025 10:06:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/2588322</guid>
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    <item>
      <title>Transportation Enterprise Data Warehouse Implementation Guide



</title>
      <link>https://rip.trb.org/View/1957057</link>
      <description><![CDATA[As part of a robust data governance strategy, transportation agencies must decide how to best manage the storage, access, and dissemination of data products and services for internal use/reuse and external distribution within its data architecture. An important piece of modern data architecture is an enterprise data warehouse, which, conceptually, will provide a way to reduce data redundancy, improve data consistency, and enable data usage for better decision-making. Effective data warehouse implementations are complex, especially when an entity has highly diverse data sets and technology infrastructure.

State departments of transportation (DOTs) need guidance on how to best architect and implement an enterprise data warehouse strategy. DOTs would also benefit from guidance on the complete set of functional requirements including, but not limited to, federation (aggregating from multiple sources), data extract-transform-load (ETL) and extract-load-transform (ELT), storage, naming convention, structure (model), roles and responsibilities, web services, data publishing processes, access by third-party applications, and records management. Any conventions, models, and structure covered by the guidance will also need to support and align with standard frameworks used in transportation, such as Industry Foundation Classes (IFC), to the greatest extent practical.

OBJECTIVE: The objective of this research is to develop a guide for enterprise data warehouse development, implementation, and best practices to support DOT business needs.

DOT business needs include, but are not limited to, efficient upload, use, sharing, security of data, data analytics, operations management, performance management, asset management, safety management, data-driven decision-making, data integration, and federal and state data reporting.]]></description>
      <pubDate>Fri, 27 May 2022 12:57:09 GMT</pubDate>
      <guid>https://rip.trb.org/View/1957057</guid>
    </item>
    <item>
      <title>Distribution Problems in eCommerce Fulfillment</title>
      <link>https://rip.trb.org/View/1845544</link>
      <description><![CDATA[In this project the research team considers an omnichannel retailer that operates both brick-and-mortar stores and super warehouses.  The retailer’s objective is to meet traditional and eCommerce fulfillment demands that can be grouped into three representative modes:  shopping in store, ordering on-line and delivering from warehouse or store, ordering on-line and picking up at store.   On the supply side, the retailer must decide the inventory at the store, the express delivery capacity, the delivery premium, and the just-in-time inventory replenishment for stores.  On the demand side, a consumer must consider in her utility of each fulfillment mode such factors as the cost of transportation, the delivery fee, the cost/risk of shopping in store, and the likelihood of unsatisfactory on-line purchase.  The research team formulates this omnichannel fulfillment model as a leader-follower game, in which the leader maximizes the retailer’s profits, and the follower allocates consumer demands between the three channels according to utility maximization.  The properties of the problem will be analyzed, and the solution methods will be developed. A case study will be constructed by calibrating a stylized model using empirical data. ]]></description>
      <pubDate>Thu, 08 Apr 2021 11:58:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/1845544</guid>
    </item>
    <item>
      <title>Southeast Los Angeles (SELA) Initiative
</title>
      <link>https://rip.trb.org/View/1637647</link>
      <description><![CDATA[SELA region is 62 square miles and includes 11 cities, 4 unincorporated areas, a high proportion of manufacturing and warehousing, and major highway and rail facilities serving port related freight (Figure 1). The population is majority Hispanic, generally low income, and classified by the state’s primary environmental burden mapping tool, CalEnviroScreen, as having high pollution burden. This case study is motivated by and leverages an earlier analysis of the area conducted by USC in 2017 in collaboration with the CSULA Pat Brown Institute and the SELA Collaborative, a partnership of 11 community and non-profit organizations (Giuliano et al, 2018). The research subtasks performed as part of this proposal are based on the above mentioned analysis and community input, including input received at a November 2017 community summit that gathered over 250 local elected officials, civic leaders, and community members. There are two main research subtasks in this the SELA initiative research plan and one engagement and outreach subtask.]]></description>
      <pubDate>Thu, 11 Jul 2019 17:39:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/1637647</guid>
    </item>
    <item>
      <title>Feasibility of Waterborne Distribution at Hunts Point Terminal Market</title>
      <link>https://rip.trb.org/View/1395735</link>
      <description><![CDATA[Hunts Point Food Distribution Center, also referred to as Hunts Point Terminal Market (HPTM), is the center or hub for food distribution for the New York Metropolitan area. Hunts Point Peninsula, located in the South Bronx, is also home to over 40,000 residents. HPTM is a cooperative owned by stockholders. The cooperative has a long-term lease with the City of New York for its cooperation and tenants.

