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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Understanding electric motorcycle adoption in Jakarta, Indonesia: A latent class cluster analysis of user profiles and motivations</title>
      <link>https://trid.trb.org/View/2686986</link>
      <description><![CDATA[As electric motorcycles gain traction in Southeast Asia, understanding user diversity is key to accelerating adoption. This study segments 500 electric motorcycle users in Jakarta based on their purchase motivations using latent class cluster analysis. Four distinct segments emerged: cost-focused users, eco-motivated adopters, tech-reliability seekers, and passive adopters. Each segment exhibits unique motivational patterns and sociodemographic traits. Cost-focused users, representing the largest segment, are primarily driven by operational savings and are more likely to be lower-income riders. Eco-motivated adopters display distinctive environmental concerns and are often students. Tech-reliability seekers prioritize battery performance and durability, reflecting longer travel distances. Passive adopters exhibit generally low motivational endorsement across dimensions, with policy and social cues being comparatively more pronounced than other motives. These findings underscore the importance of tailored policy interventions, such as battery leasing scheme, green loyalty rewards, battery standardization, and convenience nudges supported by social promotion strategies to reduce adoption barriers.]]></description>
      <pubDate>Wed, 15 Jul 2026 15:05:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686986</guid>
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    <item>
      <title>Valuing parking in the presence of minimum parking requirements and mobility management concepts—Evidence from Munich</title>
      <link>https://trid.trb.org/View/2686985</link>
      <description><![CDATA[The minimum parking requirements for residential buildings in Munich, Germany, are set at one parking unit per apartment. This policy appears to contradict Munich’s policy targets of providing affordable housing and promoting sustainable modes of transportation as it fosters car dependency and inflates housing prices. The objective of this study is to measure residents’ demand for residential off-street parking based on stated preferences. Using a survey with 226 respondents in the Munich metropolitan region, we analyze residents’ willingness to pay (WTP) for a guaranteed private parking unit under different supply scenarios using the contingent valuation method. Beyond the status quo, the supply scenarios encompass a multimodal mobility management concept (e.g., sharing services and public transit subscriptions), additional amenities at the household location (e.g., essential shops within 500 m distance), and enhanced transit accessibility. We use a linear mixed-effects regression model and weighting to derive representative average WTP estimates. We further predict population shares of residents willing to pay at least €49.50 or €95.11 per month as minimum and realistic construction costs of a parking unit, respectively. Our analysis indicates that a mobility management concept reduces of the average WTP by €7.34. We provide evidence that the minimum parking requirements do not reflect the demand given a realistic supply, and that a multimodal mobility management concept can reduce demand by an additional 16.89%. Planners and decision makers can use these findings to adapt parking requirements according to demand and strategic planning goals.]]></description>
      <pubDate>Wed, 15 Jul 2026 15:05:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686985</guid>
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    <item>
      <title>Bike-sharing demand estimation and supply allocation under the MaaS platform establishment: case study in Nanjing</title>
      <link>https://trid.trb.org/View/2686956</link>
      <description><![CDATA[Bike-sharing services have become globally prevalent in recent years, and Mobility as a Service (MaaS) is an important trend for future transportation. Bike-sharing has the potential to be integrated into a MaaS platform to facilitate connectivity with other modes of transportation. Nevertheless, the impact of MaaS on bike-sharing demand and supply remains unclear based on existing data. To address this issue, the survey-based data and actual trip data are fused to investigate the travel behavior of bike-sharing users in a future MaaS scenario. Further, this study proposes a demand–supply fusion model framework, which contains two modules. In the demand estimation module, this study utilizes spatial interpolation and Monte Carlo methods to fuse large-scale heterogeneous data sources. In the supply allocation module, an improved vehicle-connect-travel algorithm is designed to fuse estimated demand and supply information. The proposed fusion model is applied in a case study of Nanjing, China. The implementation of the method shows that the MaaS platform would significantly impact bike-sharing, requiring a 71.2% increase in bike supply to meet a 64.0% increase in cycling demand. Bike-sharing exhibits the economies-of-scale effect, that the larger the fleet size, the higher the vehicle efficiency. Meanwhile, the bike-sharing operator can use the proposed fusion model to satisfy the increased cycling demand by activating redundant bikes without the need for fleet expansion. These findings are beneficial to enhance the resilience and reliability of mobility services under a future scenario.]]></description>
