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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Modelling and simulation of free-running manoeuvring-seakeeping motion using system-based and CFD-based approaches</title>
      <link>https://trid.trb.org/View/2773918</link>
      <description><![CDATA[Six-degree-of-freedom system-based and CFD-based approaches were developed and applied to the KVLCC2 tanker for manoeuvring-seakeeping predictions in regular/irregular waves and wind. In the time-domain system-based model and in-house code, propeller and rudder systems enable free-running manoeuvres; nonlinear Froude-Krylov wave force, restoring force, and instantaneous added mass were computed on the exact wetted surface and applied for accurately capturing wave-frequency motions; wave diffraction force, drift force, and retardation function were pre-calculated at the mean position. In the CFD-based framework, a previously proposed improved body-force propeller method incorporating advance speed correction was extended to free-running simulations, implemented within numerical schemes designed for manoeuvring-seakeeping simulations. Module-level verifications and extensive simulations demonstrate that the two approaches give reasonable predictions. Incident wavelength and direction, component superposition in irregular waves, and directional spreading in short-crested waves all significantly affect the manoeuvring-seakeeping motion results. Moreover, the dominant propeller-rudder flow mechanism differs between small-rudder course-keeping and full-rudder turning manoeuvres, leading to distinct dynamic pressure distributions near the leading edge and middle region of rudder surface. On balance, the two approaches are complementary: the system-based approach supports large-scale and long-duration predictions in realistic seaways to capture overall ship behaviors, and the CFD-based approach provides detailed flow-field insights for selected conditions.]]></description>
      <pubDate>Mon, 28 Sep 2026 08:37:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2773918</guid>
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    <item>
      <title>An exact system optimum model for the schedule-based transit assignment problem</title>
      <link>https://trid.trb.org/View/2773006</link>
      <description><![CDATA[Mass transit systems in many cities are facing growing congestion. One widely studied approach to alleviating this congestion involves solving the schedule-based transit assignment problem (STAP). STAP employs a joint choice model of departure times and routes, defining a spatial–temporal path wherein passengers decide both when to depart and which route to take. User equilibrium (UE) models for the STAP indicate the current congestion cost, while system optimum (SO) models can provide insights for congestion relief directions. However, most existing STAP studies under the SO condition rely on approximate SO (Approx. SO) models, which underestimate the potential for congestion reduction in the system. The few studies in STAP that compute exact SO solutions ignore realistic constraints such as hard capacity, multi-line networks, and spatial–temporal competing demand flows. This paper proposes an exact SO method for the STAP that overcomes these limitations. We apply our approach to a case study involving part of the Hong Kong Mass Transit Railway network, which includes 5 lines, 12 interacting origin–destination (OD) pairs and 52,717 passengers. Computing an Approx. SO solution for this system indicates a modest potential for congestion reduction measures, with a cost reduction of 17.39% from the UE solution. Our exact SO solution is 36.35% lower than the UE solution, which is more than double the potential for congestion reduction. We then show how the exact SO solution can be used to identify: (i) which OD pairs have the most potential to reduce congestion; (ii) how many passengers can be reasonably shifted; (iii) future systems’ potential with increasing demand and expanding network capacity.]]></description>
      <pubDate>Tue, 22 Sep 2026 15:52:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2773006</guid>
    </item>
    <item>
      <title>Operation design of last-mile transit service with modular vehicles</title>
      <link>https://trid.trb.org/View/2714776</link>
      <description><![CDATA[Travelers and commuters often face challenges in completing the final leg of their journeys from transit hubs or stations to their ultimate destinations. Bridging this last-mile gap from the trunk lines of public transit systems remains a significant logistical hurdle. This study proposes a flexible last-mile transit service utilizing modular vehicles, which can dynamically adjust capacity by coupling or decoupling modules in response to real-time, spatially heterogeneous demand across different routes and stops. This adaptability facilitates more responsive and resource-efficient operations compared to traditional services using fixed-capacity fleets. We develop a model that explicitly accounts for dynamic passenger arrivals, optimal modular vehicle formations, and dispatching strategies to accommodate spatio-temporal demand variations. Specifically, the formulation incorporates passenger-to-route assignments, fleet size constraints, and the early return of modules at intermediate stops. To manage the dynamic operations of the modular-vehicle last-mile service, we propose a two-stage route-stop reinforcement learning (RL) framework, integrating the Soft Actor-Critic (SAC) algorithm with an optimization model. Within this framework, the SAC-based RL model determines initial dispatching decisions on each route, while the optimization model derives more detailed operational decisions for both the modules and the passengers. Numerical experiments demonstrate that the proposed approach maintains a high level of service while significantly reducing total costs. Compared to traditional non-modular operations, this route-based modular service offers distinct advantages in minimizing operational expenses and passenger waiting costs, particularly when fleet resources are constrained.]]></description>
