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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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    <item>
      <title>Use of Trajectory Option Sets to Support Collaborative Constraint Propagation</title>
      <link>https://trid.trb.org/View/2680964</link>
      <description><![CDATA[Air traffic flow management is supported by a highly distributed work system in which airline dispatchers and Federal Aviation Administration (FAA) traffic managers must coordinate. To support asynchronous coordination between a dispatcher and a traffic manager, the FAA has developed software that allows the flight operators to submit multiple, prioritized alternative flight plans. This set of alternative flight plans, submitted along with a filed route, is referred to as a Trajectory Option Set (TOS). And some airlines have now developed initial versions of software capable of generating and submitting such TOSs. This paper reports on cognitive walkthroughs with 5 dispatchers and 3 traffic managers on 5 scenarios designed to evaluate the operational concept, procedures and supporting FAA and airline software. The findings provide guidance for application of the concept of collaborative constraint propagation to support distributed work, as well as 42 recommendations for enhancing associated procedures and supporting software designs.]]></description>
      <pubDate>Sat, 02 May 2026 15:47:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2680964</guid>
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    <item>
      <title>Perceptions of change context in traffic management: An explorative study using expectancy theory</title>
      <link>https://trid.trb.org/View/2666951</link>
      <description><![CDATA[This study contributes to an increased understanding of how managers and employees perceive the change context in the field of traffic management, and what the behavioral implications are. Expectancy theory is adopted to explore how context influence the motivations of these actors. The findings reveals that motivation, being one contextual factor for change, is influenced by other contextual factors present on an individual, organizational and external level. Given that managers and employees often perceive these factors differently, and are therefore motivated by distinct drivers, effective change management should be tailored to reflect these diverse perspectives. To improve and align motivation for managers and employees in the change process, three propositions are suggested: (1) High expectancy is supported when project goals and scope align with project prevalence, and when adequate resources are perceived as available at the operational level. (2) High instrumentality requires that operative employees feel empowered to participate and be heard, while top-level managers and employees who lead project perceive the context as enabling leadership in changes. (3) High valence is achieved when the change is perceived as beneficial on all contextual levels (individual, organizational, and external).]]></description>
      <pubDate>Wed, 18 Mar 2026 09:00:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666951</guid>
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    <item>
      <title>Vehicle Re-Identification and Tracking: Algorithmic Approach, Challenges and Future Directions</title>
      <link>https://trid.trb.org/View/2553680</link>
      <description><![CDATA[Vehicle re-identification and tracking play a vital role in intelligent transportation systems as they enhance traffic management, improve safety, and optimize flow by precisely monitoring and analyzing vehicle movements across various locations. This technology enables the collecting of data in real-time, which allows for effective identification of incidents, enforcement of laws, and decision-making in urban planning. Deep learning techniques used in vehicle re-identification extract distinct characteristics to identify and match a vehicle across different camera perspectives. This bridges the non-overlapping field of camera views and forms a relationship between the detected vehicles. Tracking enhances this process by assigning a distinct identifier to the recognized vehicle, allowing for the creation of a continuous trajectory across the network for further analysis. Vehicle re-identification and tracking have made substantial progress in recent years as a result of the accelerated development of deep learning. Consequently, it is imperative to conduct a thorough examination of these chores. To provide a detailed picture of the research towards vehicle re-identification and tracking, this study provides the recent advancements of various datasets, and frameworks and strategies undertaken to perform these tasks. Specifically, the paper provides a comprehensive review of the different modes of re-identification of vehicles and further analysis. The paper also discusses the challenges and directions that can be taken in future for vehicle re-identification and tracking.]]></description>
      <pubDate>Thu, 10 Jul 2025 16:39:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2553680</guid>
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    <item>