      <pubDate>Wed, 15 Jul 2026 15:05:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686956</guid>
    </item>
    <item>
      <title>Can random regret minimization models predict traveler choices on freeways with managed Lanes?</title>
      <link>https://trid.trb.org/View/2686776</link>
      <description><![CDATA[Managed lanes (MLs) typically offer faster and more reliable travel compared to adjacent toll-free general-purpose lanes (GPLs). Successful implementation of MLs requires accurate modeling and a comprehensive understanding of travel behavior. However, individual lane decisions are often more complex than the economically rational decision-making processes that focus on toll rates versus travel time savings. Empirical evidence revealed that many travelers always choose the same lane type regardless of toll or travel time savings. Travelers who always pay a toll to use MLs are classified as ML non-choosers, while those who always use GPLs are GPL non-choosers. Those who alternate between MLs and GPLs are referred to as choosers. The existence of non-choosers challenges traditional assumptions of rational decision-making and complicates the modeling of toll facility use.Most prior research has applied random utility maximization (RUM) models to predict lane choice, while random regret minimization (RRM) models have not been explored in the context of non-choosers and choosers. Moreover, nested logit structures have not been previously applied in this context. This study addresses these gaps by using multinomial logit (MNL), nested logit (NL), and cross-nested logit (CNL) models combined with both RUM and RRM frameworks to classify choosers, ML non-choosers, or GPL non-choosers and to examine influencing factors. Using over 30 months of Katy Freeway travel data, this is the first case study to employ RRM and nested logit structures in modeling lane choice decisions within the chooser context.Results of the case study indicate that the differences in model performance are not substantial across all models, with an overall accuracy percentage of approximately 66%. For the goodness of fit, RRM-based models performed slightly better than their RUM-based counterparts. CNL models slightly outperformed NL models, which then marginally outperformed MNL models. All in all, RUM-based models showed a slight advantage in identifying choosers, whereas RRM-based models performed marginally better in identifying non-choosers. Notably, within both frameworks, the CNL models exhibited better accuracy in classifying GPL non-choosers, outperforming other models by approximately 1.5%. Travelers with higher ML-GPL speed differentials or fewer entry location variations were more likely to be non-choosers. GPL non-choosers tended to pay more consistent toll rates and traveled less frequently, whereas ML non-choosers showed the opposite pattern. Surprisingly, travelers who had knowledge of slower ML performance for a higher proportion of their trip history were less likely to be GPL non-choosers.]]></description>
      <pubDate>Wed, 15 Jul 2026 15:05:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686776</guid>
    </item>
    <item>
      <title>Integrated drone delivery network design under policy-induced restrictions</title>
      <link>https://trid.trb.org/View/2684522</link>
      <description><![CDATA[The low-altitude economy (LAE) anticipates unmanned aerial vehicles (UAVs) as a transformative solution to urban logistics challenges, offering various efficiency and sustainability benefits. The deployment of UAVs in logistics, however, is often hindered by policy-induced constraints, including infrastructure limitations, drone-specific operational characteristics, and no-fly zones. This study develops an integrated optimization framework for drone delivery systems, combining strategic depot location and tactical route planning under realistic policy-related constraints. The proposed mixed-integer linear programming model incorporates critical real-world factors such as depot capacity, payload limits, flight range, no-fly zone detours, and carbon emissions, aiming to minimize total operational costs. Through extensive case studies, we demonstrate that policy restrictions substantially impact system performance, cost, and environmental outcomes. Our findings provide actionable insights for policymakers and logistics operators, highlighting the need for adaptive regulations and infrastructure investments to unlock the full potential of UAVs in urban logistics.]]></description>
