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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>A method to improve the street-crossing risk perception ability of hearing-impaired teenagers based on constructivist teaching theory</title>
      <link>https://trid.trb.org/View/2785017</link>
      <description><![CDATA[Due to the particularity of their hearing impairments, hearing-impaired teenagers are particularly vulnerable to road traffic injuries as pedestrians. They have a higher risk of participating in traffic, especially at intersections. The aim of this study is to explore whether an intervention programme based on the theory of “constructivist teaching” can improve the street-crossing risk perception ability of hearing-impaired teenagers. In this paper, two kinds of street-crossing scenes and 20 hearing-impaired teenagers were included in a randomized controlled experiment, and an approach based on the intervention method of constructivist teaching theory was proposed. The visual characteristics and behavioural characteristics of hearing-impaired teenagers were comprehensively evaluated by the entropy weight-TOPSIS method, and an independent-sample t test was used to compare and analyse the participants' street-crossing risk perception ability. The results showed that the risk perception ability of hearing-impaired teenagers could be evaluated by the entropy weight-TOPSIS method, and the teaching method based on constructivist intervention measures could improve their risk perception ability when crossing the street. The intervention method of this study can be applied to road safety training research to improve the safety performance of vulnerable road users. In addition, it can provide a theoretical basis and practical guidance for future road safety education and training.]]></description>
      <pubDate>Mon, 05 Oct 2026 09:07:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2785017</guid>
    </item>
    <item>
      <title>Multi-modal Surveillance and Behavioral Interventions for Micromobility Safety: A Data-Driven "Safety Ecosystem" to Mitigate Traumatic Brain Injury</title>
      <link>https://trid.trb.org/View/2786707</link>
      <description><![CDATA[The rapid proliferation of micromobility (electronic scooters and bikes) represents a transformative shift in transportation use, yet its adoption has outpaced the safety frameworks required to protect users of these transportation modes. Traumatic brain injury (TBI) remains a leading cause of disability in California, and at the University of California, Davis Level 1 Trauma Hospital, the patient registry of encounters reveals that a new epidemic has emerged: a 100% increase in electronic scooter-related traumatic brain injuries within a single year (2023-2024), where only 8% of injured riders were helmeted, and 100% of patients who died were unhelmeted riders. This project will establish a multidisciplinary "Safety Ecosystem" that moves beyond reactive trauma treatment toward a proactive, data-driven prevention model for innovative policy development. By integrating retrospective clinical outcomes from the registry and Fire Department prehospital data with innovative video-based behavioral surveillance, the research team will identify the intersection of high-risk infrastructure and rider behavior (e.g., helmet use, rider speed) that may influence patient outcomes, thereby reducing morbidity and mortality related to micromobility. A targeted microlearning intervention will be designed to bridge the educational gap between clinical risk and public perception. This multidisciplinary approach will provide a scalable framework for leveraging innovative data to inform infrastructure management and safety policy, as it relates to the rising burden of brain injury among vulnerable populations who rely on micromobility.]]></description>
      <pubDate>Mon, 05 Oct 2026 13:26:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2786707</guid>
    </item>
    <item>
      <title>Evaluation of Safety Elements for Improved Pedestrian Safety at At-Grade Rail Crossings</title>
      <link>https://trid.trb.org/View/2784727</link>
      <description><![CDATA[Provide insight into how other transit/transportation agencies improve safety at at-grade crossings, particularly with helping pedestrians be more aware of train movements before crossing tracks.]]></description>
      <pubDate>Wed, 30 Sep 2026 18:03:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2784727</guid>
    </item>
    <item>
      <title>Application Practice of Intelligent Operation and Maintenance System of Escalator in Qingdao Metro Line 4</title>
      <link>https://trid.trb.org/View/2580373</link>
      <description><![CDATA[In the current rail transportation system, the intelligent subway has a good development prospect, and as a special transportation tool closely related to passenger travel, the safety of the escalator is particularly important, thus proposing an intelligent operation and maintenance system for escalators. The system consists of a line, center level system and an equipment, local end system, which monitors the operation status of the main mechanical parts of the escalator with the help of vibration, temperature, displacement sensors, and a modular data collector. Through intelligent diagnosis, expert models and algorithms, it realizes fault warnings and alerts the occurrence of accidents. The escalator's intelligent operation and maintenance system can also accurately locate the faults while doing early warning, which improves the maintenance efficiency and accuracy, reduces the labor cost, and is of great significance to strengthen the safety of the equipment and improve the operation and maintenance management. This paper analyzes the detailed cases of engineering applications and specifically discusses the system’s composition, functions, operation and maintenance platform, and early warning effect. Combined with the use of the Qingdao Metro Line 4 project, it demonstrates the significance and feasibility of the system in practical application.]]></description>