      <title>Improved Incident Response through Coordinated, Interoperable Communications</title>
      <link>https://trid.trb.org/View/2536111</link>
      <description><![CDATA[This study aimed to conduct a needs assessment and performance evaluation of Traffic Incident Management (TIM) in Louisiana and identify areas for TIM improvement. The study also aimed to assess interoperability as a solution to communication gaps. The research team achieved this by performing evaluations and assessments of Louisiana’s TIM and communications during traffic incident response. The evaluation revealed several communication gaps and TIM needs. It was found that the Traffic Management Center (TMC) systems are not fully integrated with law enforcement Computer Aided Dispatch (CAD). As a result, TMCs sometimes rely on public CAD information to detect incidents and update their incident response plans. It was also found that dispatchers are responsible to receive information from on-scene first responders and coordinate interagency communication. While this arrangement functions well for small incidents, it may lead to delays and the loss of critical information for larger events. Additionally, the evaluation suggested that there is no direct communication between the TMC and other on-field first responders. Given the crucial role that TMCs play in TIM, this could lead to problems. The TMC relies on Motorist Assistance Patrol (MAP), or the dispatchers who operate at Public Safety Answering Points (PSAPs), to obtain and pass information. This means that in locations where MAP does not operate, the TMC may have to rely on one or more dispatchers for information sharing. This may in turn lead to delays in receiving updates on incident response and the subsequent update of traveler information systems relied upon by the general public. Receiving and passing information through multiple dispatchers may result in information loss and delays in receiving accurate messages. Several of these identified gaps are due to regulations and institutional arrangements that prohibit TMC operators from directly speaking to on-scene first responders or accessing law enforcement systems.]]></description>
      <pubDate>Mon, 21 Apr 2025 12:03:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2536111</guid>
    </item>
    <item>
      <title>A Reliability-Based Network Equilibrium Model with Electric Vehicles and Gasoline Vehicles</title>
      <link>https://trid.trb.org/View/2370930</link>
      <description><![CDATA[With the popularity of electric vehicles, they have become an indispensable part of traffic flow on the road network. This paper presents a reliability-based network equilibrium model to realise the traffic flow pattern prediction on the road network with electric vehicles and gasoline vehicles, which incorporates travel time reliability, electric vehicles’ driving range and recharge requirement. The mathematical expression of reliable path travel time is derived, and the reliability-based network equilibrium model is formulated as a variational inequality problem. Then a multi-criterion labelling algorithm is proposed to solve the reliable shortest path problem, and a column-generation-based method of the successive average algorithm is proposed to solve the reliability-based network equilibrium model. The applicability and efficiency of the proposed model and algorithm are verified on the Nguyen-Dupuis network and the real road network of Sioux Falls City. The proposed model and algorithm can be extended to other road networks and help traffic managers analyse traffic conditions and make sustainable traffic policies.]]></description>
      <pubDate>Wed, 22 May 2024 10:28:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2370930</guid>
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    <item>
      <title>Preparing for Virtual Operation of Traffic Management Systems</title>
      <link>https://trid.trb.org/View/1957082</link>
      <description><![CDATA[The ability to virtually manage and operate traffic management systems (TMSs) is no longer a luxury; it needs to be a capability of the system and core capacity of an agency’s operations program. It has become a necessity for agencies to work toward developing and sustaining these capabilities and having the resources necessary to remotely manage and operate their own or another agency’s TMS. Agencies continue to explore what organizational policies, procedures, capacity, resources, and capabilities may be needed to virtually manage and operate their TMSs to support day-to-day traffic management, planned (e.g., concerts, festivals) and unplanned (e.g., during COVID-19 pandemic, weather emergency) special events.

Agencies are looking for resources to explore what planning, development, and training may be needed to successfully position or prepare TMSs with the capabilities and resources needed to allow agencies to transition the operation of a TMS involving highly technical traffic management centers to a virtual operating environment with minimal service disruptions. 

There is a need to develop technical resources to assist agencies in planning, developing, or improving their TMSs to enable virtual operation, and to assist agencies in preparing for, training, testing, and transitioning to remote or virtual TMS operation. 

