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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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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      <title>Factors associated with future transit use intentions: Evidence from large, mid-sized, and small Canadian metropolitan areas</title>
      <link>https://trid.trb.org/View/2697100</link>
      <description><![CDATA[Public transit agencies face challenges in sustaining and rebuilding ridership amid lasting impacts from the COVID-19 pandemic, making it crucial to understand who plans to use transit and why. We examine factors associated with intention to use public transit in the next year across Canada (4-point Likert scale) and assess how they vary by metropolitan area size. Using data from the Canadian Mobility Survey (N = 16,955) covering 12 census metropolitan areas, we estimate four weighted binary logistic regression models (i.e., a pooled national model and three metropolitan-area-size-specific models). Our results show that intention is strongly associated with recent transit use and self-identified transit-user status, with non-users exhibiting low intention. Baseline intention is also lower in mid-sized and small metropolitan areas than in large ones, consistent with urban scale capturing broader differences in transit context. Beyond this, higher satisfaction, perceptions that service is improving, seeing transit as suitable for reaching desired destinations (perceived accessibility), and support for increased operating funding are consistently associated with higher intention, as do living near rapid transit and deeming a 20–35-min door-to-door transit trip as reasonable, especially in larger metropolitan areas. Car use functions as a strong barrier, particularly in mid-sized and small metropolitan areas, where driving shares are highest. Overall, similar factors are associated with intention across urban scales, but their strength varies, with mid-sized and small metropolitan areas facing greater structural and behavioral barriers. These findings are of interest to policymakers and transit planners interested in increasing and retaining ridership.]]></description>
      <pubDate>Mon, 11 May 2026 17:11:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697100</guid>
    </item>
    <item>
      <title>Freight Rail’s Role in Price Stability and Supply Chain Resilience: How America’s Rail Network Quietly Buffers Inflation and Strengthens the Economy</title>
      <link>https://trid.trb.org/View/2642330</link>
      <description><![CDATA[This report looks at supply chain resiliency and freight rail. This analysis, from the Association of American Railroad's (AAR's) Policy & Economics team, argues that the predictability, resilience, and efficiency of U.S. railroad transportation can help buffer inflation and limit supply chain disruptions. Specific areas highlighted include the grain supply chain and long-haul rail, coal shipments by rail, and freight rail fuel consumption versus trucking fuel consumption. In addition, the Los Angeles-Chicago Intermodal Corridor is used as a case study examining container transport and dwell time, transit time, and trip duration versus transit, in particular during the COVID-19 pandemic.]]></description>
      <pubDate>Tue, 05 May 2026 13:15:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642330</guid>
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    <item>
      <title>Survey of State Funding for Public Transportation—Final Report 2026, Based on FY 2024 Data</title>
      <link>https://trid.trb.org/View/2696145</link>
      <description><![CDATA[This annual report provides a snapshot of state-by-state investment in public transportation from federal, state, and local funding sources. With detailed tables and charts, the report explains how different funding and tax mechanisms are used to support transit operations and capital projects; compares differences across modes and the latest ridership trends; and features a selection of innovative state funding initiatives and case studies that highlight the efforts by states to apply state funding to support transit programs beyond federal funding levels. All funding and ridership data has been updated to reflect FY 2024 survey results. This year’s report includes new information on commuter rail, new assessments of ridership trends by transit modes, and information on the continuing impact of the COVID-19 pandemic on state transit programs.]]></description>
      <pubDate>Tue, 05 May 2026 10:18:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2696145</guid>
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    <item>
      <title>Aviation Workforce: FAA Could Strengthen Regional Pilot Pipeline by Establishing Timelines for Training Initiatives</title>
      <link>https://trid.trb.org/View/2697840</link>
