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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>Geofencing to Accelerate Digital Transitions in Cities: Experiences and Findings from the GeoSence Project</title>
      <link>https://trid.trb.org/View/2671014</link>
      <description><![CDATA[Geofencing is a tool that offers innovative solutions to manage and control traffic, transport, and mobility. The technology enables cities to define digital zones and to create dynamic rules for mobility within these zones. Here we report on three geofencing use cases, their results and lessons learned that were conducted as part of the joint European project GeoSence. In the city of Gothenburg, the performance of a geofencing-based retro-fitted intelligent speed assistance system was tested and evaluated in 20 vehicles of publicly procured transport services to support drivers in complying with new speed regulations around schools. In Munich, geofencing was used to implement and enforce a new station-based parking regulation for shared e-scooters in the city’s old town. Thirdly, in Stockholm preconditions, processes and workflow for continuous changes and updating of the underlying digital geo-data bases were analysed to better understand institutional and practical challenges to implement geofencing-based digital transitions in future. Findings from the use cases and project accompanying surveys are evaluated regarding the general topics of transport management, including issues of data sharing and management, stakeholder involvement, technical & vehicle readiness, feasibility of technical platforms, as well as institutional problems related to governance, policies, resources and the acquiring of necessary competencies.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671014</guid>
    </item>
    <item>
      <title>Motorway Traffic Flow Optimization: From Theory to Practice</title>
      <link>https://trid.trb.org/View/2670989</link>
      <description><![CDATA[Variable speed limits (VSL) are currently being introduced on Ireland’s M50 motorway on a phased basis. To manage general everyday congestion associated with peak-period traffic, proactive speed management plans have been developed to allow control room operators to initiate speed reductions to optimize traffic flows and reduce the impact of traffic flow breakdown. The national roads authority in Ireland, Transport Infrastructure Ireland (TII), collects significant levels of data from the M50, and this paper outlines how the application of traffic-flow theory to the measured data has been used to identify when certain sections of the road are approaching capacity. This has enabled the provision of real-time data-driven alerts to control room operators, to identify when proactive speed management plans should be initiated. The measured data is then used to assess the effectiveness of the VSL plans, and it is shown that improvements in throughput are being achieved, along with a reduction in congestion and shockwave behavior. The findings of this study will ultimately inform the automation of proactive speed management plans on the M50.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670989</guid>
    </item>
    <item>
      <title>Intelligent Speed Assistance Guide for State Highway Safety Offices</title>
      <link>https://trid.trb.org/View/2720300</link>
      <description><![CDATA[Speeding remains one of the most persistent and deadly threats on U.S. roadways, accounting for more than 11,000 deaths in 2024, and 125,000 fatalities over the last decade. One promising countermeasure to help address speeding behavior is Intelligent Speed Assistance (ISA) technology, which uses real-time Global Positioning System (GPS) data to detect the speed limit and proactively alert (or limit) the driver if they are speeding, can reduce speeding and help promote long-term safe driving behaviors.
The Governors Highway Safety Association (GHSA) recently documented a growing number of examples of ISA’s effectiveness at the local level. In New York City, a pilot program involving 500 fleet vehicles saw a 64% reduction in speeds substantially above speed limits. A District of Columbia school bus pilot logged 10,000 miles with zero speeding events.
European research has shown that ISA can reduce crash risk and lessen the severity of injuries, particularly in areas with changing speed limits or heavy pedestrian activity. A 2019 policy report from the European Transport Safety Council estimated that ISA could cut road deaths across Europe by approximately 20%. Another study projected that equipping all vehicles with mandatory active ISA could reduce injury and fatal crashes by 20% and 37%, respectively.
Given the potential for wide adoption of ISA to substantially reduce speeding-related fatalities and serious injuries, research is needed to identify ways for state highway safety offices (SHSOs) to advance the use of this technology.