The objectives of this research are to develop two technical reports: Report No. 1, Assessing and Improving TMSs to Enable Virtual Operation, to assist agencies with planning, developing, or improving their TMSs to enable virtual operation, and Report No. 2, Operation and Implementation of TMSs Virtually, to assist agencies to prepare, plan, design, build, and operate their TMS virtually.]]></description>
      <pubDate>Fri, 27 May 2022 11:35:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1957082</guid>
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    <item>
      <title>Departure efficiency evaluation of a comprehensive transport hub based on Wi-Fi probe data and a multilayer hybrid model</title>
      <link>https://trid.trb.org/View/1926878</link>
      <description><![CDATA[Evaluation of the passenger departure efficiency of a comprehensive transport hub is essential for traffic managers. Through the evaluation, security risks in the hub can be found in time to ensure the safe departure of passengers. The attention of existing studies has focused on the analysis of the overall situation of the hub, and the quantitative description of departure status in different connection areas inside the hub is insufficient. In this study, a multilayer hybrid model based on an analytic hierarchy process and entropy weight method was established. The data collected using Wi-Fi probe technology were clustered by a K-means algorithm. The first level of the model was divided according to the connection areas of the passenger hub, and the second level was based on the number of stranded people, wait time and departure time in each connection area. It was found that the SP index has the greatest impact on departure efficiency. In addition, the impact of passenger flow aggregation on each connection area is different, and the management department should treat it accordingly. The applicability of the proposed multilayer hybrid model was verified in the example of the Chongqing north railway station.]]></description>
      <pubDate>Fri, 18 Mar 2022 12:17:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1926878</guid>
    </item>
    <item>
      <title>An Explorative Context-Aware Machine Learning Approach to Reducing Human Fatigue Risk of Traffic Control Operators</title>
      <link>https://trid.trb.org/View/1693962</link>
      <description><![CDATA[Traffic control operators are usually confronted with a high potential of human fatigue. Existing strategies to manage human fatigue in transportation are primarily by undertaking prescriptive “hours-of-work” regulations. However, these regulations lack certain flexibility and fail to consider dynamic fatigue-inducing factors in the context. To fill this gap, this study makes an explorative first step towards an improved approach for managing human fatigue. First, a fatigue causal network that can adequately represent the context factors and their dynamic interactions of human fatigue is proposed. Moreover, to overcome its problem of high dimension sparse matrix, a novel method based on the artificial immune system and extreme gradient boosting algorithm is introduced. A case study of vessel traffic management showed that the model could predict the fatigue level with high accuracy of 89%. Furthermore, to lower the risk of fatigue occurrence, a novel scheduling algorithm is also provided to adaptively arrange work for operators considering individual differences and work types. The study results showed that 27% of operators could be rearranged to reduce the possibility of human fatigue. Nevertheless, considering that more than half of operator were still fatigue in the case study, human fatigue is still a critical problem. It is hoped this research, as an explorative study, can offer insightful references to traffic management authorities in their safety management process with better operation experience.]]></description>
      <pubDate>Wed, 08 Apr 2020 08:52:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/1693962</guid>
    </item>
    <item>
      <title>Developing an Optimized UI for Traffic Incident Managers</title>
      <link>https://trid.trb.org/View/1624812</link>
      <description><![CDATA[Traffic Incident Managers (TIMs) coordinate first responders and help resolve traffic-related incidents. Currently, some use over fifteen different software applications with unique functionalities across three monitors to manage incidents, leading to redundant data entry, unnecessary task switching, and delayed responses. 40 hours of TIMs’ screens were recorded during their normal work hours at the Iowa Department of Transportation (DoT). The resulting task analysis from these videos greatly influenced the design of a simplified, web-based, user interface (UI) prototype. The new UI offers a 42.9% reduction in the steps required to manage an incident by combining the functionality of the fifteen different applications used in the existing system into a single, structured UI. This research approach offers a UI model to other DoTs that can lead to faster and more effective incident management.]]></description>