      <pubDate>Mon, 13 Jul 2026 13:58:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684522</guid>
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    <item>
      <title>Gamification as technological innovation in sustainable urban mobility: evidence from a digital field experiment</title>
      <link>https://trid.trb.org/View/2684320</link>
      <description><![CDATA[Digital and gamified tools are increasingly used to support sustainable urban mobility policies by influencing individual travel behaviour. This study analyses how three gamified incentive schemes, Inclusive, Competitive and Solidarity-based, affect sustainable mobility behaviour in a real-world context. The analysis draws on a randomized field experiment carried out in three mid-sized cities in Apulia, Southern Italy, involving 195 participants and 12,381 digitally tracked trips collected through an app and IoT devices.Results indicate that the individual reward schemes (Inclusive and Competitive) support the most stable and widespread participation, while the Solidarity-based scheme, which converts rewards into charitable donations, leads to fewer and shorter trips.The findings suggest that gamification can complement digital mobility policies by supporting motivation for sustainable travel engagement. Inclusive and performance-based designs seem to sustain participation more effectively, while solidarity incentives, although better suited for awareness and community-oriented purposes, would likely yield lower participation compared with other incentive schemes.]]></description>
      <pubDate>Mon, 13 Jul 2026 13:58:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684320</guid>
    </item>
    <item>
      <title>Multi-criteria pathfinding for high-speed rail: A Computational geospatial analysis of the Albany–New York City corridor</title>
      <link>https://trid.trb.org/View/2684281</link>
      <description><![CDATA[Intercity passenger rail between Albany and New York City has been identified as a strong candidate for higher-speed rail investment, yet existing planning studies do not provide a fine-scale, raster-based assessment of where new or substantially realigned high-speed rail corridors could feasibly be located within the Hudson Valley. This case study develops a geographic information system-based multi-criteria framework to screen environmentally and geographically suitable alignments along the corridor. Publicly available elevation, land cover, protected lands, and hydrography datasets are combined into a composite cost surface using analytic hierarchy process weighting, and least-cost path analysis is applied to derive candidate high-speed rail corridors.The composite cost surface concentrates low-impedance cells along the Hudson River Valley, reflecting the joint influence of terrain, hydrologic constraints, and conservation lands. The baseline least-cost path closely parallels the existing Amtrak Empire Service corridor while achieving a lower modeled construction cost per kilometer on the composite surface, whereas an eastern alternative is longer and traverses higher-impedance terrain and more fragmented land cover. A slope-dominant sensitivity scenario produces an alignment that overlaps the baseline path by more than 96 percent, suggesting that the resulting corridor geometry is relatively stable under plausible variations in weighting assumptions.Together, these results show how transparent, reproducible GIS-based screening methods can support early-stage corridor planning for higher-speed rail, clarify tradeoffs among terrain, environmental protection, and corridor geometry, and provide policy-relevant evidence to agencies considering investment in constrained river valley settings such as the Hudson Valley.]]></description>
      <pubDate>Mon, 13 Jul 2026 13:58:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684281</guid>
    </item>
    <item>
      <title>Advocacy coalitions and performance metrics in Tanzanian port governance: A case of Dar es Salaam port</title>
      <link>https://trid.trb.org/View/2686769</link>