      <description><![CDATA[Commercial airline pilots, including regional airline pilots, play a crucial role in facilitating economic activity by ensuring safe and efficient air travel. As in many other highly specialized fields, becoming a commercial airline pilot takes years of training and experience. The Federal Aviation Administration (FAA) Reauthorization Act of 2024 includes a provision for the U.S. Government Accountability Office (GAO) to review the supply of regional airline pilots. This report examines (1) how pilot supply and other factors affected regional airline service during the post-pandemic recovery, according to selected stakeholders; and (2) what the available data and stakeholders indicate about the current and future supply of regional airline pilots. GAO analyzed FAA pilot certification data, Department of Transportation data on regional pilot employment, and data from the Air Line Pilots Association on hourly pay rates for first-year regional airline pilots. GAO interviewed FAA officials to obtain perspectives on pilot supply and agency actions. GAO also interviewed representatives from a nongeneralizable sample of 29 aviation stakeholders, such as network and regional airlines, collegiate aviation schools, and industry associations.]]></description>
      <pubDate>Tue, 05 May 2026 10:18:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697840</guid>
    </item>
    <item>
      <title>Continuation and return of passenger behavior post-COVID-19 using long-term automatic ticket gate IC card data with focus on trip frequency, commuter pass ownership, and changes in departure time</title>
      <link>https://trid.trb.org/View/2696175</link>
      <description><![CDATA[Japan's work-style reforms and the COVID-19 pandemic have fundamentally transformed commuting patterns through widespread remote work adoption. While extensive research has documented travel behavior changes during the pandemic, few studies have quantitatively examined whether these changes persist in the post-pandemic period using actual passenger data. This study analyzes the continuation and return of passenger behavior post-COVID-19 using long-term automatic ticket gate IC card data that track individuals across multiple years. Focusing on trip frequency, commuter pass ownership, and departure time choices, the study traces behavioral transitions from the pre-pandemic period through 2023. The longitudinal tracking distinguishes passengers who maintained pandemic-era behavior changes from those who returned to pre-COVID patterns, providing empirical evidence for railway demand forecasting and transportation policy development in an era of flexible work arrangements.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:39:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2696175</guid>
    </item>
    <item>
      <title>Working from home increases work–home distances</title>
      <link>https://trid.trb.org/View/2661795</link>
      <description><![CDATA[This paper examines how the increased acceptance of working from home during and after the Covid-19 pandemic shapes how labor market and locality choices interact. We combine large administrative data on employment biographies in Germany and a new working from home potential indicator based on comprehensive data on working conditions across occupations. We find that, in the wake of the pandemic, the distance between workplace and residence has increased more strongly for workers in occupations that can be done from home: The association of working from home potential and work–home distance increased significantly since 2021 as compared to a stable pattern before. The effect is much larger for new jobs, suggesting that people match to jobs with high working from home potential that are further away than before the pandemic. Most of this effect stems from jobs in big cities, which indicates that working from home alleviates constraints by tight housing markets. We find no significant evidence that commuting patterns changed more strongly for women than for men.]]></description>
      <pubDate>Thu, 30 Apr 2026 16:38:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2661795</guid>
    </item>
    <item>
      <title>Zero- and Reduced-Fare Transit Policy and Post-Pandemic Recovery: A Multi-Agency Analysis of Ridership, Service Supply, and Access</title>
      <link>https://trid.trb.org/View/2697838</link>
      <description><![CDATA[Despite growing interest in fare reduction as a policy lever, rigorous comparative evidence on its effects, particularly in the post-pandemic context, remains limited. In Virginia some 40 transit agencies eliminated fares for some period of time during the COVID pandemic, leading the Department of Rail and Public Transportation to ask how fare reduction or fare elimination have affected ridership, operations, and access for system users. This research addresses that question by developing a structured analytical framework and applying it to a sample of transit agencies in which Virginia properties are heavily represented. Using longitudinal data spanning years before and after the pandemic “lockdown”, the research compares agencies that adopted zero- and reduced-fare policies or means-tested fare-free programs against matched fare-collecting agencies. The analysis addresses three interrelated outcomes: ridership recovery trajectories, changes in service supply and scheduled speeds and headways, and shifts in access to employment and key destinations. For a representative subset of agencies, the study also conducts a network-level analysis of access to employment using Remix, a transit planning and scheduling software tool, for a selected set of agencies that represent a range of system sizes. Findings are intended to provide evidence-based guidance for Virginia transit agencies and other stakeholders considering fare policy as a tool for ridership recovery and service quality and performance.]]></description>