The HPTM distribution center is a vital part of the food supply chain in the New York metropolitan area. Firms’ agents arrive at the food distribution center to select and pick up food. Some food is ordered in advance; therefore, it is only picked up. The food is hauled away by truck, van or other commercial vehicles many of which are refrigerated. Two types of truck trips are made to HPTM:

     (1) The inbound truck trip is for delivering food products to the distribution center (56% west of the Hudson
      River and 44% east of the Hudson River).
 
     (2) The outbound truck trip is for hauling food products from the distribution center to grocery stores,
      restaurants, and other food venues (17% west of the Hudson River and 79% east of the Hudson River).
The demand for the distribution center’s services generates 15,000 truck trips per day, including some from large distances away. Traffic flow is constant, occurring 24 hours a day, especially during the very early morning hours. There are times during the daily operating cycle when congestion is formed on the roads leading to and from the distribution center and congestion is formed in the terminal itself. Congestion implies air pollution, noise pollution, additional road wear-and-tear, an increase of public spending on health and infrastructure maintenance and other negative externalities.

The large HPTM distribution center does not have simple and quick access. The geographical layout of the New York Metropolitan area of highways, bridges and tunnels along rivers and creeks complicates the surface transportation delivery. Delivery takes more miles to drive and more time to deliver. As a result, at times of peak demand, vehicles spend excessive time waiting and idling and on the road wasting fuel and emitting CO₂ and other gases.]]></description>
      <pubDate>Wed, 20 Jan 2016 17:39:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/1395735</guid>
    </item>
    <item>
      <title>Exploring Novel Applications of Archived Transportation Data: Predicting Freeway Crash Risk, Border Crossing Delay and Inclement Weather Impacts</title>
      <link>https://rip.trb.org/View/1258297</link>
      <description><![CDATA[There has recently been an increased interest in taking advantage of the latest Intelligent Transportation Systems (ITS) technologies to improve the efficiency, safety, resiliency, and environmental friendliness of the transportation system. The focus of this proposal is one specific ITS application or user service, namely Archived Data Management Systems (ADMS). ADMS or ITS Data Warehouses are designed to archive, fuse, organize and analyze ITS data and can therefore support a wide range of very useful applications at a minimal additional cost. Given the benefits of ITS Data Warehouses, researchers from the University at Buffalo (UB) and the State University of New York (SUNY) have recently been working with the different organizations in the Buffalo-Niagara region that collect transportation-related data to develop a prototype ITS data warehouse for the region. The proposed project has two primary objectives. First, the project proposes to further develop the prototype ITS data warehouse, currently under development by UB, in order to make it ready for use by participating agencies. Specifically, the work proposed includes: (1) further development and refinement of the programs designed to read and import the different traffic data streams; (2) the inclusion of additional data streams; and (3) the development of the graphical user interface (GUI) and the addition of new functionalities to allow the user to run a number of queries and perform different types of analysis. The second objective of the proposed research is to utilize the data within the ITS data warehouse to support three innovative and novel applications of archived data. These are: (1) Developing models and methods for predicting the likely crash risk in real time; this work will involve correlating and fusing: (a) incident data from Niagara International Transportation Technology Coalition (NITTEC) logs; (b) real-time counts from the New York State Department of Transportation (NYSDOT) or NYSTA; (c) real-time link-based speeds from the TRANSMIT system; and (d) weather information from the national weather service; (2) Developing predictive models for predicting border crossing delays at the Niagara Frontier Border Crossings; this work will involve fusing data regarding: (a) volumes; (b) border delays; and (c) weather; (3) Analyzing the impact of inclement weather on traffic operations, with a special emphasis on studying the impact of snow on truck operations, which will involve fusing data about: (a) counts; (b) speeds; (c) accidents; and (d) weather. The aforementioned three applications are universal in nature, and all have far-reaching implications and broad impacts that go well beyond the Buffalo-Niagara region or the State of New York. Moreover, the work related to the development of the ITS data warehouse itself can serve as s a model deployment to other regions across New York State and the country.]]></description>
      <pubDate>Tue, 06 Aug 2013 01:01:13 GMT</pubDate>
      <guid>https://rip.trb.org/View/1258297</guid>
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