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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>Research in Progress (RIP)</title>
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      <title>Expanding the Capability of the Statewide Travel Demand Model Using Dynamic Traffic Assignment</title>
      <link>https://rip.trb.org/View/2248973</link>
      <description><![CDATA[A relatively recent modeling innovation known as dynamic traffic assignment (DTA) is designed to represent fluctuating traffic volumes and long trips on complex networks over the course of a single day. Integrating an optional DTA step into existing traffic modeling would improve the model’s accuracy, flexibility, and versatility, thereby enhancing ADOT’s ability to evaluate complex modernization projects—such as traffic interchange reconfiguration, intelligent transportation systems, and other traffic operations enhancements—and model traffic congestion and freight movement more accurately than is currently possible. 
The proposed study would build on the results of ADOT's SPR-768 Dynamic Traffic Assignment: Assessing Its Value as a Planning Support Tool in Arizona.]]></description>
      <pubDate>Fri, 15 Sep 2023 17:45:34 GMT</pubDate>
      <guid>https://rip.trb.org/View/2248973</guid>
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      <title>Assessment of Austin, El Paso, and San Antonio HERO Incident Management Programs</title>
      <link>https://rip.trb.org/View/2055957</link>
      <description><![CDATA[The Texas Department of Transportation (TxDOT) aimed at improving safety and keeping traffic flowing, the Highway Emergency Response Operator (HERO) program was established to clear minor crashes from roadways and assist motorists in need. Following the public's positive response, more districts have instituted HERO programs in recent years. Although HERO has proven popular, the program has not been formally assessed. The objective of this project is to conduct a systematic assessment of HERO in Austin, El Paso, and San Antonio. The research team will perform comprehensive analyses in terms of operational efficiency, staffing and equipment levels, incident response and clearance time improvements, impacts on travel delay, and benefit to cost ratio through a series of on-site interviews, data analysis, and Dynamic Traffic Assignment micro-simulations. The research team will compare clearance times on Safety Service Patrol (SSP) routes vs. non-SSP routes, and contract service vs. non-contract service. Recommendations and guidance shall be provided to TxDOT’s districts and Traffic Safety Division to improve HERO effectiveness and efficiency. This project will give TxDOT a thorough understanding of HERO as well as future improvement recommendations.
]]></description>
      <pubDate>Thu, 03 Nov 2022 12:19:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/2055957</guid>
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      <title>Dynamic Traffic Assignment: Assessing Its Value as a Planning Support Tool in Arizona</title>
      <link>https://rip.trb.org/View/1516639</link>
      <description><![CDATA[The Arizona Statewide Travel Demand Model (AZTDM) simulates the interaction between people and the roadway system. The model produces travel forecasts used for highway design and transportation planning.

However, the AZTDM currently has a static traffic assignment process, which represents average conditions over a long period, in contrast to the rapidity with which traffic levels can change in the real world.

A recently developed technology, called dynamic traffic assignment (DTA), is designed to represent fluctuating traffic volumes and long trips on complex networks. DTA may enhance ADOT’s understanding of existing and future travel behavior, enabling a more accurate modeling of traffic congestion and freight movement, as well as the testing of alternative solutions.

The objective of the research is to evaluate the feasibility of using DTA statewide and the implications in terms of cost, accuracy, and integration with the existing model.