      <pubDate>Thu, 30 Apr 2026 08:37:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697838</guid>
    </item>
    <item>
      <title>Spatio-temporal analysis of public transportation ridership: leveraging APC data for a comprehensive evaluation of usage rates</title>
      <link>https://trid.trb.org/View/2691800</link>
      <description><![CDATA[The emphasis on the efficient utilization of public transportation resources has become particularly relevant in recent years due to the post-pandemic fluctuation in public transportation usage and the rise in operational costs. The analysis of transportation usage rates provides valuable insights into the efficiency of the service, offering an indicator that integrates actual demand with the capacity. This study aims to develop a methodology for analyzing the occupancy rate from large-scale datasets to identify gaps between supply and demand in public transportation. Leveraging the spatio-temporal granularity of data from Automatic People Counting (APC) systems and relying on the Generalized Linear Mixed Effects Model and the Generalized Mixed-Effect Random Forest, in this study we propose a methodology for analyzing factors determining low occupancy rates. The model’s results are examined at both the segment and ride levels. Initially, the analysis focuses on identifying segments more likely associated with low occupancy rates, understanding factors influencing the probability of having low occupancy rates, and exploring their relationships. Subsequently, the analysis extends to the temporal distribution of low-occupancy-rate situations, encompassing its impact on the entire journey. The proposed methodology is applied to analyze APC data, provided by the company responsible for public transport management in Milan, on a radial route of the surface transportation network.]]></description>
      <pubDate>Wed, 29 Apr 2026 17:04:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691800</guid>
    </item>
    <item>
      <title>Regularization of Micro-mobility Modes in an Emerging Economy: A Case of India</title>
      <link>https://trid.trb.org/View/2581526</link>
      <description><![CDATA[The rise in growing traffic congestion, long urban commute durations, and lack of last and first-mile connectivity to public transport has led to citizens scouting for alternative modes to reach their desired destinations in the most economic, convenient, and time-saving manner. The concept of micro-mobility fits in these conditions to provide hassle-free, affordable, and easy-to-use solutions for the citizens across all demographics. Micro-mobility has emerged as a popular discourse in the world to address transportation and climate-change-related urban issues and challenges. While in other parts of the globe, micro-mobility is booming, in India, it is still in the early years of introducing micro-mobility. The outbreak of the COVID-19 pandemic has made the users explore these options of micro-mobility especially the young as a group as the risk of contracting the coronavirus is lower through micro-mobility. This paper is an attempt to critically review the existing operational characteristics of micro-mobility modes and also analyze the user’s opinion towards this new concept of micro-mobility. This paper also tested various regularizing strategies to control the measures ranging from limiting the circulation speed, limiting the scale of operations, limiting the operation areas, and restricting it completely from a few public spaces to provide better safe conditions to the users as well as promote to have a better regulation process of micro-mobility in Indian cities.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:47:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581526</guid>
    </item>
    <item>
      <title>Post-COVID-19 recovery and resilience in passenger and cargo traffic: A Bayesian vector autoregressive analysis of India’s top 10 busiest airports</title>
      <link>https://trid.trb.org/View/2664106</link>
      <description><![CDATA[This study examines the post-COVID-19 resilience of India’s ten busiest airports using passenger and cargo traffic data from 2016 to 2024. A Bayesian vector autoregression (BVAR) model generates counterfactual forecasts, enabling a comparative assessment to classify airports as outperformers, forecast achievers, or underperformers. Beyond performance categorisation, the study investigates the role of airport infrastructure in shaping resilience outcomes through Spearman correlation and ordered logistic regression (OLOGIT) analysis. Results indicate that infrastructure attributes such as cargo terminal availability, runway capacity, and metro connectivity are significantly associated with higher resilience. Airports with stronger and more adaptive infrastructure recovered more effectively from pandemic disruptions. These findings offer actionable insights for infrastructure planning, crisis preparedness, and long-term policy strategies aligned with national initiatives such as the UDAN regional connectivity scheme.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:34:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664106</guid>