      <description><![CDATA[Governance coalitions have been a decisive force in reshaping performance at Tanzania’s Dar es Salaam Port. Using the Advocacy Coalition Framework (ACF), this study codes 127 governance artefacts and compiles a 2015–2023 dataset on cargo throughput, container dwell time, ship-turnaround time, and UNCTAD’s Liner Shipping Connectivity Index. Interrupted time-series estimates show that the PPP phase raised cargo throughput by 1.52 million tonnes and reduced dwell time by 1.11 days, while the market-led strategic-investor concession added a further 2.87 million tonnes and cut 0.72 days (p < 0.01). A standardized composite competitiveness index (average z-scores across the four KPIs) shifts from negative to positive territory by 2023, indicating sustained system-wide improvement rather than isolated gains. Results remain robust under HAC corrections, alternative level-and-slope specifications, placebo break tests, and regional benchmarking, and the governance effects persist after controlling for CAPEX intensity suggesting that accountability structures and coordination capacity are central efficiency levers, not investment scale alone. Policy priorities include full single-window coverage, public berth-reliability dashboards, and expanded SGR block-train operations to inland depots.]]></description>
      <pubDate>Mon, 13 Jul 2026 13:58:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686769</guid>
    </item>
    <item>
      <title>The impact of delayed urban rail projects on land prices in Hanoi, Vietnam</title>
      <link>https://trid.trb.org/View/2725428</link>
      <description><![CDATA[Uncovering the causal relationship between urban rail investments and the real estate market is critical for financing infrastructure projects. Previous studies have explored the impact of urban rail transit on property prices and have mainly reported positive effects for projects that experienced no operational delays. However, delays in urban rail projects may generate uncertainty about future accessibility benefits, yet their effects have received much less attention in the literature. To fill this gap, we examine the effects of a delayed urban rail project on land prices using a novel approach that combines machine learning and spatial difference-in-differences models. Specifically, we examine how completed construction and delayed operation of the first urban rail line influence land prices in Hanoi, Vietnam. Our results reveal that completed construction had a positive effect on land prices, with prices increasing by 3.76% in treatment zones compared to control zones. Notably, land plots within 150-300 meters of the construction site experienced the highest price increases after construction completion. However, during the delayed operation phase, land prices within 750 meters of the station decreased significantly by 3.45%, indicating that prolonged uncertainty may weaken expectations regarding future accessibility benefits. We further discuss the relationship between urban rail investment and land price premiums, highlighting concerns about their inequitable distribution. This study provides insights for urban planners and policymakers on capturing and reinvesting the benefits of infrastructure investments to fund future transport projects.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2725428</guid>
    </item>
    <item>
      <title>A Governance-Oriented Framework for Prioritizing Construction-Phase Risks in Cross-National High-Speed Railway Delivery: Evidence from the Thai-Chinese HSR Project</title>
      <link>https://trid.trb.org/View/2725172</link>
      <description><![CDATA[The Thai–Chinese high-speed railway (HSR) project is a large-scale cross-national transport infrastructure project involving complex stakeholder coordination, contractual arrangements, and construction-stage governance. This study develops a dual-ranking framework that combines structural equation modeling (SEM)-derived structural salience with risk exposure to prioritize construction-stage risks. A risk list was developed through literature review, expert consultation, and IOC assessment, and 584 valid questionnaires were collected from Chinese and Thai practitioners involved in Thailand’s HSR projects. Principal component analysis was used for exploratory screening, while confirmatory factor analysis and a second-order SEM were used to examine the survey-based risk structure. Risk exposure was measured using the probability–impact method. The results identify five risk dimensions and show that supply disruptions, price fluctuations, import and export restrictions, and inadequate site security are the key priority risks. Geotechnical uncertainty, financial and currency-related risks, partner coordination, partner non-compliance, and force majeure events are structurally salient but underexposed. In contrast, inadequate insurance, delayed payments, design-related problems, site handover uncertainty, and inefficient communication are highly exposed but less structurally salient. The China–Thailand comparison shows that risk exposure varies by stakeholder role: Chinese respondents are more sensitive to cross-border financial and contractual interfaces, while Thai respondents are more sensitive to local implementation, design adaptation, site conditions, and changes in resource prices. The findings suggest that bilateral HSR governance should prioritize cross-border supply chain coordination, import/export facilitation, price and procurement monitoring, site security management, and role-specific risk allocation between Chinese and Thai stakeholders.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2725172</guid>
