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    <title>Transport Research International Documentation (TRID)</title>
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    <language>en-us</language>
    <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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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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>
    </item>
    <item>
      <title>Workload balancing for flight dispatchers</title>
      <link>https://trid.trb.org/View/2622435</link>
      <description><![CDATA[Flight dispatchers are responsible for flight planning prior to departure and flight monitoring while en-route. Their work involves multi-tasking and their workload is dynamic. We study such a problem under two nonlinear workload balancing measures: minimum peak workload and minimum absolute deviation. In order to solve practical instances efficiently, we use decomposition through Lagrangian relaxation to reduce the problem into easier-to-solve subproblems and prove that the Lagrangian lower bound has a closed-form expression for the peak workload objective. To find feasible solutions, we develop a Focus-Search-and-Improve heuristic with a genetic algorithm core where parts of the feasible solution set are explored and searched by a genetic algorithm, and solutions are further fine-tuned by an improvement heuristic. To test the efficiency of the proposed approach, we generated 231 instances based on 2019 U.S. Bureau of Transportation flight data that involve 17 different carriers and up to 3968 flights per instance. Numerical testing demonstrates the efficiency of the proposed approach in that the Lagrangian lower bound is very tight, and the heuristic finds optimal solutions in 33.4% of the instances and are on average 3.5% away from the Lagrangian lower bound. It also reveals that the difficulty of the problem increases for smaller workstation-to-flight ratios, and that the peak workload objective achieves the goal of balancing the workload at times where peaks occur but does not necessarily balance the workload throughout the workday. On the other hand, the absolute deviation objective achieves better balance between workstations at the expense of a slight increase in peak workload.]]></description>
      <pubDate>Tue, 06 Jan 2026 09:17:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2622435</guid>
    </item>
    <item>
      <title>Enhancing transportation agility through neuroadaptive AI and behavioural decision intelligence</title>
      <link>https://trid.trb.org/View/2554371</link>
      <description><![CDATA[Transportation systems increasingly face real-time disruptions—from urban congestion to infrastructure failures—that demand agile, human-informed responses. While traditional AI tools offer operational support, they often overlook the cognitive and emotional conditions under which critical decisions are made by drivers, dispatchers, and mobility coordinators. This gap limits their effectiveness in high-stress, rapidly changing environments where human decision-makers play a critical role. To address this, the present study introduces a neuroadaptive framework for transportation agility that integrates real-time behavioral insights into intelligent decision-support systems. This framework, inspired by the foundational principles of supply chain agility (SCA), consists of three interconnected stages: sensing operator stress and cognitive load, predicting decision tendencies, and reconfiguring mobility strategies in real time. Crucially, the framework incorporates a reinforcement learning element, forming a continuous feedback loop that refines AI responses based on user behavior and system performance. This adaptive mechanism ensures that transport platforms evolve toward more human-aligned, context-aware decision-making, enhancing both agility and resilience over time. By advancing this novel, human-centric model, the study extends the agility discourse into the transportation domain, emphasizing the critical link between cognitive awareness, real-time adaptation, and long-term system learning. This approach offers a scalable foundation for adaptive, context-aware, and resilient mobility networks, aligning closely with the demands of future smart cities and intelligent transport systems.]]></description>
      <pubDate>Thu, 05 Jun 2025 14:01:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2554371</guid>
    </item>
    <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>Modern Problems of Assessing the Work Efficiency of Train Dispatchers</title>
      <link>https://trid.trb.org/View/2407738</link>
      <description><![CDATA[Within the framework of the implementation of the transportation process and ensuring its efficiency, the main task is to make employees to realize the goals of railway transport reform achieved with the dominant role of labor. In modern conditions, dispatch control of the transportation process is a rather complex, hierarchical system. At different levels of this system, their own management objects and their own production tasks are formed. The efficiency of the operational management of transportation is determined by the structure of management bodies, the organization of the labor activity of dispatchers at each range of the railway. A train dispatcher’s activity, like any labor process, also has got its own organization and realizes in the frames of concrete system. There were attempts to assess the labor effectiveness and its difficulty in the given category of workers on the basis of integral and general indicators, such as labor productivity of dispatcher’s shifts, railway profits and returns in general and so on. This way turned out ineffective too, because all operating parameters of the railway transport greatly affect the quantity of factors mentioned above. Undoubtedly, in the condition of centralization of the transportation complex management function in Russian Railways, activities of workers and derivative of train traffic management, the quality of railway maintenance services also need to be assessed using special criteria and indicators, which are closely linked to train dispatcher and his professionalism.]]></description>