      <pubDate>Wed, 30 Sep 2026 16:24:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2580373</guid>
    </item>
    <item>
      <title>Beyond infrastructure: exploring drivers of subjective cycling safety using directed acyclic graphs (DAG)</title>
      <link>https://trid.trb.org/View/2727342</link>
      <description><![CDATA[A key reason why people refrain from cycling is a lack of perceived safety. Past research clearly demonstrates that safety perceptions are not only a result of different cycling infrastructures but reflect differences in individual and social factors. However, it remains unclear what causes these differences, as many studies on cycling safety do not pay sufficient attention to causal structures. This study deploys contrafactual causal analysis to screen existing evidence and develop a set of testable models. We use directed acyclic graphs (DAG) and statistically realize them via linear regression models to identify drivers of subjective cycling safety. In addition to gender and age, which are known to shape safety perceptions, we also investigate the impact of people’s social environment on cycling safety. Our analysis of telephone survey data from Germany (N = 1530) reveals that women feel less safe than men and safety perceptions vary across age groups, clearly supporting previous research. More importantly, the study shows that a pro-cycling social environment promotes subjective safety. Self-reported cycling competence acts as a central mediator across all three models while lower subjective safety among women—especially those with a migration background—reflects greater levels of anxiety. Implications for policy and planning such as infrastructure design for the most vulnerable and lifelong learning offers are also discussed.]]></description>
      <pubDate>Wed, 30 Sep 2026 16:23:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727342</guid>
    </item>
    <item>
      <title>“Whose Streets? Our Streets!”: Contesting Space and Embodying Risk in Shenzhen’s E-scooter Governance</title>
      <link>https://trid.trb.org/View/2704158</link>
      <description><![CDATA[This study examines the evolving role of e-scooters in Shenzhen, a rapidly urbanising megacity, as a lens to understand the complex interplay between urban mobility, governance, and social dynamics. Utilising Dynamic Topic Modelling (DTM) on 243,601 Sina Weibo posts from 2017 to 2025, we analyse public discourse to reveal the multifaceted impacts of these disruptive technologies.Our findings demonstrate a dual urban meaning for e-scooters: serving as instrumental tools for efficiency-driven commuting and as poetic vessels for emotional expression and personal autonomy. We identify distinct temporal politics of urban risks—including periodic commuting hazards, event-driven infrastructure crises, and continuous, low-visibility gendered threats—which are often unaddressed by reactive governance. Crucially, risks are differentially embodied, disproportionately impacting vulnerable groups like women and low-income users due to persistent spatial constraints and selective institutional interventions. This research advances theoretical understanding of urban mobility by foregrounding temporal and embodied dimensions of risk, offering critical empirical insights into efficiency-safety-equity tensions in non-Western contexts, and showcasing DTM’s value for complex discourse analysis.]]></description>
      <pubDate>Wed, 30 Sep 2026 16:23:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2704158</guid>
    </item>
    <item>
      <title>To swap or not to swap? Exploring the drivers, barriers, and gender differences in battery-swapping for two-wheeler EVs: A behavioral reasoning perspective</title>
      <link>https://trid.trb.org/View/2762494</link>
      <description><![CDATA[The growing emphasis on electric mobility has accentuated the need for efficient energy replenishment solutions like battery swapping. However, the drivers and barriers among battery-swapping users remain unclear in the extant literature. This study investigates the key antecedents influencing the use of battery-swapping among two-wheeler EV users through the lens of behavioral reasoning theory. We used a mixed-method approach, conducting qualitative interviews (N = 25) to uncover contextual reasons for and against adoption, followed by quantitative surveys (N = 317) in India for empirical validation. The findings reveal that openness to new EV technology enhances the reasons for and attitude, while lessening the reasons against adoption. Perceived economic benefits, instant gratification, battery life extension, and increased vehicle range are the key reasons for battery-swapping adoption. The prominent reasons against (Barriers) adoption are infrastructure challenges, lack of interoperability, battery performance anxiety, and safety risks. Moderation analysis on gender shows that attitude is a stronger driver of use behavior for male users, whereas reasons against have a more significant adverse effect on swapping behavior of female EV users. This study provides actionable insights for policymakers and service providers to enhance battery swapping adoption by fostering positive attitudes and mitigating perceived barriers to accelerate sustainable mobility transitions.]]></description>
      <pubDate>Wed, 30 Sep 2026 16:23:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2762494</guid>
    </item>
    <item>
      <title>Assessing environmental and policy influences on bike-sharing: Evidence from Trondheim, Norway</title>