    </item>
    <item>
      <title>Alternative Energy Pathways for the Global Shipping Industry</title>
      <link>https://trid.trb.org/View/2720667</link>
      <description><![CDATA[Faced with escalating maritime emissions, the IMO recognizes the critical importance of energy transition. To explore feasible pathways, this study utilizes the Bass diffusion and modified power-law exponential hybrid growth models to simulate zero-carbon energy diffusion. Conventional and transitional energy proportions are subsequently deduced using IMO targets as constraints. Based on varying technological support and policy enforcement, nine scenarios were established within the LEAP system to simulate global emissions and the EEOI from 2012 to 2050. Results demonstrate that under the BAU scenario, emissions escalate to 1,644.6 Mt by 2050, a 44.9% increase from 2008. Without technological assistance, energy substitution alone fails to meet absolute annual reduction targets. Conversely, technology-assisted scenarios show substantial potential. Specifically, the T-PE-L scenario projects emissions of 893.8 Mt in 2030 and 326.9 Mt in 2040, making it the only pathway achieving full year-on-year compliance. To sustain compliance, other technology-assisted scenarios require zero-carbon energy to secure 2030 market shares of 5.6%, 11.2%, or 12.1%. These findings provide quantitative evidence highlighting the necessity of technological assistance and transitional energy to support IMO policymaking, infrastructure planning, and fleet retrofitting.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:32:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720667</guid>
    </item>
    <item>
      <title>15-minute city and life satisfaction: Evidence from university students in Lahore, Pakistan</title>
      <link>https://trid.trb.org/View/2681556</link>
      <description><![CDATA[The 15-minute city concept seeks to promote health, well-being, and quality of life by ensuring that essential services are located within a 15-minute walking or cycling distance from housing, accessible through sustainable modes of transportation. This study aims to evaluate the compliance of this concept in a developing country context and provide empirical evidence by examining the effects of 15-minute access to basic services on perceived health, perceived accessibility, and life satisfaction.To assess pedestrian accessibility in Lahore, Pakistan, we adapted the NEXT proximity index—originally developed as part of the Landscape Metropolis Project in Italy—which scores 15-minute access using open data sources. A network analysis was conducted to determine the shortest travel times to various points of interest, including education, transportation, healthcare, shops, restaurants, leisure spaces, places of worship, and financial services. Each hexagonal unit in the study area was assigned an access score proportional to its proximity to these facilities. These access scores were then analyzed through linear regression models, using survey data collected from 520 university students on their perceived health, perceived accessibility, and life satisfaction. Calculations made using WorldPop estimates on Lahorés population reveal that only up to 30% of the citýs population resides in areas that qualify as a 15-minute city for each facility type. Moreover, access to bus stops significantly enhances both perceived accessibility and life satisfaction, while proximity to healthcare services shows the strongest positive association with life satisfaction.]]></description>
      <pubDate>Mon, 06 Jul 2026 15:58:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681556</guid>
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    <item>
      <title>Pedestrian-vehicle distance as a predictor of driver compliance at crosswalks equipped with rectangular rapid flashing Beacons: A case study</title>
      <link>https://trid.trb.org/View/2681562</link>