OBJECTIVE: The objective of this research is to develop a guide that supports efforts by SHSOs to: 1) Conduct comprehensive stakeholder assessment to identify which groups have the greatest need for education and which hold the most influence over its adoption. 2) Develop a core set of educational active ISA materials or leveraging materials available from other sources. 3) Ensure that SHSO staff have a strong foundational understanding of active ISA. Staff training should cover how active ISA works, its effectiveness as demonstrated in peer-reviewed research, relevant policy considerations and communication strategies tailored to different audiences. 4) Establish clear metrics and evaluation processes allows SHSOs to measure the effectiveness of educational initiatives and outreach efforts. 5) Engage with key stakeholders to advance pilot programs. 6.) Develop guidelines and implementation frameworks for pilot projects that help SHSOs evaluate and demonstrate effective strategies for modifying speeding behavior through ISA technologies, including  recommendations on target driver populations, stakeholder coordination, public communication, data collection, performance measures, privacy considerations, and evaluation methodologies to support broad adoption.
]]></description>
      <pubDate>Thu, 02 Jul 2026 20:16:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720300</guid>
    </item>
    <item>
      <title>Design, analysis, and experiments of longitudinal speed active disturbance rejection controller considering multi-source disturbances for low-speed park intelligent vehicles</title>
      <link>https://trid.trb.org/View/2680771</link>
      <description><![CDATA[Generally, uncertain factors such as air resistance, tire deformation, and road resistance will be considered in the speed tracking controllers of intelligent vehicles with complex longitudinal drive model. However, the dynamics induced by the above factors aren’t obvious for low-speed park scenarios, while the complex drive model is difficult to model with high accuracy and will introduce more parameters in practical applications. In view of this, a speed active disturbance rejection controller for low-speed intelligent vehicles is proposed. Firstly, a speed tracking kinematics model is established, of which the system delay, modeling, and external environment are regarded as the uncertain total disturbances in low-speed environments. Then, a linear extended state observer (LESO) is designed to estimate the unknown total disturbances and compensate for the control system in real time. Meanwhile, the proportional differentiation (PD) controller is designed to jointly tune the system stability with the LESO, thus forming a linear active disturbance rejection control (LADRC). Finally, the convergence of the discrete LESO and the consistent boundedness of LADRC are analyzed, respectively. The software-in-the-loop (SiL) experimental results show that the LADRC controller is effective. Also, a semi-physical hardware-in-loop (HiL) platform is built and results confirm the good robustness of LADRC. Further, the LADRC, proportional integral derivative (PID) and PD controllers are compared in the real vehicle test, and results show that the superiority of the LADRC controller.]]></description>
      <pubDate>Thu, 25 Jun 2026 09:10:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680771</guid>
    </item>
    <item>
      <title>Intelligent Speed Assistance: A New Tool for Safer Roads: A Guide for State Highway Safety Offices</title>
      <link>https://trid.trb.org/View/2712652</link>
      <description><![CDATA[Intelligent Speed Assistance (ISA) is an in-vehicle system that identifies the posted speed limit on a given road and compares it with the vehicle’s current speed. To do this, ISA draws on several complementary technologies: Global Navigation Satellite Systems (GNSS), which pinpoint the vehicle’s exact location; digital speed limit maps, which provide information on the applicable speed limit for that location; traffic sign recognition cameras, which verify speed limit signs in real time; and human–machine interface (HMI), which delivers alerts or interventions to the driver. ISA has been shown to reduce crash risk and lessen the severity of injuries, particularly in areas with changing speed limits or heavy pedestrian activity. This report discusses speed management, ISA benefits, piloting and regulating ISA, key active ISA users, the role of state highway safety offices, an ISA implementation roadmap, and funding ISA equipment and programs.]]></description>
      <pubDate>Mon, 22 Jun 2026 07:23:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712652</guid>
    </item>
    <item>
      <title>Speed Management Countermeasure Selection and Process Guidance</title>
      <link>https://trid.trb.org/View/2716606</link>
      <description><![CDATA[Higher speed increases the risk of a fatal or serious crash and reduces the likelihood of survival. The Massachusetts Department of Transportation (MassDOT) seeks to enhance its design and process guidance to help municipalities achieve speed management objectives. This project aims to develop methods and guidance in three areas: 1. Develop a method to systemically identify current and future areas of speed concern; 2. Create guidance for the selection of speed management countermeasures given particular roadway and context conditions; 3. Create guidance about how to execute a municipal speed management program and implement speed management countermeasures.]]></description>
