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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>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Impact of Dynamic Ramp Closures on Urban Expressway Traffic: A Field Study</title>
      <link>https://trid.trb.org/View/2655533</link>
      <description><![CDATA[Ramp controls, such as ramp metering and closure, have been known as a promising strategy for alleviating traffic congestion in urban expressway networks. While ramp metering is a widely adopted practice globally, dynamic ramp closure has received less attention. The key distinction between the two lies in their signaling and effects on queue formation: ramp metering utilizes short-cycled signals to manage entering traffic, potentially causing long queues during peak arrival times, whereas dynamic ramp closure conveys a noncycled no-entry signal, prompting drivers to plan alternative routes in advance, thereby effectively preventing queues. This difference suggests that dynamic ramp closure has potential to avoid the gridlock issues at adjacent intersections due to spilled queues. In this study, we have developed and implemented the world’s first city-wide dynamic ramp closure system on urban expressways in Changchun, China, leveraging data from both fixed-point detectors and connected and automated vehicles (CAVs). Our field analysis revealed that dynamic ramp closure yields significant improvements, with expressway traffic speed increasing by over 20% and throughput by 10% compared to scenarios without control. Additionally, our research indicated that travel speeds on parallel ground streets remain relatively unaffected, suggesting an overall improvement over the entire road network. We also examined driver noncompliance with dynamic ramp closures and outlined how traffic departments educated the public and mitigated noncompliance. The successful implementation of this dynamic ramp closure system serves as a compelling demonstration of its effectiveness, providing valuable insights and potential solutions for other cities grappling with similar traffic congestion issues.]]></description>
      <pubDate>Wed, 08 Apr 2026 13:57:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655533</guid>
    </item>
    <item>
      <title>Scalable analysis of stop-and-go waves: Representation, measurements and insights</title>
      <link>https://trid.trb.org/View/2626071</link>
      <description><![CDATA[Analyzing stop-and-go waves at the scale of miles and hours of data is an emerging challenge in traffic research. The past 5 years have seen an explosion in the availability of large-scale traffic data containing traffic waves and complex congestion patterns, making existing approaches unsuitable for repeatable and scalable analysis of traffic waves in these data. This paper makes a first step towards addressing this challenge by introducing an automatic and scalable stop-and-go wave identification method capable of capturing wave generation, propagation, dissipation, as well as bifurcation and merging, which have previously been observed only very rarely. Using a concise and simple critical-speed based definition of a stop-and-go wave, the proposed method identifies all wave boundaries that encompass spatio-temporal points where vehicle speed is below a chosen critical speed. The method is built upon a graph representation of the spatio-temporal points associated with stop-and-go waves, specifically wave front (start) points and wave tail (end) points, and approaches the solution as a graph component identification problem. It enables the measurement of wave properties at scale. The method is implemented in Python and demonstrated on a large-scale dataset, I-24 MOTION INCEPTION. Our results show insights on the complexity of traffic waves. Traffic waves can bifurcate and merge at a scale that has never been observed or described before. The clustering analysis of all the identified wave components reveals the different topological structures of traffic waves. We explored that the wave merge or bifurcation points can be explained by spatial features. The gallery of all the identified wave topologies is demonstrated at https://trafficwaves.github.io/.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2626071</guid>
    </item>
    <item>
      <title>Dynamic Lane Assignment with Signal Optimization for Connected Autonomous Vehicle (CAV): A Synthesis of Literature</title>
      <link>https://trid.trb.org/View/2562224</link>
