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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>Toward Ubiquitous Trajectory‐Based Traffic Network Diagnosis Systems
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      <link>https://rip.trb.org/View/2625315</link>
      <description><![CDATA[This project aims to develop a trajectory-based traffic network diagnosis system to address urban congestion by leveraging vehicle trajectory data and open-source tools. The system operates at both planning and operational levels, offering scalable, real-time diagnosis and mitigation of congestion issues. It integrates advanced equilibrium models and mesoscopic simulations, prioritizing computational efficiency and actionable results. By democratizing access to traffic diagnostics and enabling rapid deployment, the project envisions empowering cities worldwide to manage congestion sustainably, enhance urban mobility, and improve quality of life.

]]></description>
      <pubDate>Thu, 13 Nov 2025 16:01:21 GMT</pubDate>
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      <title>Contraflow Evacuation Planning for I-65 in Alabama</title>
      <link>https://rip.trb.org/View/1243463</link>
      <description><![CDATA[The goal of this project is to assist the Alabama Department of Transportation (ALDOT) in the planning of contraflow operations for hurricane evacuation along I-65. The idea is to reverse one direction of the roadway to accommodate the substantially increased travel flow moving from the impact area. One problem faced by ALDOT is scheduling the contraflow process. The timing for the deployment of equipment and personnel and the initiation and termination of counterflow impact the effectiveness, safety, and cost of the operation. The researchers will investigate methodologies and develop a modeling framework to determine the onset and duration of counterflow. They will also create a set of look-up tables and a prototype computer tool to assist ALDOT in planning counterflow evacuation. Different from previous studies, this research will feature: (1) a well-established and reliable meso-scopic traffic flow simulation, the cell transmission model; (2) robust and stochastic optimization techniques to determine the onset and duration of contraflow; (3) incident identification and characterization using artificial-intelligence techniques; (4) a sensitivity analysis to account for inaccurate estimation of evacuee's route-choice behaviors. The project team will work closely with ALDOT to ensure that the models, algorithms, and prototype computer tool are customized to their needs.]]></description>
      <pubDate>Tue, 12 Feb 2013 01:01:10 GMT</pubDate>
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