      <pubDate>Thu, 18 Jun 2026 09:44:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2716606</guid>
    </item>
    <item>
      <title>The effect of section speed control on vehicle speeds at a road construction zone</title>
      <link>https://trid.trb.org/View/2676431</link>
      <description><![CDATA[Road construction zones present heightened safety risks due to complex traffic organization. This study investigates the influence of section speed control (SSC) on driver behaviour in such environments using a naturalistic driving study (NDS) approach. The methodology relied on dashboard camcorder recordings combined with GPS data to analyse vehicle speeds, distances between vehicles, and traffic rule compliance before, during, and after SSC operation. Before SSC installation, 97.3% of overtaking vehicles exceeded the speed limit, with speeds reaching up to 130 km/h and an average excess of 32 km/h. After SSC was introduced, average speeds dropped from 103 km/h to 81 km/h, although some vehicles still exceeded the limit, with a maximum speed of 106 km/h. The system also notably reduced excessive speeding among lorries, 40.7% of which had previously exceeded the limit. Amongst other observations, particularly disturbing were 31 instances of lorries overtaking in designated no-overtaking zones, clearly disregarding posted traffic signs. The key finding was the immediate return to pre-installation speed levels once SSC was removed, highlighting a significant drawback: while SSC effectively reduced speeding and improved compliance during its operation, it failed to produce lasting changes in driver behaviour. This suggests that while such a measure as SSC can enhance road safety in the short term, additional measures may be necessary to sustain its impact in road construction zones. Additionally, the study shows that the applied NDS methodology provides an easy and effective means to assess driver behaviour under real-world conditions.]]></description>
      <pubDate>Thu, 18 Jun 2026 09:05:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2676431</guid>
    </item>
    <item>
      <title>Robust dynamic real-time control strategies for high-frequency bus service: a multi-agent reinforcement learning framework</title>
      <link>https://trid.trb.org/View/2701209</link>
      <description><![CDATA[This study addresses the multifaceted challenge of ensuring the regularity of bus services, minimizing bus bunching, and facilitating synchronized bus connections across routes. An enhanced multi-agent reinforcement learning algorithm, namely the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, is proposed to implement real-time control strategies for addressing these issues simultaneously. The merit of the modified MADDPG algorithm lies in its ability to continuously learn while adeptly navigating the non-stationary operating nature of bus system networks. A case study of a bus corridor is used to train and test the algorithm. Four robust scenarios, each presenting varying degrees of travel time and dwell time variations, are designed to assess the algorithm’s robustness. Results indicate that the MADDPG algorithm can significantly increase the likelihood of synchronized bus transfers across multiple routes by two or three times while maintaining the service reliability on each route. Moreover, the flexibility of the MADDPG algorithm in training bus policies allows it to effectively adapt to up to 90% variations in bus travel times and demand changes, even amid disruptive events in real-world scenarios.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701209</guid>
    </item>
    <item>
      <title>Model-based variable speed limit control on wireless charging lanes: Formulation and algorithm</title>
      <link>https://trid.trb.org/View/2618117</link>
      <description><![CDATA[This paper addresses the variable speed limit (VSL) control problem on wireless charging lanes (WCLs). We first introduce a predictive model to describe the evolution of both traffic flow and the state of charge of electric vehicles, considering the impact of VSL control. The model is formulated as a piecewise affine system through various linearization techniques. Subsequently, we propose a control model that accounts for both traffic and charging efficiencies. By employing a hybrid model predictive control approach, the control problem at each stage is cast as a mixed-integer linear programming (MILP) problem. To expedite the MILP problem, we propose an innovative learning-based algorithm, termed Learning from K-nearest Neighbors mode sequences (LKNMS). The algorithm identifies and eliminates predicted inactive system states (each represented by a binary variable) by leveraging historical solutions of the binary configuration. It thereby significantly reduces the size of the resulting MILP problem. We conduct a series of numerical examples on a 10.7 km WCL to test the proposed control model and algorithm. Our simulation results reveal that VSL control can significantly affect the charging efficiency of WCLs, particularly under light traffic conditions. Moreover, an inherent conflict between traffic efficiency and charging efficiency consistently arises on WCLs. The proposed algorithm significantly reduces the computational time of the MILP problem from 46 % of the 60s control cycle to 5∼12%, without compromising closed-loop performance, which implies strong potential for real-time implementation. We further test the proposed algorithm on a 26.75 km WCL to confirm its robust scalability to large-scale networks.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:14:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2618117</guid>