      <link>https://trid.trb.org/View/2701637</link>
      <description><![CDATA[Bike-sharing systems (BSS) play a vital role in sustainable urban mobility, yet their effectiveness in cities with hilly terrain and cold climates remains underexplored. This study examines the evolution of bike-sharing ridership in Trondheim, Norway, between 2019 and 2024, assessing the impact of topography, climate, and policy interventions. Using an enriched dataset integrating elevation, weather, transport accessibility, and land use characteristics, the study applies Ordinary Least Squares (OLS) regression with year-variable interaction terms to evaluate changing ridership determinants, alongside spatial change detection mapping to identify shifting demand patterns. The results indicate that while steep slopes and adverse weather remain key constraints, their negative effects have diminished over time. Spatial analysis also highlights growing demand in university and northwest districts, while highelevation residential areas continue to experience declining ridership. The findings indicate the need for targeted interventions, such as electric bike integration, optimised station placement, improved cycling infrastructure, and enhanced winter maintenance. These strategies could potentially mitigate environmental barriers and support the long-term viability of bike-sharing in hilly, cold-weather cities.]]></description>
      <pubDate>Wed, 30 Sep 2026 15:57:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701637</guid>
    </item>
    <item>
      <title>Safe cycling to school: Rethinking inequalities in the distribution of cycling infrastructure</title>
      <link>https://trid.trb.org/View/2781356</link>
      <description><![CDATA[Bicycle riding as a mode of transport is advocated by academia, government, and community organizations due to its well-recognized health and environmental benefits. Enabling children to ride to school safely is fundamental to developing lifelong cycling habits. Previous studies show that the lack of safe cycling infrastructure is the main parental concern that restricts children from cycling. However, whether socially different communities have equitable access to safe cycling facilities and how such inequalities can be effectively identified remain underexplored. This study introduces two important yet underexamined dimensions of bikeability assessment: infrastructure quality and connectivity to key destinations, and conceptualizes bikeability as continuous access to destinations via high-quality (safe) cycling infrastructure. Using the Greater Melbourne Area, Australia, as a case study, we first applied a ‘Cycling Infrastructure Classification System’ to categorize facilities and identify those deemed ‘safe,’ with classification validated using street-view imagery. Spatial queries were then employed to identify dwellings with general versus ‘safe’ cycling access to public schools. The distribution of these dwellings and their association with socioeconomic factors were subsequently analysed using inequality statistics and a Robust Geographical Detector (RGD). Our analysis of Greater Melbourne reveals that while dwellings with safe cycling access to schools are distributed with relative equality across socioeconomic groups, this apparent equity is primarily driven by an overall scarcity of safe infrastructure. Furthermore, spatial analysis shows that areas with fewer families with children or more zero-vehicle households, which contain 80% of all dwellings, have the lowest levels of safe cycling access, underscoring a critical need for future cycling networks to prioritize both quality and equitable coverage.]]></description>
      <pubDate>Wed, 30 Sep 2026 09:28:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2781356</guid>
    </item>
    <item>
      <title>Remote working and sustainable commuting across socio-spatial contexts: Interactions of distance, time and workplace accessibility</title>
      <link>https://trid.trb.org/View/2781354</link>
      <description><![CDATA[This study examines how remote working influences commuting across socio-spatial contexts, focusing on its interaction with commuting distance, travel time and the use of sustainable transport modes. Using a case study of business parks across North Rhine-Westphalia, Germany, the study draws on an analytical sample of 2289 employees from 70 companies, who participated in a standardized mobility survey conducted between August 2023 and December 2024. The survey includes objective and subjective factors related to residential settings and workplace accessibility. A nested logistic regression model with interaction effects was applied to assess the impact of remote working on mode choice. The results reveal that longer commuting distances reduce the likelihood of using sustainable transport modes. The interaction between remote working and commuting distance reverses this pattern: frequent remote workers with shorter commutes are less likely to choose sustainable modes, whereas those with longer commutes are more likely to do so. These findings suggest that the effects of remote working on commuting behaviour depend on commute length and the opportunities to combine work and travel more efficiently. Residential settings show no clear influence on the use of sustainable transport modes. Overall, this study highlights the importance of understanding how remote working reshapes the relationship between working conditions and mobility to support the transition towards sustainable transport.]]></description>
      <pubDate>Wed, 30 Sep 2026 09:28:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2781354</guid>
    </item>
    <item>
      <title>Evaluating Autonomous Vehicles’ Pedestrian Safety Benefits in Road Networks</title>
      <link>https://trid.trb.org/View/2780216</link>