      <pubDate>Wed, 16 Sep 2026 11:21:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714776</guid>
    </item>
    <item>
      <title>Using system dynamics to explore shared mobility and sustainability connections</title>
      <link>https://trid.trb.org/View/2728254</link>
      <description><![CDATA[Shared mobility technologies promise new pathways toward sustainable transportation, yet concerns remain regarding their unintended consequences on urban mobility systems. While several studies have examined these impacts, most rely on linear cause-and-effect methodologies that fail to account for the complexity inherent in urban mobility. This study addresses this gap by applying qualitative system dynamics modeling to detect, describe, and analyze the implications of shared mobility on urban mobility sustainability. Causal loop diagrams (CLDs) of the urban mobility system were developed under two distinct scenarios: in its original state and after implementing shared micromobility, carsharing, ridesharing, and on-demand ride services. Beyond identifying key contributions from the literature, these CLDs were built by actively connecting variables and causal relationships across multiple studies, capturing systemic interdependencies that isolated, linear approaches cannot reveal. Results indicated that a non-linear paradigm of thinking provides a comprehensive framework to address urban mobility issues. Interpreting the CLDs from a sustainability perspective revealed that policies favoring one mode of transportation, without considering indirect and long-term effects, can undermine the sustainability of the system. Furthermore, the resulting qualitative models facilitate the visualization of both the direct and indirect consequences of implementing technologies and public policies.]]></description>
      <pubDate>Thu, 13 Aug 2026 17:03:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2728254</guid>
    </item>
    <item>
      <title>Bibliometric Analysis of Transport Infrastructure Hypernetwork: Review and Prospects</title>
      <link>https://trid.trb.org/View/2727486</link>
      <description><![CDATA[The transport infrastructure is transitioning into a multilayer, multifunctional hypernetwork form, posing challenges to traditional single-mode planning methods in analyzing cross-system risk transmission mechanisms and achieving spatiotemporal resource optimization. This leads to suboptimal system synergy and resilience. By examining articles on TIH research from 2002 to 2025 in the Web of Science core database, this study utilizes VOSviewer and CiteSpace bibliometric analysis software to visualize annual publication volumes, countries, journals, authors, institutions, keywords, and cocitations. It identifies hotspots and trends in TIH research across time and space dimensions. While research on the TIH commenced early, significant growth occurred only in the past 5 years. Current research predominantly focuses on multiagent trajectory prediction, cross-modal fusion, and resilient multilayer networks. The knowledge structure analysis presented in this study elucidates the evolution of knowledge and frontier breakthroughs in TIH research, offering insights to scholars in the field. This empirical evidence supports multimode collaborative modeling, intelligent resilience technology development, and policy formulation to enhance the operational efficiency and disaster response capabilities of hypernetwork systems. This study advocates for theoretical innovation to support the sustainable development of infrastructure in alignment with carbon-neutral goals.]]></description>
      <pubDate>Mon, 27 Jul 2026 09:46:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727486</guid>
    </item>
    <item>
      <title>On the satisfaction function of random utility models: A theoretical review with new developments in weibit-based choice models</title>
      <link>https://trid.trb.org/View/2623431</link>
      <description><![CDATA[This study presents a theoretical review of the satisfaction function, the expected maximum utility or minimum disutility of travel choices, which plays an important role in the random utility theory and has wide applications in transportation system analyses. New developments in the satisfaction function of the recently developed weibit-based multiplicative random utility models are discussed and compared with the extensively studied logsum-type satisfaction function derived from logit-based models. A characterization of weibit-based choice probabilities is established based on the weibit-based satisfaction function, which is shown to be a multiplicative analogue of the well-known relationship between logit-based choice probabilities and logsum-type satisfaction functions. A comparison with the conventional logit-based satisfaction function is made, from which we show that the weibit-based satisfaction function is inherently more appropriate for reflecting the percentage variation in disutility. Furthermore, potential applications of the weibit-based satisfaction function are illustrated, including weibit-based choice probability generation, utility-based accessibility measurement, and accessibility-based vulnerability analysis.]]></description>