    </item>
    <item>
      <title>Development and Evaluation of Roadside Safety Systems for Motorcyclists—FY25</title>
      <link>https://trid.trb.org/View/2709271</link>
      <description><![CDATA[Motorcycle fatalities have continued to rise in the United States over the past decade. The design of roadways and roadside safety hardware often neglects consideration for the safety of motorcycle road users. Under fiscal year 2025 of TPF-5(482), two research tasks were prioritized for evaluation and consideration of motorcycle safety. The first research task evaluated four roadway design elements and their effect on motorcycle safety. This consisted of evaluating raised crosswalks, speed bumps, vertical drop-offs, and roundabouts using an exploratory analysis in BikeSim. Computer simulations were performed to evaluate the potential for loss of motorcycle vehicle stability when engaging these roadway design elements in different conditions and scenarios. Interaction with these roadway design elements with low roadway friction values was found to be the primary source of loss of motorcycle vehicle stability. The second research task developed and evaluated two design concepts for terminating a rubrail element in a motorcycle-friendly guardrail system. Both design concepts were modeled for finite element analysis and evaluated through computer simulations. Manual for Assessing Safety Hardware (MASH) Test 3-10 and 3-11 computer simulations were performed to evaluate the performance of the design concepts according to MASH Test Level 3. Both systems were found to indicate satisfactory crashworthy performance in the computer simulations.]]></description>
      <pubDate>Tue, 09 Jun 2026 10:56:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2709271</guid>
    </item>
    <item>
      <title>Valve Fleets: A Novel Control Method for Mixed Traffic Flow Regulation With Applications in Bottleneck Segments</title>
      <link>https://trid.trb.org/View/2659075</link>
      <description><![CDATA[This study proposes a mixed traffic flow control structure, utilizing multi-lane fleets composed of a small portion of connected and autonomous vehicles (CAVs) in mixed flow as mobile actuators. Multiple fleets formed within the mixed traffic flow feature a novel structure and a valve-like function that regulates both traffic volume and speed, referred to as “valve fleet”. Specifically, the travel speed and structural spacing of valve fleets are controllable parameters, which can regulate the surrounding traffic speed and the flow through the fleet based on the downstream traffic state to decongest bottlenecks. Then, a control-oriented mobile cell transmission model (MCTM) is developed to characterize the macroscopic traffic dynamics with the presence and influence of valve fleets and bottleneck areas on freeways. Moreover, a hierarchical framework for mixed traffic flow regulation is designed, where the upper-level traffic optimization model dynamically determines all fleets’ parameters in a rolling-horizon fashion to minimize total travel time and suppress local congestion. The decentralized lower-level fleet controller adopts model predictive control (MPC) to coordinate CAVs’ motions and handles interactions between CAVs and human-driven vehicles (HDVs). To evaluate the proposed method, we conduct microscopic experiments in the SUMO simulator to implement the proposed traffic control method in realistic traffic environments. The comprehensive comparison results demonstrate the proposed method’s superiority in enhancing traffic efficiency and alleviating congestion at freeway bottleneck segments.]]></description>
      <pubDate>Thu, 28 May 2026 17:09:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659075</guid>
    </item>
    <item>
      <title>Coordinated Multi-Agent Reinforcement Learning Method for Integrating Transit Signal Priority and Speed Guidance Control</title>
      <link>https://trid.trb.org/View/2659016</link>
      <description><![CDATA[Transit signal priority (TSP) is an effective approach to improve the service quality of public transit and increase its modal share. However, prioritizing transit vehicles can compromise overall traffic efficiency. To address this trade-off, speed guidance can be integrated to help non-transit vehicles pass through intersections smoothly. This paper proposes a novel multi-agent reinforcement learning framework, termed Co-ST, to coordinate TSP and speed guidance at the network level. Specifically, Co-ST features a joint policy architecture with dedicated actors for TSP and speed guidance, alongside a unified critic network that jointly evaluates and coordinates the dynamic interaction between the two control strategies. Co-ST incorporates a TSP-oriented multi-objective reward function balancing transit-specific goals, such as schedule deviation and bus priority, with general goals, including queue length, vehicle wait time, and travel speed. A novel co-optimization scheme is proposed to address the complexity inherent in multi-objective optimization. The effectiveness of Co-ST is validated through simulations on a real-world urban traffic network. Experimental results demonstrate that Co-ST consistently outperforms state-of-the-art benchmarks regarding key metrics such as intersection delays, queue lengths, and average vehicle speed, ultimately enhancing traffic efficiency for both transit buses and general traffic.]]></description>