      <pubDate>Wed, 19 Mar 2025 10:12:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407738</guid>
    </item>
    <item>
      <title>Evaluation of Risk Shift Between Individuals and Teams in an Operational Task</title>
      <link>https://trid.trb.org/View/2480132</link>
      <description><![CDATA[This study sought to find a polarized risk shift between individual risk decisions and team risk decisions in an operational task. Risk shift theory has been explored in behavioral psychology and teamwork literature and is defined as the propensity of teams to make riskier decisions when compared to individuals. However, the findings from previous work were based on participant responses to hypothetical, abstract thought problems. These previous tasks lacked attributes present in an operational domain, including complexity, accountability, realism, and measurable risk. This study sought to bridge this gap by investigating whether this risk shift phenomena occurs in an operational task. Humans often work in teams in these domains, and increasingly, humans are also working with agents. Thus, an evaluation was done to first establish the existence of risk shift in human-only teams in an operational setting. The study had one independent variable: decision-maker with two levels, individual and team. The task design involved an aviation dispatch task, where participants simulated the role of a flight dispatcher. Participants were responsible to make dispatch decisions on whether to divert, hold, or send 25 airplanes, while weighing the potential consequences of incurring policy violations based on the possibility of an approaching storm. Results from the study showed the absolute value of the shift was significantly different than zero. Additionally, a thematic analysis found that groups varied in their decision-making strategies, using approaches like deferring to an influential teammate, averaging decisions amongst teammates, and collaborating to come to a new team decision. Establishing operational HHT risk shift in a realistic scenario provides the foundation for future experiments to examine how humans and autonomous agents perform teaming tasks in dynamic contexts involving risk.]]></description>
      <pubDate>Thu, 06 Feb 2025 10:49:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2480132</guid>
    </item>
    <item>
      <title>Using HFACS to understand human error in railway dispatcher performance: a study of proactive safety inspection records</title>
      <link>https://trid.trb.org/View/2485316</link>
      <description><![CDATA[This study analyzes 4,095 proactive safety inspection records obtained from a large dispatching centre by utilising the HFACS framework. These proactive safety inspection records offer comprehensive documentation of incidents, capturing major accidents and numerous minor discrepancies and lapses that often go unnoticed in accident reports. The analysis revealed that most incidents were attributed to unsafe actions, primarily skill-based errors and poor decision-making. Additionally, contributing factors such as adverse mental states, personal readiness, and crew resource management were found to play a significant role as preconditions for unsafe acts. Path analyses further established a significant correlation between factors such as unsafe supervision, preconditions for unsafe acts, and the occurrence of unsafe acts. In their discussion, the authors critically evaluate the strengths and limitations of proactive safety inspection records in safety research. Moreover, the authors emphasise these findings’ potential to enhance safety within the railway industry.]]></description>
      <pubDate>Tue, 28 Jan 2025 14:05:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2485316</guid>
    </item>
    <item>
      <title>Identification of Entrant’s Abilities on the Basis of Sugeno-Type Fuzzy Inference Systems</title>
      <link>https://trid.trb.org/View/2470715</link>
      <description><![CDATA[In the conditions of effective training in aviation for dispatchers and pilots, it requires the use of infocommunication systems capable of working under conditions of fuzzy uncertainty in real time. The functioning of such systems is based on fuzzy inference systems. However, the development and implementation of these systems requires the creation of fuzzy knowledge bases. Therefore, special attention in this study is paid to the creation of a system of fuzzy inferences and the formation of a fuzzy knowledge base of this system. The result is a lozenge-type fuzzy inference system. The fuzzy knowledge base of the system contains the rules according to which, based on the results of test computer game problems of varying complexity, a conclusion is formed about the applicant’s ability to acquire knowledge and skills in a certain specialty. When developing the rules, both the results of passing different levels of professionally oriented computer test games were taken into account, and the interest of dispatchers and pilots was taken into account. Therefore, the proposed fuzzy rules of the knowledge base of the fuzzy inference system make it possible to assess not only the ability of the controller or pilot to solve certain problems. This dependence of the input dataset on time allows the implementation of a fuzzy inference system of the Sugeno type, using clear input data in the formation of inferences.]]></description>