      <pubDate>Wed, 24 Jun 2026 11:31:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2623431</guid>
    </item>
    <item>
      <title>Enhancing Traditional Adaptive Cruise Control through Map-Based Feature Integration: A Performance Evaluation Study on Stationary Vehicle Response at High Speeds</title>
      <link>https://trid.trb.org/View/2691846</link>
      <description><![CDATA[Adaptive Cruise Control (ACC) has become a widely adopted driver-assist technology, designed primarily to regulate a vehicle’s longitudinal movement while maintaining a safe following distance from the preceding vehicle. A key performance criterion is the system’s ability to detect and respond to both moving and stationary target vehicles within the ego vehicle’s path. While manufacturers typically validate ACC performance within specific speed ranges, responding to stationary objects remains particularly challenging due to limited sensor range, difficulty in detecting distant stationary targets, and constrained deceleration capabilities. Beyond certified operating limits, overall system reliability may degrade. Nonetheless, increasing industry and regulatory expectations are driving the need to extend ACC functionality across wider and more clearly defined speed domains.Modern ACC systems are further evolving to recognize and respond to various road features, including traffic lights, STOP signs, intersections, curved road segments, and roundabouts—an expanding set of scenarios enabled by multi-sensor fusion and map integration using standard definition (SD) and high definition (HD) maps. Regulatory frameworks are increasingly addressing these map-based functionalities.This paper investigates the interaction between map-based functionalities and traditional ACC behavior, specifically examining how map integration enhances ACC responsiveness to critical scenarios. Due to the wide variety of possible cases, this study focuses on stationary vehicle encounters, recognized as the most challenging and safety-critical scenario, particularly at higher speeds. Simulation studies are conducted to evaluate the impact of map-based augmentation on ACC performance, with results demonstrating performance improvements. For instance, at 50 mph on straight roads, the ego vehicle safely stopped ~4 meters from the target stationary vehicle using map-based anticipatory braking, compared to less than 1 meter with traditional ACC. These findings highlight the extended operational capability and safety benefits offered by the proposed approach, even beyond conventional speed limits.]]></description>
      <pubDate>Wed, 03 Jun 2026 09:07:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691846</guid>
    </item>
    <item>
      <title>Evaluating policy packages to accelerate and sustain electric vehicle adoption in Australia</title>
      <link>https://trid.trb.org/View/2697232</link>
      <description><![CDATA[Decarbonizing Australia’s transport sector requires policies that simultaneously influence technology costs, charging accessibility, and consumer behavior. This study develops a System Dynamics (SD) model that integrates electric vehicle (EV) adoption with biofuel blending to capture transitional emission-reduction pathways overlooked in previous research. Behavioral drivers—cost perception, infrastructure availability, social dynamics, and environmental awareness—are endogenized through interacting feedback loops, allowing dynamic evaluation of policy portfolios. Scenario analysis shows that current policies achieve only 77% EV market share by 2035, while ambitious, front-loaded interventions combining higher subsidies, accelerated charger deployment, and awareness campaigns achieve full adoption at lower long-term societal cost once environmental damages are internalized. A forward-looking multi-stage elasticity analysis identifies subsidies as the most influential policy lever, followed by infrastructure and awareness. The design of subsidy phase-outs emerges as critical: abrupt withdrawal collapses adoption, whereas gradual, maturity-based reductions sustain market stability. Findings offer actionable guidance for cost-effective, behaviorally grounded decarbonization pathways.]]></description>
      <pubDate>Tue, 05 May 2026 09:26:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697232</guid>
    </item>
    <item>
      <title>System-of-systems Safety for Low-altitude Aviation Transportation</title>
      <link>https://trid.trb.org/View/2660570</link>
      <description><![CDATA[Low-altitude (LA) transportation is rapidly evolving as a new sector of traditional aviation industry. Specifically, existing aviation safety studies were largely developed under traditional aviation System-of-systems (SoS) architectures, and primarily address system-level risks (human, vehicle, communication-navigation-surveillance, or operational management) with clear system boundaries. As a new SoS, LA SoS may have new emergent risk types and cross-domain cascading risk propagation via new architecture. This paper considers the LA transportation SoS from architecture viewpoint, and analyzes its new characteristics and risk patterns. Therefore, we propose LA SoS safety engineering framework to handle these possible new challenges through architecture design, testing & evaluation, and safety management. Accordingly, our SoS safety engineering framework mainly includes: architecture design (human-automation safety control and digital flight rules), testing & evaluation (traceable design-to-verification and equipment safety requirement), and safety management (monitor-assess-mitigate for in-time risk prediction and mitigation). Our safety engineering framework aims to provide possible solution for this new complex system of LA aviation transportation.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:00:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2660570</guid>