      <description><![CDATA[Traffic demand varies significantly in urban areas, impacting intersection performance. Current control strategies assume fixed lane assignment with signal optimization that focuses on the traffic movements at each approach. This leads to inefficient use of temporal and spatial resources. To improve the intersection performance in such cases, Dynamic Lane Assignment (DLA), a component of Intelligent Transportation Systems (ITS), is employed to improve the intersection efficiency. As we move into an era where Connected and Automated Vehicle (CAV) technology is increasingly recognized for enhancing traffic safety and efficiency, it is important to consider that CAVs and human-driven vehicles (HDVs) will co-exist in the system for a substantial period. This necessitates managing CAVs alongside HDVs, which could benefit from dedicated lane assignments for CAVs together with signal optimization to enhance overall system performance and efficiency. However, research on CAV-based DLA combined with signal optimization in mixed traffic environments remains limited. This research focuses on understanding the state-of-the-art of managing intersections with DLA in mixed traffic environments. Information was gathered from previous research papers and public documents. For the synthesis, studies were categorized into the following topics: (1) application of DLA combined with signal optimization for CAVs; (2) application of DLA with CAVs for freeway management; and (3) other lane assignment strategies such as Dynamic Lane Grouping (DLG). The synthesis focuses on the assumptions, strategies, and policies related to lane assignment, as well as the methodologies employed in these studies. Finally, the paper provides a comprehensive overview of DLA strategies for intersection management, identifies research gaps, and proposes future directions for mixed traffic environments.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2562224</guid>
    </item>
    <item>
      <title>A first-order link-based flow model with variable speed limits and capacity drops for freeway networks</title>
      <link>https://trid.trb.org/View/2601649</link>
      <description><![CDATA[First-order link-based traffic flow models are computationally efficient in simulating freeway networks. However, the standard link transmission models fall short of reproducing traffic phenomena such as capacity drop (CD). Moreover, traffic control measures such as variable speed limits (VSLs) control may change the fundamental diagram and should be captured by traffic flow models. This study proposes a first-order link-based flow model incorporating VSL and CD for freeway simulation. In the proposed model, the vehicle flow through each link is characterized by cumulative inflow and outflow, which are influenced by the time-varying free flow speed caused by the VSL at the link's upstream boundary. CD is modeled by incorporating the traffic state-dependent capacity at the freeway lane-drop positions. A node model is then developed to determine and regulate the flow propagation between adjacent links. Simulation experiments were conducted on freeways to evaluate the model's effectiveness. The results demonstrate its ability to accurately predict traffic operations under VSL and CD while maintaining a computationally tractable representation of flow propagation.]]></description>
      <pubDate>Fri, 14 Nov 2025 08:44:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2601649</guid>
    </item>
    <item>
      <title>Sequencing-Enabled Hierarchical Cooperative CAV On-Ramp Merging Control With Enhanced Stability and Feasibility</title>
      <link>https://trid.trb.org/View/2591800</link>
      <description><![CDATA[This paper develops a sequencing-enabled hierarchical connected automated vehicle (CAV) cooperative on-ramp merging control framework. The proposed framework consists of a two-layer design: the upper-level control sequences the vehicles to harmonize the traffic density across mainline and on-ramp segments, simultaneously enhancing lower-level control efficiency through a mixed-integer linear programming formulation. Subsequently, the lower-level control, in turn, employs a longitudinal distributed model predictive control (MPC) supplemented by a virtual car-following (CF) concept to ensure three key aspects: asymptotic local stability, 𝑙₂ norm string stability, and safety. Proofs of asymptotic local stability and 𝑙₂ norm string stability are mathematically derived. Compared to other prevalent asymptotic local-stable MPC controllers, the proposed distributed MPC controller greatly expands the initial feasible set. Additionally, an auxiliary lateral control is developed to maintain lane-keeping and merging smoothness while accommodating ramp geometric curvature. To validate the proposed framework, multiple numerical experiments are conducted. Results indicate a notable outperformance of our upper-level controller against a distance-based sequencing method. Furthermore, the lower-level control effectively ensures smooth acceleration, safe merging with adequate spacing, adherence to proven longitudinal local and string stability, and rapid regulation of lateral deviations.]]></description>
      <pubDate>Mon, 03 Nov 2025 16:34:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2591800</guid>
    </item>
    <item>
