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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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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Safety Performance of Safe System Treatments for Corridors and Intersections that May Impact Capacity</title>
      <link>https://trid.trb.org/View/2712178</link>
      <description><![CDATA[Transportation agencies are increasingly adopting the Safe System Approach (SSA), which emphasizes a holistic approach to eliminating all fatal and serious traffic injuries on road segments and at intersections. Historically, efforts to reduce congestion often led to the addition of through lanes, implementation of short auxiliary lanes at intersections to facilitate right turns and through movements, and other treatments. However, agencies are now exploring lane reductions—commonly referred to as right-of-way reallocation, road diets, or reconfigurations—to improve safety. In some cases, roads previously widened to accommodate peak-hour traffic are being reevaluated through the lens of the SSA.

Implementing these changes requires a comprehensive understanding of the associated safety impacts and the ability to predict crash outcomes resulting from modifications to roadway capacity. Safety outcomes associated with capacity modifications carry substantial weight in routine planning and operational decisions. Current evidence, however, is limited, and context-specific effects, especially for vulnerable road users, are not well quantified. Additional research is therefore needed to quantify how short auxiliary lanes and cross-section changes affect exposure, likelihood, and severity.

The objectives of this research are to (1) quantify the safety impacts of SSA treatments that may affect roadway capacity and (2) develop analysis methodologies, such as crash modification factors (CMFs) and crash prediction models, to evaluate how these treatments affect crash exposure, likelihood, and severity across all road users and crash types, including pedestrian and bicyclist crashes. The research results can enable planners, designers, traffic engineers, and other decision-makers to make evidence-based choices that balance safety with operational and capacity needs.]]></description>
      <pubDate>Tue, 09 Jun 2026 15:00:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712178</guid>
    </item>
    <item>
      <title>Traffic Breakdown Prediction Beyond Stochastic Capacity Models: Machine Learning Approach</title>
      <link>https://trid.trb.org/View/2709302</link>
      <description><![CDATA[This study focuses on the application of machine learning models for a short-term prediction of traffic breakdowns on freeways. Traffic breakdowns, which occur when demand exceeds the momentary capacity, are typically predicted using probabilistic methods, but these approaches do not fully capture the short-term variability inherent in traffic flow. In this work, the methodology is advanced by employing machine learning techniques to predict traffic flow conditions, relying exclusively on lane-by-lane analysis of current detector data without utilizing any upstream or downstream information. Traffic conditions are classified into distinct categories, including breakdowns, and a neural network is employed to predict them, providing a robust method for identifying intervals in which the momentary capacity of a freeway is reached. Capacity estimates from the neural network are then compared with those from widely accepted statistical methods, revealing minimal differences, and thereby validating the effectiveness of the neural network approach in capacity analysis. Moreover, comparing the short-term flow conditions predicted based on the two approaches revealed superiority of neural network in providing significantly more accurate classifications. These findings highlight the significant potential of machine learning methods as powerful tools for momentary capacity estimation, with applications across various transportation systems management and operations strategies.]]></description>
      <pubDate>Wed, 03 Jun 2026 09:07:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2709302</guid>
    </item>
    <item>
      <title>Dynamic Lane Configuration for Improved Traffic Efficiency on Motorways</title>
      <link>https://trid.trb.org/View/2658925</link>