    </item>
    <item>
      <title>Comprehensive literature review of systemic safety analysis: Trends and development in the maritime sector</title>
      <link>https://trid.trb.org/View/2687085</link>
      <description><![CDATA[With the growing complexity of sociotechnical systems in maritime transportation, system-theoretic approaches such as STPA, STAMP, and CAST have emerged as effective tools through their focus on control problems. To strengthen both theoretical foundations and practical implementation in the industry, it is necessary to review the development of systems theory within this domain, addressing current limitations and outlining future research directions. This article presents a comprehensive review of system-theory applications in maritime transportation, encompassing modelling processes, application areas, and associated challenges. A bibliometric analysis of 76 papers published between 2015 and 2024 was conducted to identify thematic clusters, keywords, and research trends. The review examined how systems theory has been applied, the data sources employed to generate models, and how these methods are integrated with conventional risk assessment approaches. Findings indicate that STPA is the most widely adopted technique in the maritime sector for systems-based safety analysis. More than half of the reviewed studies applied systems theory to risk analysis for autonomous vessels, demonstrating researchers’ confidence in STPA’s capacity to address the challenges of highly complex systems such as autonomous ships. At the same time, there is a growing interest in combining STPA with other methodologies to produce quantifiable results for safety assessments. Consequently, an increasing proportion of studies are evolving towards integration with computational methods, algorithms, and Quantitative Risk Assessment (QRA). Overall, this paper provides a critical overview of system-theory applications in the maritime domain, highlighting limitations while offering recommendations to guide future research and practice.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:57:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2687085</guid>
    </item>
    <item>
      <title>Analysis of maritime accident governance behaviors based on evolutionary game theory and system dynamics</title>
      <link>https://trid.trb.org/View/2641310</link>
      <description><![CDATA[Current research on maritime accident governance lacks a systematic framework to capture the dynamic interaction mechanisms among governments, shipping companies, and crew members—particularly in analyzing how their conflicting objectives evolve across development stages. This study breaks through the limitations of traditional static models by innovatively integrating evolutionary game theory, system dynamics, and industry lifecycle theory to construct a tripartite dynamic governance model. The dynamic evolutionary processes of stakeholders' strategic choices under different scenarios and their sensitivity to key parameters are analyzed. The results indicate that the government plays a dominant role in the process of maritime accident governance, assuming different roles at various stages. The cost of crew members' safety behaviors is crucial for promoting effective governance, and the government should rationally control subsidies to accelerate the transition of maritime accident governance to a mature stage. By integrating evolutionary game theory with system dynamics, this study innovatively constructs a comprehensive dynamic decision-making model, it offers practical insights and effective strategies for policymakers to promote maritime accident governance. The proposed methodology extends conventional static risk assessment paradigms, offering actionable strategies for safety-critical infrastructure governance across transportation, energy, and chemical industries.]]></description>
      <pubDate>Mon, 02 Mar 2026 08:55:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2641310</guid>
    </item>
    <item>
      <title>System Dynamics Models for Sustainable Transportation Systems: Integrating Economic, Environmental, and Social Dimensions</title>
      <link>https://trid.trb.org/View/2642261</link>
      <description><![CDATA[The overall sustainability of transportation systems is shaped by the dynamic interplay of economic, environmental, and social factors. While system dynamics modeling has been employed to analyze transportation policies, this research offers novel insights into the intricate mechanisms driving sustainability. By developing system dynamics models of transportation systems, we have identified several key findings. First, the economic dimension is significantly influenced by transportation system efficiency. Second, the environmental dimension is affected by the adoption of eco-friendly vehicles and energy conservation measures, which also influence efficient pricing and prioritization strategies. Third, the social dimension is shaped by both the effectiveness and the operational efficiency of the transportation system. Furthermore, scenario analyses involving infrastructure improvements, the adoption of environmentally sound vehicles, and public transport expansion reveal disproportionately large benefits across all three sustainability dimensions. Consequently, this research contributes actionable insights for policymakers seeking to optimize transportation system sustainability by fostering a deeper understanding of these complex dynamics. The positive outcomes of these proposed scenarios were confirmed to be robust through a comprehensive sensitivity analysis, strengthening their practical applicability.]]></description>