      <title>A traffic control strategy for freeway merging zones cooperating safety and efficiency in the intelligent connected environment of mixed vehicles</title>
      <link>https://trid.trb.org/View/2589234</link>
      <description><![CDATA[The manner and intensity of vehicle interactions in a mixed-vehicle traffic flow differ from those in a typical traffic flow. This difference leads to greater potential conflicts and decreased efficiency in freeway merging zones, which involve a large amount of vehicle crossing behaviour. To avoid the deterioration of traffic status, cooperative control of safety and efficiency for mixed-vehicle traffic flow using connected and automated vehicles (CAVs) in freeway merging zones is proposed. First, a multi-objective nonlinear mixed-integer program model for cooperative safety and efficiency is presented at the vehicle level to optimize CAV’s behavioural decisions using historical predicted data. Second, a Transformer neural network is adopted to forecast the traffic state under different control weights, accounting for the dynamic characteristics of the traffic system. An adaptive weighting model is constructed to choose the optimal solution from the Pareto frontier derived from the multi-objective problem. To ensure the feasibility of vehicle-level decisions and to facilitate system-level optimization, CAVs are capable of sharing and coordinating their behaviour decisions through iterations. A typical scenario involving a two-lane freeway merging area is analysed, and the results show that the cooperative control strategy can effectively optimize the traffic state. Even at 20% CAV penetration rates, this strategy reduces total parking delays by 48.7% and time-integrated time-to-collision (TIT) by 72.2%.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2589234</guid>
    </item>
    <item>
      <title>Development and Assessment of Peak-Period Ramp Closure Strategies for Interstate Highways</title>
      <link>https://trid.trb.org/View/2571793</link>
      <description><![CDATA[With the ever-increasing congestion facing freeways, engineers must explore every possible tool at their disposal. Freeway ramp closures present a potentially underutilized approach for mitigating freeway traffic problems. Selecting and implementing such closures, however, presents a very difficult problem. Due to the potential public outcry and traffic disturbances that can result from misused ramp closure, special care must be given to ramp closure deployment. Even when a feasible ramp closure deployment is known, numerous possible implementation possibilities exists ranging from simply signing to manual and automatic gate operations. This report documents the research to develop a formal laboratorial analysis procedure for evaluating peak-period ramp closure strategies and produce guidelines for successful implementation. These guidelines consider the potential implementation solutions and their application for the Texas Department of Transportation (TxDOT), including the before-and-after-implementation system performance assessment and monitoring plans. The field implementation and evaluation of ramp closure was not a part of this research project. However, the field evaluation plan proposed in this report will provide guidance for undertaking such an endeavor.]]></description>
      <pubDate>Tue, 02 Sep 2025 10:34:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571793</guid>
    </item>
    <item>
      <title>Dynamic Routing on Freeway Systems Using Automatic Vehicle Identification (AVI) Data</title>
      <link>https://trid.trb.org/View/2567167</link>
      <description><![CDATA[This report examines issues related to identifying the potential routes and their associated attributes for an individual wishing to travel along the Houston freeway network. A dynamic approach is taken whereby the link travel time that is used in calculating the route travel time is based on the time the drivers arrive at a given link rather than the time when they began their journeys. The link travel times were calculated using Automatic Vehicle Identification (AVI) data from a test bed on U.S. 290. It was found that real-time link travel times are relevant, as compared to historical link travel times, for approximately 20 minutes into the future. In contrast, forecast link travel times are relevant, as compared to historical link travel times, for approximately 30 to 35 minutes on average. A prototype computer model has been developed for examining dynamic routing issues and tested on the Houston network. It was demonstrated that in certain situations, particularly those for longer distance trips, a driver has a choice of routes in the Houston network and that often the different route travel times are not statistically different. In this situation it may be best to allow an option whereby the routes and their attributes are provided to the driver rather than a recommendation of the best or fastest route.]]></description>