      <description><![CDATA[The need for additional capacity in motorway networks during periods of high demand is unavoidable if congestion is to be prevented. Increasing capacity by building new roads is often infeasible, leaving operation-based traffic control measures as the primary approach to exploit the existing infrastructure. In this paper, the novel concept of dynamic lane configuration is introduced, which opens a new avenue in motorway traffic control that harnesses the infrastructure for traffic improvement. The lateral capacity of the existing motorway infrastructure is under-utilized due to lanes that are much wider than the vehicle’s width. Dynamic lane configuration suggests that while current wide lanes ensure safety during high-speed driving, lower speed limits can be actively imposed during times of high traffic demand, allowing the lane width to be reduced, thanks to the reduced required lateral gap between vehicles at lower longitudinal speeds. By narrowing the lanes prior to congestion, it is possible to reclaim wasted space and add lanes to the road, leading to a dynamic capacity increase during the operation. This dynamic infrastructure layout with demand-responsive lane configuration during operation bridges the traffic management and infrastructure design. A model-based optimal control approach is developed to model the dynamic lane configuration and to define the times and locations of changing lane configuration. The proposed approach is tested in a simulation environment on two different motorway networks, each with a different configuration and demand profile. The promising results indicate the potential of the proposed approach in congestion mitigation and reducing travel time.]]></description>
      <pubDate>Thu, 28 May 2026 17:09:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658925</guid>
    </item>
    <item>
      <title>Impact of Roadside Friction on Traffic Flow Characteristics at Midblocks under Mixed-Traffic Conditions: Comprehensive Review</title>
      <link>https://trid.trb.org/View/2705422</link>
      <description><![CDATA[Roadside friction, the resistive forces that are exerted through traffic by activities along the carriageway edge or shoulder, significantly influences traffic performance. These activities reduce effective roadway width, leading to speed reductions, capacity constraints, poor levels of service (LOS), and safety hazards. Although developed countries with homogeneous traffic conditions manage such factors effectively, mixed-traffic conditions in regions like India exacerbate their impact. Addressing friction elements is crucial for developing effective traffic management strategies, improving road efficiency, and refining highway capacity manuals. This paper reviews three decades of research on midblock road sections, examining side friction’s influence on key traffic parameters such as speed, capacity, delay, congestion, and LOS. Additionally, it evaluates different methodologies employed to quantify these effects, including regression models, simulation techniques, and capacity adjustment factors. Moreover, the authors made an effort to identify and delineate the research gaps, with the intent of opening new avenues of study on the multifaceted impacts of side friction.]]></description>
      <pubDate>Tue, 26 May 2026 16:57:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2705422</guid>
    </item>
    <item>
      <title>MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC)</title>
      <link>https://trid.trb.org/View/2663009</link>
      <description><![CDATA[Commercial availability of vehicle automation has become mainstream. Most of today’s new vehicles can perform longitudinal car following autonomously via Adaptive Cruise Control (ACC). Field experiments demonstrate that today’s commercially available ACC vehicles provide similar headways and capacities as human-driven vehicles on freeways under steady-state and free-flow conditions. However, field tests also demonstrated that the design of today’s commercially available ACC vehicles can lead to further capacity reduction when operating in non-steady-state conditions where queues are present and speeds frequently fluctuate. These experiments generated MicroSimACC, a comprehensive set of field data that encompasses full speed range car following with interruptions from lane change manoeuvres. This will benefit the research community by providing benchmark data for developing models to be integrated into microscopic simulations for more prospective analyses and planning.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663009</guid>
    </item>
    <item>
      <title>Roadspace allocation between autos, buses, and bicycles with heterogeneous demand</title>
      <link>https://trid.trb.org/View/2661801</link>