      <pubDate>Tue, 17 Feb 2026 13:12:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642261</guid>
    </item>
    <item>
      <title>Toward LLM-agent-based modeling of transportation systems: A conceptual framework</title>
      <link>https://trid.trb.org/View/2633682</link>
      <description><![CDATA[In transportation system planning, agent-based models (ABMs) and microsimulations have become pivotal tools for understanding system dynamics and supporting decision-making. However, existing ABMs remain limited in their behavioral representation, flexibility, and reliance on comprehensive input data. This paper argues that recent advancements in large language models (LLMs) present a promising new avenue for enhancing agent-based transportation modeling. We propose an LLM-agent-based framework in which LLM agents act as behaviorally rich proxies for human travelers. By leveraging LLMs’ capabilities in natural language understanding, contextual reasoning, and generalization, our framework aims to overcome key limitations of traditional ABMs and unlock new modeling possibilities. We design LLM agents with structured profiles, memory systems, perception, decision-making, and action modules to align with the principles of activity-based travel demand modeling. Through system design and literature synthesis, we outline the conceptual and practical advantages of this approach and support our vision with a small-scale proof of concept simulation. Lastly, we discuss the remaining challenges and propose hybrid modeling as a near-term integration strategy. By positioning LLM agents as a novel and promising paradigm, we aim to expand the role of LLMs in agent-based transportation modeling and pave the way for new approaches to travel demand modeling.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633682</guid>
    </item>
    <item>
      <title>Usage patterns and system dynamics of car-sharing in Chinese cities: Insights from a data-driven framework</title>
      <link>https://trid.trb.org/View/2615254</link>
      <description><![CDATA[Car-sharing has emerged as a promising mode of sustainable urban mobility and has expanded rapidly in recent years. In China’s fast-evolving market, this sector has grown swiftly, and operational performance varies across cities. To gain a deeper understanding of usage patterns and system dynamics, this study develops a data-driven analytical framework and applies it to car-sharing systems in five Chinese cities, demonstrating its value in advancing sustainable mobility policies and operational strategies. Nearly 2 billion vehicle status records were collected via mobile platforms, from which over 1.7 million valid trips were identified. By integrating in-vehicle sensor data, we further reconstructed travel trajectories and analyzed trip characteristics, user behavior, and operational performance. A Bayesian ensemble modeling approach was then employed to decompose performance trends and detect change-points, with interrupted time-series analysis incorporated to assess event-related effects, providing a comprehensive view of system dynamics over time. The results reveal both common patterns and context-specific features in car-sharing usage and quantify the heterogeneous impacts of supply-side adjustments and external disruptions on system performance. These findings provide concrete parameters and empirical evidence to support more adaptive, efficient and resilient operational strategies, with practical implications for the design of sustainable car-sharing policies.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2615254</guid>
    </item>
    <item>
      <title>Risk Analysis Framework for Airport Infrastructure Systems: A Novel Integrated Approach</title>
      <link>https://trid.trb.org/View/2613629</link>
      <description><![CDATA[Airports are complex infrastructure systems characterized by diverse equipment, activities, and departments that must seamlessly integrate to fulfill their roles with minimal faults. Enhancing the reliability of airport systems is vital to maintain their operational efficiency. The purpose of this study is to develop a risk analysis framework based on integrated fuzzy-failure mode and effects analysis for assessing risks of airport systems. The potential failure modes associated with each system and failure causes are identified based on historical incidents and interviewing experts. The fuzzy approach is used to prioritize failure modes based on severity, occurrence, and detectability. The risk priority numbers of integrated fuzzy-failure mode and effects analysis (fuzzy-FMEA) are benchmarked with the traditional failure mode and effects analysis to highlight the benefits of considering uncertainties using fuzzy approach. The findings showed that the most critical failure modes are jet fuel tank rupture, runway approach light failure, weather station readings transmission failure, flickering approach lights, and instrument landing system glideslope deviation. The study indicates the appropriateness of the integrated fuzzy-FMEA approach for assessing risks of airport systems. It highlights that proactive maintenance practices, robust infrastructure, and continuous monitoring are essential and effective practices for ensuring the safety and reliability of airport operations.]]></description>
      <pubDate>Tue, 20 Jan 2026 10:17:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613629</guid>
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