      <pubDate>Mon, 17 Jun 2019 12:31:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/1624812</guid>
    </item>
    <item>
      <title>The Software-Based Challenges Faced by Traffic Incident Managers</title>
      <link>https://trid.trb.org/View/1496340</link>
      <description><![CDATA[There are many tools in the toolbox of traffic incident management, however, as any good tradesmen will tell you, poor quality tools and an unorganized toolbox lead to slower and less effective work. This is the precise problem faced by traffic incident managers (TIMs) as they use a complicated and convoluted system of software to deploy the tools of traffic incident management. It is the aim of this paper to highlight and quantify the human-computer system challenges faced by TIMs within a Midwestern DOT, so that traffic incident management may be improved by providing TIMs with better tools and an organized toolbox from which to work. The authors of this paper identify the challenges and areas of inefficient faced by TIMs by using behavioral coding, the construction of a hierarchical tasks analysis, and Visual, Auditory, Cognitive, and Psychomotor (VACP) workload modelling.With these methods, the authors found that the human-computer system used by TIMs is challenging to operate and has several inefficiencies. Behavioral coding revealed that a significant amount of time is spent filling our reports, using maps, and communicating with a variety of personnel. The task analysis provides the requirements that must be met by a redesigned system, and identifies several inefficient and redundant processes. Also, VACP modelling shows that TIMs are mentally overworked a significant amount of time, and that the four primary mental processing channels are not utilized equally.]]></description>
      <pubDate>Tue, 20 Feb 2018 09:27:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1496340</guid>
    </item>
    <item>
      <title>An Approach to Designing an Autonomic Network of Traffic Managers</title>
      <link>https://trid.trb.org/View/1427476</link>
      <description><![CDATA[In this paper the goal is to provide the vehicle a minimum set of simple tasks, and allow it to be largely guided by the smartness of the infrastructure. This vehicle-to-infrastructure (V2I) connectivity is emphasized as the basic building block to ultimately (perhaps indirectly) achieve vehicle-to-vehicle (V2V) coordination. Assuming that every vehicle has a built-in set of embedded systems which perform intelligent actions, such as location sensing, Anti-lock Braking System, and Lane Change Warning System, it is shown that a collision-free coordinated motion of vehicles can be achieved by designing a network of autonomic Traffic Managers (TM), where each TM manages vehicles using its own resources such as real-time controllers, arbiters, and other external actuators. Being autonomic a TM will have the ability to reconfigure the system owned by it, protect itself from unauthorized attacks and repair itself in order to minimize its downtime.]]></description>
      <pubDate>Mon, 21 Nov 2016 13:42:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1427476</guid>
    </item>
    <item>
      <title>Importance of Maintenance Management's Evaluation on Vehicle Fleet Energy Efficiency</title>
      <link>https://trid.trb.org/View/1415338</link>
      <description><![CDATA[In this paper, the importance of evaluating a manager’s efficiency on fleet energy efficiency increase is presented in the framework of maintenance management. For the fleet operation to become more energy efficient it is necessary to efficiently manage its maintenance. Fleet maintenance management influences both the vehicle maintenance process, as well as the core transport process, but also the environment. In this sense, the effective maintenance management requires an integrated consideration of the vehicle maintenance process, transport process and their environment. Since the effects of the implementation of certain measures of maintenance management can be measured by various indicators, the paper defines suitable parameters from the transport process, from the vehicle maintenance process and from the environment. Defined indicators can be used to measure the manager’s efficiency. For this purpose, a model of indicators was developed with calculated relative weights. By using the developed model “Overall management score” (S), it shows to what extent the managers were effective in the maintenance management. Based on the results achieved by the model implementation in a company with a vehicle fleet, the importance of evaluating managers is highlighted to increase the energy efficiency of the fleet.]]></description>
      <pubDate>Thu, 28 Jul 2016 10:47:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1415338</guid>
    </item>
    <item>
      <title>KNOW-IN Project Outcomes in Support of Training Road Transport Managers</title>
      <link>https://trid.trb.org/View/1414007</link>