      <description><![CDATA[The allocation of road space among different transport modes has long been a key issue in urban planning, yet it lacks solid theoretical foundations. This paper investigates the optimal allocation of road space among three transport modes: private vehicles, buses, and bicycles, for overall system performance. The travel time for each mode is determined based on travel speed derived from fundamental diagrams (FDs). Changes in bus travel time are the least sensitive to excessive demand, as the number of buses is only indirectly affected by demand. A mode choice equilibrium framework based on deterministic user equilibrium is proposed to handle cases with and without heterogeneity in passengers’ waiting time thresholds for buses. Analytical and numerical results reveal that the optimal road space allocation strategy depends on the demand level. Without considering passenger heterogeneity, the optimal strategy is a corner solution - allocating all road space to one of the three transport modes. When heterogeneity is considered, low and medium demand levels result in all space being allocated to private vehicles and bicycles, respectively. For high demand levels, the optimal solution is a non-corner solution, where road space is allocated to both buses and bicycles, and the proportion allocated to buses increases as demand rises. The initial road space share for buses significantly influences system performance. Crucially, this induces either a virtuous or vicious cycle that impacts public transport usage. The threshold for this effect is around 0.4, meaning that allocating approximately half of the road space to buses is critical, and this threshold decreases as demand increases. This study highlights the importance of tailoring road space allocation strategies to demand levels to maximize transport efficiency.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2661801</guid>
    </item>
    <item>
      <title>Capacity Analysis and Safety Assessment of Unsignalized Intersection Using Conflict Technique</title>
      <link>https://trid.trb.org/View/2581532</link>
      <description><![CDATA[Intersections pose special safety concerns because of the high probability of critical conflicts resulting from unsafe driver actions and maneuvers. The absence of movement priorities, lack of lane discipline, forced entry by non-priority movements, etc., at unsignalized intersections violate the assumptions involved in capacity calculation. A key aspect of this study is to analyze conflicting flows at unsignalized intersections, which vary depending on site conditions and geometrical features in heterogeneous traffic environments and to estimate movement capacity at unsignalized intersections. At unsignalized intersections, vehicles from different directions cross and turn simultaneously, resulting in severe vehicle-vehicle conflicts. Thus, traffic safety is an important aspect to be evaluated at unsignalized intersections. The study also aims at conducting a safety assessment at unsignalized intersections using the microsimulation model (VISSIM) coupled with the Surrogate Safety Assessment Model (SSAM). The study found that SSAM is adaptable to intersections of varying geometry and serving heterogeneous traffic.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581532</guid>
    </item>
    <item>
      <title>Empirical Validation of Continuum Traffic Flow Model of Capacity Drop at Sag and Tunnel Bottlenecks</title>
      <link>https://trid.trb.org/View/2661735</link>
      <description><![CDATA[This study validates the continuum traffic flow model of capacity drop at sag and tunnel bottlenecks, as proposed by Jin (Transp. Res. B Methodol. 107, 41–56, 2018) and Wada et al. (Transp. Res. C Emerg. Technol. 113, 260–276, 2020), through empirical analysis. Specifically, after addressing the limitations in the existing studies, we calibrate the model using data from multiple congestion events at several expressway bottlenecks. We then demonstrate that the model can reproduce the observed speed recovery near the head of the queue, and assess whether both estimated bottleneck capacities and locations are consistent with observed traffic conditions. Finally, as an application of the calibration results, we examine the relationship between the spatial changes in the estimated traffic capacity and longitudinal gradients.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2661735</guid>
    </item>
    <item>
      <title>Impact of Autonomous Vehicles on Capacity of a Two-Lane Highway</title>
      <link>https://trid.trb.org/View/2579833</link>
      <description><![CDATA[An autonomous vehicle (AV) or driverless car ensures safety using advanced sensor and positioning technologies with little or no human input. With numerous emerging technologies, it is important to know the potential capacity effects of AVs to aid our decision-making process with future investments. As AVs are not widely used especially in developing countries like India, it is difficult to study the behaviour of AVs and their interactions with other vehicles in the field. Hence, the mid-block section of a two-lane highway incorporating AVs is simulated using VISSM in this study to analyse how AVs impact the capacity of the highway. Passenger cars are replaced by autonomous cars in the model and the model is calibrated using travel time as measure, and the change in the capacity for various penetration rates of AV is estimated. The study gave promising outputs in terms of capacity enhancement and found that the introduction of the AVs can enable better utilization of the available road space.]]></description>