      <pubDate>Tue, 05 Aug 2025 11:40:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2567167</guid>
    </item>
    <item>
      <title>Deep Reinforcement Learning Freeway Controller Chooses Ramp Metering Over Variable Speed Limits</title>
      <link>https://trid.trb.org/View/2563664</link>
      <description><![CDATA[The benefits of controlling a freeway bottleneck using reinforcement-learning-(RL)-based ramp metering (RM) and/or variable speed limit (VSL) controllers are well established. However, in the event of using both RM and VSL to control the freeway, it is not clear how each method benefits the traffic stream in contrast to the other. We argue that, depending on traffic conditions, it may be better to use one and not both, or more importantly, to dynamically switch between the two. Moreover, a learning agent can automate the switch when warranted. In this paper, we offer intensive analysis and performance evaluations for RL as well as regulator-based RM and VSL controllers applied on both a Aimsun simulated hypothetical freeway network from literature and a real-world freeway on-ramp, extracted from Queen Elizabeth Way (QEW) located in Ontario, Canada with different levels of demand. The findings indicate that RM is more effective and beneficial than VSL in heavily congested scenarios as opposed to VSL, which can be beneficial in moderate and low congested scenarios. We also show that RL has the advantage of automatically prioritizing one control method over the other depending on traffic conditions. We demonstrate that in heavy congestion scenarios, the RL control agent that manages both RM and VSL clearly chooses RM over VSL.]]></description>
      <pubDate>Fri, 13 Jun 2025 09:13:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2563664</guid>
    </item>
    <item>
      <title>Evaluation of the Benefits of Traffic Surveillance and Control on the Gulf Freeway</title>
      <link>https://trid.trb.org/View/2548950</link>
      <description><![CDATA[Freeway surveillance and control have been used to improve traffic operation on and near the Gulf Freeway in Houston, Texas. Several research reports previously issued by the Texas Transportation Institute have investigated the nature and types of surveillance and control and have documented their effects on the Gulf Freeway. This report gives an economic evaluation of the loss of time resulting from freeway obstructions and an evaluation of the benefits of freeway surveillance and control.]]></description>
      <pubDate>Tue, 27 May 2025 10:12:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548950</guid>
    </item>
    <item>
      <title>Deterministic Aspects of Freeway Operations and Control</title>
      <link>https://trid.trb.org/View/2548953</link>
      <description><![CDATA[An automatic traffic surveillance and control system is to be installed on the Gulf Freeway in Houston, Texas. A traffic surveillance system should involve the continuous sampling of basic traffic characteristics for interpretation by established control parameters, in order to provide a quantitative knowledge of operating conditions necessary for immediate rational control and future design. The control logic of a surveillance system, or any system for that matter, is that combination of techniques and devices employed to regulate the operation of that system. The analysis shows what information is needed and where it will be obtained. Then and only then can the conception and design of the processing and analyzing equipment necessary to convert data into operational decisions and design warrants be described. The purpose of this investigation is to establish some of the control parameters necessary to provide a quantitative knowledge of freeway operations and a rational basis for future freeway surveillance and control. Traffic operations should be defined, characterized and described as particular states of traffic flow, thus affording the means of developing rational control parameters.]]></description>
      <pubDate>Tue, 27 May 2025 10:12:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548953</guid>
    </item>
    <item>
      <title>Cost-Effectiveness Analysis of Freeway Ramp Control</title>
      <link>https://trid.trb.org/View/2548951</link>
      <description><![CDATA[This report is concerned with the evaluation of alternative freeway merging control systems from a cost-effectiveness standpoint. Alternative systems that were evaluated include: 1) Analog Satellite System, 2) Digital Satellite System, and 3) Digital Central Control System. The report also provides a methodology for evaluating the cost-effectiveness of freeway control systems. This methodology is consistent with a multilevel system design concept. The multilevel approach is directed towards establishing a hierarchy of control that results not only in an efficient system but one that can be implemented in stages. Each succeeding stage results in increased system sophistication and consequently an increase in cost. The cost-effectiveness of each of four stages (or levels) of control has been evaluated and is reported herein.]]></description>