      <pubDate>Thu, 28 May 2026 17:09:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659016</guid>
    </item>
    <item>
      <title>Implementing the Safe System Approach for Speed Management in Utah</title>
      <link>https://trid.trb.org/View/2685460</link>
      <description><![CDATA[Speed management is central to reducing fatal and serious injury crashes. The Safe System Approach, an emerging roadway safety paradigm in the United States, recognizes human error and vulnerability and focuses on minimizing crash severity through coordinated policy, design, and operational strategies. This research examines how Safe System Approach principles can be applied to speed management, with a focus on identifying practical countermeasures and implementation strategies relevant to the Utah Department of Transportation (UDOT). A compendium of practice was conducted to evaluate speed management countermeasures and document how cities and state Departments of Transportation are implementing Safe System Approach-based strategies. Thirty-two countermeasures were identified, including policy-based programs, automated enforcement, and roadway design treatments such as road diets, roundabouts, curb extensions, and gateway features. Findings show that implementing multiple, coordinated strategies is more effective than isolated interventions. The use of high-quality, context-sensitive speed and safety data supports proactive alignment of speed limits, roadway design, and safety goals. Establishing a clear Safe System Approach vision, supported by available federal and state tools, provides agencies with clear guidance for implementation. Based on the results of this research, several recommendations were provided for UDOT, including continuing to implement countermeasures for speed management in speed limit setting policies, evaluating current policies related to speed safety cameras in the state, incorporating Safe System Approach practices in the Strategic Highway Safety Plan, creating a speed management action plan, and placing a strong emphasis on community education tied to speed management.]]></description>
      <pubDate>Fri, 08 May 2026 17:09:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685460</guid>
    </item>
    <item>
      <title>Accounting for passenger loss in bus bunching reduction: a robust real-time speed control method</title>
      <link>https://trid.trb.org/View/2663004</link>
      <description><![CDATA[Bus bunching is a common phenomenon resulting from the inherent instability influenced by factors such as traffic and passenger behaviour. However, the issue of passenger loss caused by extended waiting time, is often overlooked despite being a significant concern for passengers. This paper addresses this problem by modelling passenger arrival and loss as a Markov birth–death process. We present a transit route model that incorporates passenger loss while considering additional factors, such as stochasticity, overtaking, passenger alighting, and bus capacity constraints. The primary objective of our model is to minimise passenger loss. To achieve this, we conduct an analysis about the characteristics of passenger loss. Under mild assumptions, we prove that passenger loss increases as the headways between buses exhibit greater variance. We also develop a robust optimisation (RO) method and corresponding algorithms to minimise passenger loss. To validate the effectiveness of our control method, we conduct numerical experiments using both computer-generated and real-world data. The results demonstrate that our method effectively reduces bus bunching, passenger loss, and waiting time compared to the existing literature.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663004</guid>
    </item>
    <item>
      <title>A Review of Safety and Operational Impacts of Various Speed Limits</title>
      <link>https://trid.trb.org/View/2581530</link>
      <description><![CDATA[Speed is the uttermost element influencing the incidence and ferocity of road accidents. The mitigation of the frequency of over speeding is seen as an essential goal for mitigating the number and severity of collisions, and the conventional method for doing so is through posted speed zoning or posted speed limit. Various speed control strategies are now being incorporated on roads to curb accidents’ frequency and risk. Some of the speed control strategies used worldwide are Uniform Speed Limit (USL), Differential Speed Limit (DSL), Variable Speed Limit (VSL), and Lane-Based Speed Limit (LBSL). In this paper, previous research based on the implementation of DSL on different classes of roads at various road stretches has been summarised, and all the conclusions are considered for an upcoming virgin project titled “Determining safety aspects of differential speed limit on Indian roads”.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581530</guid>
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