    </item>
    <item>
      <title>How has the importance of factors influencing telework adoption changed over time? Observing pre- to late-pandemic trends using multi-year data from two US regions</title>
      <link>https://trid.trb.org/View/2663853</link>
      <description><![CDATA[Teleworking, significantly accelerated by the COVID-19 pandemic, has altered traditional work arrangements and commuting habits. To understand factors influencing telework behavior and their changes over time, we examine telework adoption trends using three waves of cross-sectional survey data collected in the springs of 2021–2023 (and including retrospective pre-COVID data) in the Dallas–Fort Worth–Arlington (DFA) and Washington (DC)–Arlington–Alexandria (WAA) regions. We categorize employees into non-teleworkers (NTWers), non-usual teleworkers (NUTWers), and usual teleworkers (UTWers) based on their frequency of full days working from home. Region- and year-specific multinomial logit (MNL) models are constructed to identify factors influencing telework patterns across different pandemic phases. Four groups of influential factors are revealed: those consistent in significance throughout (e.g., education and income), those fading across years (e.g., car-related attitudes), those strengthening over time (e.g., telework attitudes), and those with differential impacts between NUTW and UTW (e.g., household composition). For instance, in WAA, workers with young children were more likely than others to be NUTWers pre- and early-pandemic, but this factor faded in significance in later years. Conversely, the impact of having school-aged children on NUTWing strengthened in the late-pandemic period. Additionally, pro-car ownership attitudes decreased the propensity to UTW throughout the years, though this influence faded late in the pandemic. These findings highlight the dynamic interplay between work-family balance, job characteristics, and attitudes related to telework adoption. The results provide valuable insights for policymakers and employers aiming to optimize flexible work arrangements, refine telework policies, and address future workforce needs.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:34:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663853</guid>
    </item>
    <item>
      <title>The new geography of work and mobility: Behavioural, spatial and sectoral dynamics of telework during and after COVID-19</title>
      <link>https://trid.trb.org/View/2666893</link>
      <description><![CDATA[The COVID-19 pandemic triggered a rapid expansion of telework, reshaping commuting patterns and urban mobility, yet its sectoral and spatial dynamics in rapidly developing megacities remain insufficiently understood. This study introduces an operational framework that integrates large-scale location-based services (LBS) mobility data with official employment statistics to measure telework transitions in Shenzhen, China, from 2019 to 2022. Results show an initial 14.5% surge in frequent telework that stabilised at 9% above pre-pandemic levels, with pronounced divergence across industries: skilled scalable service sectors sustained elevated telework adoption, whereas manufacturing and consumer-facing industries largely returned to onsite work. Spatially, telework persistence concentrated in central business districts and knowledge-intensive clusters, consolidating a more monocentric hybrid-work geography. Regression models reveal strong associations between telework uptake and sociodemographic factors, commuting distance, and built-environment features such as amenity density, mixed land use and high-rise development. Moderation analysis further shows that industry composition amplifies or attenuates built-environment influences, reinforcing sector-specific telework feasibility. By integrating mobility-derived behavioural indicators with urban form and sectoral structures, this study provides a transferable analytical framework for monitoring hybrid work in data-scarce contexts and offers globally relevant insights for transport planning, mixed-use development and the governance of post-pandemic work–travel transitions.]]></description>
      <pubDate>Wed, 29 Apr 2026 16:34:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666893</guid>
    </item>
    <item>
      <title>The heterogeneous relationship between multi-scalar accessibility and economic diversity: Evidence from Hong Kong</title>
      <link>https://trid.trb.org/View/2673215</link>