]]></description>
      <pubDate>Thu, 21 Jun 2018 13:08:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/1516639</guid>
    </item>
    <item>
      <title>Addressing Fidelity Between Meso- and Micro-Simulations to Evaluate Traffic Flows in Multiresolution Modeling</title>
      <link>https://rip.trb.org/View/1465504</link>
      <description><![CDATA[Currently, traffic management strategies such as adaptive control and ramp metering systems go through simulation-based testing of the strategies, before field-testing of hardware/software systems, and implementation and evaluation of the system. Simulation testing have been quite successful for isolated intersections and single intersections, and small networks with 1-3 intersections – where the effect of re-routing due to incidents, major events that result in changes in traffic patterns, have none or only minor impacts on the simulations. For larger networks, when there is both lane based dynamics for intersection control and ramps, and link based dynamics for re-routing, integrated models have lack of fidelity between lane dynamics (microscopic simulations) and link dynamics (macroscopic simulation). Part of the lack of fidelity among the meso- and micro-models is due to scope; dynamic traffic assignment (DTA)-type models usually approximate links and path loads for planning purposes while scope of micro-simulation models is on traffic management through small networks. This project will attempt to develop a meso-type model that will approximate the spatial-temporal traffic patterns of a VISSIM model, a well-known micro-simulation model. In other words, instead of fitting a large DTA model based on fitting flows on a few measured links, we would develop a model, here on referred to Model X, which approximates all the flows of a VISSIM model albeit faster than VISSIM.]]></description>
      <pubDate>Wed, 26 Apr 2017 16:53:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/1465504</guid>
    </item>
    <item>
      <title>Integrating Meso- and Micro- Simulation Models to Evaluate Traffic Management Strategies</title>
      <link>https://rip.trb.org/View/1363809</link>
      <description><![CDATA[Currently, traffic management strategies such as adaptive control and ramp metering systems go though the following steps: (i) conceptualization of strategies, (ii) development of logic and software algorithms, (iii) simulation-based testing of the strategies, (iv) hardware implementation, (v) field testing of hardware/software systems, (vi) operational testing of the proposed systems, (vii) implementation and evaluation of the system. The simulation testing done in step (iii), when performed, is conducted using models based in one of the several of-the-shelf-simulation packages such as VISSIM, CORSIM, AIMSUN etc. Such models and simulation testing have been quite successful for isolated intersections and single intersections, and small networks with 1-3 intersections - where the effect of re-routing due to incidents, major events that result in changes in traffic patterns have none or only simple impacts on the simulations. Meso-models that simulate small to large networks, on the other hand, are used mostly at a planning level to evaluate long-term impacts of network wide transportation decisions and management strategies such as network changes (e.g. adding a lane), managed lanes, congestion pricing, dynamic messages, etc. Simulation based "Dynamic Traffic Assignment" (DTA) are typical of such models - where planners input traffic demand in terms of time-dependent Origin-Destination travel demands, and the models outputs traffic conditions, usually at the time resolution of hourly traffic conditions each day of the week. Some simulation based DTA models are being used in USA and elsewhere. It should be noted that meso simulation is really a spatial-temporal approximation of micro-simulation traffic - time steps in meso is in terms of 6 seconds, or 10 seconds, or in minutes whereas in micro they are in seconds or tenths of seconds; spatial resolution is in terms of roads segments and tenths of miles in meso whereas in micro one refers to vehicles in lanes and spaces in fractions of feet. The integration of micro-and macro- models has been attempted before, but the integration is not as seamless as it should be. Results of a macro model are sent "down" to the micro-model to provide travel demand, usually in a straightforward manner, but the results of the micro-model are not easily sent "up" to the macro model. Still this is very much needed, especially in the testing of Dynamic Mobility Applications (DMA) that are envisioned due to connected vehicle technologies, and Active Traffic and Demand Management (ATDM) strategies, multiple resolution in space and time is required. This project will consider two such applications: Proactive Multimodal Traffic Signal Control (PMTSC1) and Multimodal Adaptive Ramp Metering (MARM*). The signal control algorithms require data with time and space resolution of feet and seconds and while the optimization objectives require the prediction of traffic through the intersections over several minutes and even over hours. As with PMTSC, MARM algorithms require data with time and space resolution of feet and seconds and while the optimization objectives require the prediction of traffic through the ramps over several minutes and hours. Note that in both PMTSC and MARM, algorithms require prediction of the network conditions and the feedback of the conditions from the controls being developed.]]></description>
      <pubDate>Tue, 04 Aug 2015 01:00:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/1363809</guid>
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    <item>
      <title>Simulation Study of Emergency Evacuation of Greater Jackson due to Hazardous Material Incident</title>
      <link>https://rip.trb.org/View/1346112</link>
      <description><![CDATA[In response to both natural and man-made disasters, emergency evacuation aims to move a large disaster affected Volume through a multimodal transportation network towards safer areas quickly and efficiently. The derailment of a freight train in downtown Jackson thus causing the spillage of chlorine, a highly toxic hazardous material, is assumed as an emergency evacuation scenario to (1) identify weak links in the highway network; and to (2) develop effective emergency evacuation strategies to reduce congestion on highway networks.  In this report the area that will be affected by the gas spill extends from Mill Street on the west to Airport Road on the east and Meadowbrook Road on the north to Fortification on the south. The traffic operation was simulated using a dynamic traffic assignment (DTA) based traffic-network planning and simulation program DynusT. The origin and destination (OD) demand was calibrated using observed traffic volume data at several critical evacuation routes. Various traffic management strategies such as baseline traffic control, traffic management strategies and contra-flow deployment were employed to reduce congestion on highways during emergency situations.]]></description>
      <pubDate>Fri, 13 Mar 2015 01:00:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/1346112</guid>
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      <title>Modeling Traffic Flow at Merge Bottlenecks Considering Merging Location Choice</title>
      <link>https://rip.trb.org/View/1239207</link>
      <description><![CDATA[Merge bottlenecks, such as lane drops, junctions with entry ramps, and freeway-to-freeway merges, are the most common places where traffic congestion initiates. These are the places where drivers compete for reduced road space and are forced to interact. Furthermore, merge junctions are also fundamental building blocks of networks, hence their models are essential components of network traffic models widely used in dynamic traffic assignment and other network applications. Despite recent renewed interest and progress made in modeling merge bottlenecks, the understanding of and ability to model them is far less mature than those related to traffic on homogeneous road sections, partly due to the complexity of merge dynamics and partly insufficient observations. In this research, the project will attempt to gain a better understanding of traffic system behavior at merge bottlenecks through careful studies of vehicle trajectories from on-ramp junctions, and use this understanding to develop more realistic merging traffic flow models that takes into account the choice of merging locations. It is expected that this research can help build a solid foundation of network traffic flow theory by addressing an essential component of this theory, namely merging traffic dynamics, which in turn can help the design of more effective traffic control strategies to reduce traffic congestion caused by merge bottlenecks.]]></description>
      <pubDate>Thu, 31 Jan 2013 01:01:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/1239207</guid>
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