      <pubDate>Tue, 27 May 2025 10:12:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548951</guid>
    </item>
    <item>
      <title>Capacity-Demand Analysis of the Wayside Interchange on the Gulf Freeway</title>
      <link>https://trid.trb.org/View/2548956</link>
      <description><![CDATA[Studies have indicated that to improve the traffic flow on freeways during the peak period, some control of the interchange traffic is required. In the study of the Gulf Freeway in Houston, Texas, several control procedures are under consideration which will encourage, or force, greater use of the frontage roads and arterial streets by freeway traffic. This increased travel on the street system must be considered in evaluating the overall effect of control on traffic operations. In the systems analysis of traffic flow on the Gulf Freeway, the Wayside Interchange has been designated as one of the critical areas of restrictive capacity. The initial stages in the development of freeway traffic control systems required that serious consideration be given to improving the capacity of this interchange on the frontage roads and cross street. As the control systems develop and broaden, other critical interchanges will be studied with the same objectives and by the same technique reported in this paper. As part of the Design Phase of the Level of Service Project, studies were conducted at this interchange with the objective of determining the means of increasing the capacity of the frontage roads without impairing the movement of traffic on the cross street. The results of the studies indicate that the operation can be improved in three ways: 1. Assign more right-of-way to the critical approaches; 2. Improve the operation of the vehicle queues by decreasing the starting delays and average headways; and 3. Remove traffic which can be rerouted. The modifications in design, control and operation of the interchange necessary to effect these improvements are presented in this report for the consideration of the Texas Highway Department.]]></description>
      <pubDate>Tue, 27 May 2025 10:12:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548956</guid>
    </item>
    <item>
      <title>Some Considerations of Vehicular Density on Urban Freeways</title>
      <link>https://trid.trb.org/View/2548954</link>
      <description><![CDATA[This report includes parts of a general study of the various aspects of vehicular density for use in the control of freeway traffic. Density is herein considered singly as a possible control element of a freeway operational system. This study provides information which may be useful for freeway control methods. Electronic equipment manufacturers should be encouraged by this study to develop density sensing systems. The scope of this report specifically involves principal study areas described as follows: 1. The principal features of existing methods used to measure or estimate density are reviewed. 2. Results of aerial photography studies of the Gulf Freeway in Houston, Texas, are utilized to show how density may be related to volume as well as to certain geometric features of the freeway facility. 3. A field study method is described which yields continuous values of vehicular concentration on certain sections of a freeway. The results of several of these density-trap studies are analyzed for the purpose of determining the variability and frequency distributions of freeway concentration and relating the length of sensing sections to the variability of concentration. 4. The analysis of the data demonstrates a means of establishing optimum, or critical, freeway concentration values and provides a means of identifying critical, or bottleneck, sections at a freeway which exhibit recurring high densities.]]></description>
      <pubDate>Tue, 27 May 2025 10:12:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548954</guid>
    </item>
    <item>
      <title>Stochastic Considerations in Freeway Operations and Control</title>
      <link>https://trid.trb.org/View/2543333</link>
      <description><![CDATA[The objectives of this study were to: 1. Formulate and test a moving-queue model of traffic flow based on the assumption that the lengths of moving queues reflect congestion, just as stationary queues reflect congestion in classical queuing theory; 2. Describe freeway congestion quantitatively; 3. Suggest which of the traffic characteristics and parameters that reflect congestion quantitatively are capable of automatic detection, measurement and control, as a step toward automatic freeway surveillance; and 4. Generalize the results of this study to the design of future freeway facilities.]]></description>
      <pubDate>Wed, 21 May 2025 14:12:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2543333</guid>
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