      <description><![CDATA[Economic diversity, typically characterized by small independent businesses, faces a declining trend in many regions and countries due to market consolidation and the post-pandemic landscape. While transportation accessibility is widely advocated for economic growth, its nuanced role in economic diversity across multiple spatial scales and socioeconomic contexts remains critically underexamined. This study examines complex dynamics in Hong Kong, analyzing how local, citywide, and regional accessibility, both individually and interactively, relate to economic diversity, as measured by the percentage of independent restaurants. Our findings reveal that citywide and regional accessibility are generally associated with lower diversity, overshadowing the non-significant role of local accessibility. Additionally, these relationships are not universal but are deeply contingent on local socioeconomic context. We find a stark income-based divergence: advanced city and regional accessibility suppress independent businesses in low-income areas, while fostering them in high-income areas. The effects of multi-scalar accessibility are also conditional on age structure: a higher percentage of the older adults may witness a decline in the percentage of independent restaurants under advanced citywide and regional accessibility. Conversely, this same broad multi-scalar accessibility is positively associated with the percentage of independent restaurants in high-youth areas. We conclude that effective policy must be context-sensitive, accounting for both the geographical scale of accessibility and the socioeconomic characteristics of neighborhoods, thereby fostering equitable and resilient urban economies.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:17:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673215</guid>
    </item>
    <item>
      <title>Resilience and efficiency of global container ports: A DEA–Malmquist analysis based on physical infrastructure and strategic typologies</title>
      <link>https://trid.trb.org/View/2658012</link>
      <description><![CDATA[Container port efficiency is vital for sustaining global trade, especially amid disruptions such as the COVID-19 pandemic, which exposed systemic weaknesses such as port congestion and schedule delays. However, limited research has systematically evaluated port performance dynamics across systemic shocks, especially from a resilience and investment-alignment perspective. In this study, a Malmquist data envelopment analysis (DEA) framework is applied to examine the efficiency and productivity trends of major container ports from 2018 to 2022. The proposed model addresses cross-port differences and data constraints by focusing on key physical infrastructure inputs—gantry cranes, port area, and quay length—and container throughput as output. The results show that ports such as Singapore and Shanghai consistently achieve high efficiency, whereas other ports lag behind. Productivity gains mainly reflect technological change (TC), not technical efficiency change (TEC), exposing a gap with the scale efficiency change (SEC) needed to realize investments. A strategic matrix classifies ports by overall performance and progress, identifying resilient and advancing ports such as Ningbo-Zhoushan and Qingdao. These insights help policymakers and port managers align investment with long-term resilience goals and respond more effectively to future disruptions.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658012</guid>
    </item>
    <item>
      <title>A projection-based regret theory method for evaluating service quality of public transportation systems under interval type-2 fuzzy environment during COVID-19 pandemic</title>
      <link>https://trid.trb.org/View/2657078</link>
      <description><![CDATA[Public transportation plays a vital role in urban mobility, particularly in large and densely populated cities. As a result, evaluating service quality of public transportation systems has become a strategic decision-making concern for both private and public sections. In particular, facing with the expeditiously spreading of coronavirus disease 2019 (COVID-19), it led to an unprecedented decline in public transit demand and revenue, while also exacerbating traffic congestion during peak hours. This study aims to improve the passengers' satisfaction problem of public transportation during the COVID-19 pandemic, and to assess their satisfaction degrees by conducting passengers’ satisfaction surveys. A novel projection-based regret theory approach based on interval type-2 fuzzy sets (IT2FSs) is introduced to solve multi-criteria decision-making problems related to service evaluation. First, a projection model of IT2FSs is formulated, incorporating both distance and angle information. Second, by integrating this projection model with regret theory, new utility and regret-rejoice functions are constructed to enhance decision-making effectiveness. Comparative analyses with existing methods demonstrate the superiority of the proposed approach in capturing the psychological factors of decision makers. The model yields more reliable and realistic outcomes, offering valuable insights into future enhancements in public transportation service quality. Furthermore, sensitivity analysis verifies the robustness of the method, as the ranking results remain stable when varying parameter settings. As a conclusion, the service quality of public transportation systems from the best to the worst in sequence are as follows: taxi, e-hailing, bus, van and metro, and this can assist policymakers and transit agencies in making more informed and efficient resource allocation decisions during and after the pandemic.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2657078</guid>
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