      <description><![CDATA[The paper presents the results of KNOW-IN (Knowledge-Intensive Freight Transport Small and medium-sized enterprises (SMEs). For a new generation of smart, sustainable and inclusive oriented Road Transport Managers) project, which was developed under the European Union (EU) Programme Lifelong Learning Programme/Leonardo Da Vinci (LLP/LDV) in 2012-2013. The project was aimed at creating a new professional figure: the European road transport manager (EU-RTM) who should possess management skills, tools and actions needed to overcome the challenges faced by the sector. KNOW-IN was coordinated by the European Business and Innovation Centre (CEEI) in Albacete, Spain, and the team consisted of participants from Belgium, Bulgaria, Italy, Norway and the United Kingdom.  Based on the desk and field research on training needs of staff, topics and methods of training, the attitude of road transport companies to staff training on workplace and the qualities that EU-RTM needs to possess, the project consortium developed:(1) Information Toolkit, which is an e-handbook, designed for the European road transport manager (EU-RTM) who wants to increase his/her knowledge and skills in the field of road transport and management. It is where managers in road transport can find solutions to many problems they face to in their daily work routine such as: civil, commercial, social and financial law; business and financial management of the enterprise; market access; technical standards and technical aspects of operation and road safety; (2) EU-RTM European Qualification Framework (EQF) and Recognition of Prior Learning (RPL). The matrix of knowledge, skills and competences necessary for road transport managers (EU-RTM) is based on the idea to link them with learning outcomes. The EU-RTM EQF is operationally defined by a system of indicators based on learning outcomes, regardless of how or where these are achieved. (3) The following 9 summarized sections of study were determined in compliance with the EQF: Administrative, Business Management, Planning and coordination, Dealing with customers, Human Resource, Management, Vehicle maintenance, Communication, Social skills. (4) Each section includes a set of learning outcomes as their number depends on its complex nature. Depending on knowledge and skills acquired, the quality of the EU-RTM is to be assessed. The tools developed within KNOW-IN project can be applied across the EU road transport sector. They are available for employers to assess the knowledge and skills of employees set against a standard framework. If any gaps are established, then training should be implemented and it is where project outcomes could be used.]]></description>
      <pubDate>Thu, 28 Jul 2016 10:02:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1414007</guid>
    </item>
    <item>
      <title>Intelligent Transport Systems in the Big Cities of China Based on Public Service</title>
      <link>https://trid.trb.org/View/1369472</link>
      <description><![CDATA[In the field of traffic management, the development of traffic information technology has provided the technical support for intelligent transportation systems (ITS) and has become an important means to the traffic manager, which does improve the government’s administrative ability. This paper will analyze the intelligent transportation development mode of some representative cities in China on the basis of the necessity of research of intelligent transportation system based on the public service of the big cities in China, such as Peking, Shanghai and Guangzhou through the method of systematic analysis, and advance some research methods for the big cities, and offer reference for the development of ITS in big cities in China.]]></description>
      <pubDate>Fri, 23 Oct 2015 09:28:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/1369472</guid>
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    <item>
      <title>Using Short Term Traffic Predictors in Traffic Management Centres</title>
      <link>https://trid.trb.org/View/1340410</link>
      <description><![CDATA[The ERA-NET ROAD Mobility research project "STEP" implemented short term prediction within traffic management centres to support traffic management decisions and ultimately improve network performance. STEP aimed to establish a better understanding of the operational short term prediction requirements of traffic managers at interurban and urban traffic management centres in Europe. STEP has explored the gaps between the state-of-the-art and requirements of operators in terms of functional application, data requirements, interfacing and the success of existing tools that are used. Central to the project were real-life trials conducted in an operational traffic management centre environment, testing the tools against user requirements while learning valuable (practical) lessons during implementation. This paper reports on the results of the STEP project – lessons learnt about the state-of-the-art, operational user requirements in terms of short term prediction, and implementing and deploying predictors for live traffic management operations.]]></description>
      <pubDate>Mon, 02 Feb 2015 10:27:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/1340410</guid>
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