      <pubDate>Tue, 28 Apr 2026 16:55:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579833</guid>
    </item>
    <item>
      <title>Capacity and Level of Service Estimation of a Roundabout: A Case Study in Silchar</title>
      <link>https://trid.trb.org/View/2671584</link>
      <description><![CDATA[Population growth in Silchar has necessitated the development of efficient transportation systems to alleviate traffic congestion and enhance mobility. This research project focuses on the capacity and level of service (LOS) estimation of a critical roundabout in the city, which is crucial for regulating traffic flow and ensuring smooth vehicular movement. The study aims to evaluate the roundabout’s capacity and LOS to identify areas for improvement and optimization. A comprehensive analysis was conducted using field observations and traffic engineering methodologies, including Indo-HCM 2017, IRC: 65–1976, and Highway Capacity Manual (HCM) 2010 guidelines. Capacity and LOS estimation involved calculating critical gaps and clearance times between minor and major road vehicles using the INAFOGA and clearance time methods for the Indo-HCM method. The IRC method estimated roundabout capacity based on weaving traffic proportions, while HCM 2010 used average control delay. Findings indicate that the roundabout’s capacity, as estimated by Indo-HCM, is 2414 PCU/h with a corresponding LOS B, reflecting efficient functionality with moderate delays. IRC: 65–1976 methodology suggests a capacity of 2884 PCU/h, essential for effective traffic flow. HCM 2010 analysis shows varying capacities for different approaches varying between 792 PCU/hr and 977 PCU/hr, with LOS of C, A, B, and A for four approaches. The outcomes are expected to guide urban planners, traffic engineers, and policymakers in making informed decisions to enhance the transportation network of Silchar, contributing to the city’s sustainable development. Integrating three methodologies enhances accuracy and reliability in transportation planning and traffic management.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671584</guid>
    </item>
    <item>
      <title>Impact of Localized Rain Events on traffic Breakdown</title>
      <link>https://trid.trb.org/View/2682779</link>
      <description><![CDATA[Understanding the relationship between weather events and freeway traffic flow is important for enhancing transportation infrastructure resilience. This study investigates the effects of localized rain events on freeway capacity, with a specific focus on traffic breakdowns. Analysis of connected vehicle data under varying rain conditions reveals that traffic breakdowns are most likely to occur at the boundaries of rain zones. Shortly, localized rain events disrupt traffic more significantly than widespread, persistent rainfall, due to a habituation effect where drivers adjust to prolonged adverse conditions. Unlike previous studies which broadly examine the impact of rain on traffic flow, this research focuses on the distinct effects of localized rain events, providing a more nuanced understanding of precipitation-induced disruptions. The findings from this study could offer practical guidance for improving traffic management strategies, optimizing road design, and enhancing driver safety during adverse weather events.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2682779</guid>
    </item>
    <item>
      <title>Multiclass First-in-First-Out Cell Transmission Model (MF-CTM): A Traffic Flow Model to Estimate Dynamic Road Capacity due to Connected Autonomous Vehicles Operating in Mixed Traffic</title>
      <link>https://trid.trb.org/View/2682061</link>
      <description><![CDATA[Connected Autonomous Vehicle (CAV) is a new technology that can operate without human intervention and able to communicate with other CAVs and connected infrastructure. Due to its ability, CAV is expected to create significant change in traffic management and creates benefits e.g., increasing road traffic performance, road safety improvement. Before CAV has a significant share on the road, there will be a transition period where CAV co-exists with normal vehicle (NV). The purpose of this study is therefore to develop a tool, based on cell transmission model (CTM), to assess the impact of CAV in mixed traffic. We name the model as multiclass first-in-first-out cell transmission model (MF-CTM). The model has three distinct features, namely: i) First-in-First-Out (FIFO), ii) Dynamic Maximum Flow Rate, and iii) Dynamic Maximum Cell Occupancy. In this study, we present the mathematical formulas, algorithm, and numerical illustration of the MF-CTM for a one-lane single road link. By simulation using MF-CTM, we demonstrate that the model can: i) represent decreasing queue length and dissipation time during congestion as CAV share increases, ii) maintain the order of vehicle groups (traffic cohort) during congested condition, iii) represent fluctuation in link outflow rates due to fluctuating CAV shares in the traffic. For further studies, the formulations and algorithm of MF-CTM can be extended into networks and include more elements e.g., signalised intersections, bus lanes, etc. In the future, we expect that the MF-CTM can be a useful tool to assess the effectiveness of traffic management measures involving CAVs.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2682061</guid>