      <description><![CDATA[Pedestrian safety at crosswalks remains a critical concern, yet current design standards emphasize vehicular stopping sight distance (SSD), potentially overlooking pedestrian needs. This study introduces Pedestrian Crossing Sight Distance (PCSD) and evaluates driver compliance at both SSD and PCSD distances to identify the importance of developing pedestrian-specific distance criteria for safe crossing initiation. This study investigates how vehicle-crosswalk distance at crossing initiation influences driver yielding behavior. An observational case study was conducted at a marked crosswalk equipped with Rectangular Rapid Flashing Beacons (RRFBs) in Auburn, Alabama (two-lane urban roadway adjacent to a public park). Controlled staged crossings ensured consistent pedestrian behavior. Video analysis captured vehicle approach speed, initial position, vehicle type, lane position, and compliance (yield/non-yield). Logistic regression revealed yield probability decreases significantly with higher speeds and shorter distances. At 35 mph, yield probability ranged from 25 to 60% when vehicles were at SSD but increased to 50–80% at Pedestrian Crossing Sight Distance (PCSD, 337 ft). Drivers also yielded farther from the crosswalk at PCSD (60–75 ft) vs SSD (40–50 ft). These distance-compliance relationships highlight limitations of SSD-based crossing decisions and support distance-based criteria (PCSD-scale gaps) for improving yielding reliability. Findings inform pedestrian crossing guidance and infrastructure evaluation.]]></description>
      <pubDate>Mon, 06 Jul 2026 15:58:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681562</guid>
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    <item>
      <title>Enhancing urban refueling efficiency: Strategies for sustainable mobility and economic impact</title>
      <link>https://trid.trb.org/View/2681561</link>
      <description><![CDATA[In response to increasing concerns about operational inefficiencies and environmental impacts at petrol stations, this operational research investigates strategies to enhance refueling efficiency across 103 stations in Perth. A pilot study employing observational methods and time-motion analysis established ideal benchmarks for core refueling activities. Empirical analysis of driver behavior during high-demand periods—often driven by fuel price discounts—and regular off-peak hours revealed significant performance gaps, highlighting substantial opportunities for efficiency improvements. Eliminating non-essential tasks could yield time savings of up to 67% during peak periods and 45% during off-peak periods. Economic analysis demonstrated mutual benefits when refueling processes align with these benchmarks, with potential daily savings nearing 29,000 h, equivalent to AUD 660,000 in minimum wage earnings for drivers. Furthermore, optimizing station capacity could accommodate an additional 12,800 customers daily, generating over AUD 870,000 in increased revenue. The proposed Petrol Station Efficiency Enhancement Model (PSEEM) integrates insights from transportation engineering and refueling infrastructure optimization to improve station operations. Globally applicable, PSEEM offers practical solutions to urban challenges by promoting sustainable mobility, optimizing resource use, enhancing customer satisfaction, improving transportation networks, and reducing greenhouse gas emissions.]]></description>
      <pubDate>Mon, 06 Jul 2026 15:58:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681561</guid>
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      <title>Assessing transit-oriented development readiness: a GIS multi-criteria evaluation of Lahore’s orange line corridor</title>
      <link>https://trid.trb.org/View/2681532</link>
      <description><![CDATA[This study examines the Transit-Oriented Development (TOD) potential of stations along the Orange Line metro rail corridor in Lahore, Pakistan, focusing on various metrics such as population density, commercial activity, pedestrian infrastructure, and safety. Utilizing a comprehensive TOD readiness index, we rank the stations’ ability to facilitate TOD development. Applying the Geographic Information System Multi-Criteria Decision-making Analysis approach to calculate the index score for each station, the analysis reveals that top-performing stations, such as Ali Town and Thokar Niaz Baig, exhibit high population and commercial densities, robust pedestrian infrastructure, and diverse land uses, reflecting successful TOD characteristics. In contrast, low-performing stations, including Hanjarwal, Pakistan Mint, and Islam Park, suffer from inadequate pedestrian amenities, low commercial activity, and limited transfers to other routes, contributing to their underutilization. The findings highlight the need for targeted interventions in underperforming areas to enhance walkability, promote mixed-use development, and improve overall transit access. By identifying key indicators influencing TOD readiness, this study offers valuable insights for urban planners and policymakers in developing countries aiming to foster sustainable transport systems and create vibrant, livable urban spaces around new transit systems. Understanding policy levers that enhance the TOD potential of mass transit stations can boost ridership and contribute to the broader goals of urban sustainability and livability.]]></description>
      <pubDate>Mon, 06 Jul 2026 15:58:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681532</guid>
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