      <pubDate>Tue, 31 Dec 2024 16:30:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2470715</guid>
    </item>
    <item>
      <title>Smart Connected and Automated Vehicle Fleet Management: Developing Regional Dispatch Decision Support for Congestion Mitigation</title>
      <link>https://trid.trb.org/View/2470487</link>
      <description><![CDATA[With the arrival of new technologies like connected and self-driving autonomous vehicles (AVs), the workload of regional dispatchers will increase. To this end, the CADS (Congestion Alerting Decision Support) tool was developed to support strategic transportation planning (on the order of weeks to months) and tactical transportation planning (on the order of hours to days). It allows dispatchers and other decision makers the ability to run what-if simulations to determine how and when to allocate future resources for different scenarios. Such a tool can be used operationally, like in the days before a hurricane to improve planning, but also in training to provide a host of practice scenarios for new planners, dispatchers and other emergency planning personnel. One current limitation of CADS is its inability to connect congestion metrics to predictions of safety, which could be very useful to dispatchers, especially as AVs increase in numbers. Research determined that when operating in mixed traffic as a following vehicle in a platooning scenario, AVs had longer response times, which could lead to an increase in the number and severity of conflicts, and thus problems with potential overall safety. If CADS could track metrics like AV platoon length, heterogeneity of platoon vehicles on a highway and braking response times, it is possible that CADS could highlight risk profiles for areas of congestion that involve AVs. However, additional research showed that incorporating commonly-used models likely do well in predicting where AVs will be at a given time, but struggle with predicting acceleration and deceleration, indicating more work is needed before such simulations can realistically be used for risk projections.]]></description>
      <pubDate>Thu, 19 Dec 2024 14:14:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2470487</guid>
    </item>
    <item>
      <title>Optimal Dispatcher Number for One-Way Carsharing Services Considering Break Requirement</title>
      <link>https://trid.trb.org/View/2389713</link>
      <description><![CDATA[This study investigates the dispatcher number (DN) of one-way carsharing services (CSSs), considering the critical yet overlooked aspect of dispatchers’ break requirement with vehicle relocation and dispatcher assignments. The DN problem aims to minimize the daily cost of one-way CSS operators by determining the fleet size, the number of dispatchers, vehicle relocation, and dispatcher movement under the restriction on the maximum accumulative working time of dispatchers. The novelty of the study lies in the incorporation of the break requirement consideration of dispatchers into the personnel assignment during the operation period. A nonlinear integer programming (NLIP) model is first developed for the DN problem. By exploring the structure of the proposed model, an effective heuristic solution method consisting of optimization and simulation modules is proposed to obtain the optimal solution to the problem. Numerical experiments based on EVCARD, a popular one-way CSS operator in China, are conducted to demonstrate the effectiveness of the proposed models and solution method and the rationality of incorporating the break requirement into the decision-making process. Furthermore, the authors investigated the impacts of critical parameters, such as payment for dispatchers and relocation cost, on the performance of the one-way CSS, providing valuable insights for carsharing service operators.]]></description>
      <pubDate>Mon, 21 Oct 2024 17:02:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389713</guid>
    </item>
    <item>
      <title>A Systems-Theoretic Computational Model of Human Performance in an Advanced Railroad
Dispatch Operation</title>
      <link>https://trid.trb.org/View/2431663</link>
      <description><![CDATA[The Federal Railroad Administration sponsored a research team from Duke University to study railroad dispatcher workload in association with automation under various scenarios and task demands. The team developed a computational model to help examine, understand, and predict the effects of the introduction of technology and automation on dispatcher personnel workload. As railroads implement automation through technologies like Positive Train Control, the role of dispatchers could become more significant in rail traffic control and operational management. It may be important to factor in the effects of changes on the performance of dispatchers, as well as train crews, to maintain acceptable levels of safety in operations for individual trains and the broader networked rail system. The Simulator of Humans and Automation in Dispatch Operations (SHADO) was developed as a rapid prototyping tool that allows decision-makers in the industry to test present and future concepts of operations that embed automated and autonomous systems. This report provides a case study of real-world dispatch operations across three shift schedules in both short-line freight rail and commuter rail scenarios. These findings support the use of SHADO in analysis for additional dispatch operations settings.]]></description>