    </item>
    <item>
      <title>Traffic Dynamics of Vehicles Passing Each Other on Bidirectional Undivided Narrow Roads</title>
      <link>https://trid.trb.org/View/2646845</link>
      <description><![CDATA[This study investigates traffic dynamics on bidirectional undivided narrow roads. A novel heuristic-based passing (HP) model is proposed to microscopically model the complex passing maneuvers. Considering both perceived visual stimuli and steering imprecision, the model incorporates two heuristics that determine the driving direction and speed in the navigation of the most direct but unobstructed route. Real-world experiments analyzing the passing process of two vehicles on undivided narrow roads with varying widths were conducted. The results reveal that vehicles decelerated, veered toward the roadside to facilitate an oncoming vehicle’s passage and then readjusted to the center of the road, providing empirical support to the proposed HP model. In addition, as the road width increased, both the passing speed and clearance distance increased. The calibrated HP model could replicate the trajectories of the passing vehicles, demonstrating its accuracy. Real-world field observations were made at two undivided roads of varying widths and opposing traffic densities to investigate the macroscopic traffic patterns under the influence of lateral friction. The results showed that, on the undivided narrow road, when the traffic density in the travel direction was relatively low, the presence of high-density opposing traffic significantly reduced the speed of vehicles in the travel direction. Moreover, the proposed microscopic HP model well replicated the macroscopic traffic flow patterns. Overall, the results of this study enhance the understanding of traffic dynamics in the passing process on undivided narrow roads, offer insights for local road geometric design, and help identify sources of congestion evolution. © 2025 The Author(s)]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646845</guid>
    </item>
    <item>
      <title>Impact of cooperative adaptive cruise control vehicles on freeways: analysis of merging zone capacity</title>
      <link>https://trid.trb.org/View/2643279</link>
      <description><![CDATA[This research proposed an analytical capacity model for mixed traffic flow at freeway merging zones, consisting of Connected and Automated Vehicles (CAVs) equipped with Cooperative Adaptive Cruise Control (CACC) and Human-driven Vehicles (HVs). The model quantifies both the capacity loss caused by the impedance of CACC platoons on merging traffic and the capacity gain from reduced headways within the platoons. To ensure its reliability, the model was validated through microscopic simulations, demonstrating an accuracy level exceeding 80%, regardless of changes in traffic conditions. These conditions include CAV penetration rates, ramp demand levels, and the maximum allowed platooning size.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643279</guid>
    </item>
    <item>
      <title>Conflict-based before-after safety evaluation of changing single lane LWA into dual lanes LWA at signalized intersection</title>
      <link>https://trid.trb.org/View/2643255</link>
      <description><![CDATA[This study aims to evaluate the safety effectiveness of changing a single-lane Left-turn waiting area (LWA) to an dual-lane LWA at signalized intersections using conflict-based before–after safety analysis. Traffic conflicts are obtained from treatment and control sites at two intersections in Nanjing, China. A hierarchical Bayesian generalized extreme value distribution (HB-GEV) model is developed for the safety analysis. The model combines traffic conflicts at different sites and periods and incorporates them into a uniform model. The treatment effectiveness is measured by the odds ratio calculated from the HB-GEV model. Result shows that treatment effectiveness varies from 45% to 52% in terms of the reduction in estimated annual crashes. Analysis of the heatmaps shows that traffic conflict distribution becomes more concentrated after adding a left-turn lane to the LWA. The findings of the study indicate a considerable improvement in safety after the implementation of an dual-lane LWA at signalized intersections.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643255</guid>
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