      <pubDate>Sat, 21 Sep 2024 16:56:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2431663</guid>
    </item>
    <item>
      <title>Research on Emergency Capacity Training System for Rail Transit Dispatchers</title>
      <link>https://trid.trb.org/View/1975940</link>
      <description><![CDATA[With the rapid development of rail transit, in order to solve the increasingly severe contradiction between supply and demand of rail transit traffic dispatchers and to improve the emergency response capability of traffic dispatchers, it is urgent to establish a complete train system for emergency response capability of rail transit traffic dispatchers. Based on the current situation and demand of Beijing subway dispatching command, this paper designed a training simulation system composed of two subsystems: scenario playback system and simulation training system, analyzed the functions of dispatcher operation environment simulation and instructor system simulation, and designed simulation software system architecture. As a comprehensive simulation system integrating multiple dispatching links, the system can simulate various emergencies and train dispatcher’s emergency handling ability in an all-round way. It will give full play to the incomparable advantages of traditional methods in traffic dispatcher training and emergency drills.]]></description>
      <pubDate>Fri, 30 Aug 2024 16:58:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1975940</guid>
    </item>
    <item>
      <title>Communication architecture for real-time decision support systems in railway nodes</title>
      <link>https://trid.trb.org/View/2319326</link>
      <description><![CDATA[Rail transport nodes are complex systems providing transport for goods and people. The dispatcher providing operational control is essential for the proper functioning of these nodes. His role mainly consists of decision-making connected with the allocation of limited resources such as tracks or personnel. These decisions are complicated because of many unexpected influences, e.g., train delays. Recognizing the importance of decision support for the dispatcher's decision-making process, the authors had designed a real-time decision support system with a simulation model at its core. Such a system requires a high-quality information source for its operation, that needs to be efficiently acquired, processed, and used. In this paper, therefore, the authors address the possibilities of obtaining up-to-date information about the railway system. Moreover, the authors designed a communication architecture that allows the distribution of information to the designed decision support system with a simulation model in the core.]]></description>
      <pubDate>Tue, 23 Apr 2024 10:49:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2319326</guid>
    </item>
    <item>
      <title>Research on cyber-physical system models of downhole locomotive dispatching and fault</title>
      <link>https://trid.trb.org/View/2329907</link>
      <description><![CDATA[Fault diagnosis is of great significance for the rapid recovery of the system after the accident. Intelligent dispatching among multiple controllers is developed in this work to improve the efficiency of downhole locomotive dispatching, finally realizing unmanned intelligent locomotive dispatching. The locomotive dispatching logic processing model of with signal lights, rutting machine, locomotives, and other equipment is established based on the model theory of cyber-physical systems (CPS). The model tasks in this system are combined with the embedded controller tasks which make it convenient to optimize the logic processing procedures using Ptolemy II software. Key findings indicate that the proposed model can make the locomotive dispatching process without deadlock and make the processing procedure more reasonable. Simulation and practical experiments demonstrate that the controller cooperation speed can be improved after the CPS model is built, which can realize safer and more effective automatic locomotive dispatching.]]></description>
      <pubDate>Tue, 13 Feb 2024 12:27:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2329907</guid>
    </item>
    <item>
      <title>Urban Air Mobility Fleet Manager Gap Analysis and System Design</title>
      <link>https://trid.trb.org/View/1973024</link>
      <description><![CDATA[NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in research to facilitate the introduction of air taxis into the US National Airspace System. Given the history of conventional aircraft operations, it is clear that dispatcher support will be required for UAM. This paper presents a gap analysis, system requirements, and a workstation design concept for the UAM dispatcher or Fleet Manager (FM) position. The gap analysis focuses on the differences between the tasks of the airline dispatcher and those projected for the FM. FM system capabilities and data requirements are then presented as foundations for software development. An initial user interface concept is provided. The FM software uses a single, large display. The system supports prediction, monitoring, and task execution. This paper is intended to support FM software design for future air taxi systems.]]></description>
      <pubDate>Wed, 22 Feb 2023 09:57:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973024</guid>
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