      <description><![CDATA[The purpose of this work was to investigate how CAV (connected autonomous vehicle) deployments affect pedestrian safety and the tradeoffs between safety and traffic congestion that are induced by CAV navigation around a city, particularly in the context of mixed human-driven vehicle and CAV populations. The project focused on developing methods to choose routing and control strategies that navigate this tradeoff, addressing scalability challenges in operating over city-wide road networks as well as exploring the use of large language models (LLMs) to reduce the need to gather new data on the effectiveness of different routing strategies. The main results include an algorithm that provably optimizes traffic congestion subject to a safety constraint, a characterization of the efficiency tradeoffs involved in partitioning a city into different regions for navigation control, techniques for making LLMs more efficient in generating navigation strategies for vehicles over time, and an analysis of how routing strategies must be adapted to local road topology in order to effectively account for traffic congestion.]]></description>
      <pubDate>Tue, 29 Sep 2026 15:46:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2780216</guid>
    </item>
    <item>
      <title>Generating Unsafe Road Activity from LLMs and Road Imagery to Learn Better Safety</title>
      <link>https://trid.trb.org/View/2780215</link>
      <description><![CDATA[The Federal Highway Administration (FHWA) zero death vision is a strategic goal to eliminate all traffic fatalities and severe injuries. One of the pillars of this strategy is to advance life-saving technology in vehicles and infrastructure. Many such in-vehicle technological advances have been developed and deployed in the past decade such as backup cameras, lane departure warning systems, adaptive cruise control, emergency brake systems, driver attention monitoring, etc. However, deployments of technology in the infrastructure have lagged. Most infrastructure advances have centered around redesigning roads to control traffic and improve visibility of vulnerable road users (VRUs), i.e., anyone in the road environment unprotected by a vehicle's frame. Ideally, the infrastructure should also monitor road activity for unsafe conditions and communicate those conditions to drivers and VRUs. To accomplish this goal, the infrastructure needs to be instrumented with sensors to capture data for real-time analysis and devices for relaying information to all road users. With prior UTC support, we have addressed some of the building blocks needed for a ‘smart’ infrastructure such developing and deploying methods for reliably detecting and tracking vehicles, classifying anomalous activity, and estimating 3D vehicle parameters (speed and direction). These methods were developed using images collected from cameras deployed at intersections. The main challenges that we faced were difficulty identifying a variety of ‘unsafe’ events because they rarely occurred at the deployment locations and difficulty tracking pedestrians and bicyclist because they were rarely captured.]]></description>
      <pubDate>Tue, 29 Sep 2026 15:46:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2780215</guid>
    </item>
    <item>
      <title>Exploring the Impact of Funding for Unconventional Data Collection on Vulnerable Road User (VRU) Safety Improvements, Phase II</title>
      <link>https://trid.trb.org/View/2777676</link>
      <description><![CDATA[This study explores the organizational and contextual factors, including funding, that influence the adoption and integration of emerging data sources by state Departments of Transportation (DOTs), with a focus on active transportation and vulnerable road user (VRU) safety. Building on Phase 1 planning efforts, this phase involved a national survey of DOT professionals and a practitioner workshop. Using a hybrid framework that combines the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, the study applies Partial Least Squares Structural Equation Modeling to examine how internal factors such as organizational support and funding, and external factors such as stakeholder pressure and perceived benefits, shape agency attitudes, behavioral intentions, and integration outcomes. Results show that organizational support and peer pressure are the strongest drivers of adoption, while funding and perceived benefits alone have limited impact. Despite generally positive attitudes among DOTs, the actual integration of emerging data sources remains limited. This underscores the need for greater institutional readiness and technical capacity. The study offers actionable insights for agencies aiming to modernize data practices and improve VRU safety.]]></description>
      <pubDate>Mon, 28 Sep 2026 16:46:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2777676</guid>
    </item>
    <item>
      <title>Examining Impacts of Tradable Credit Schemes on Delivery Services using an Agent- and Activity-Based Simulation Framework</title>
      <link>https://trid.trb.org/View/2781348</link>
      <description><![CDATA[This paper presents a generalized Tradable Credit Scheme (TCS) framework for urban logistics. We rigorously compare an integrated market (MoLoCo), where urban mobility and last-mile delivery activities share a unified currency (Coins), against a sector-specific market (LoCo) with an independent emission cap for logistics. This study explores the regulatory effectiveness of these frameworks and evaluates the efficacy of adaptive operational strategies employed by a monopoly logistics provider. Using an agent- and activity-based simulation for Munich, Germany, we evaluate regulatory effectiveness and adaptive logistics strategies. Results indicate that MoLoCo framework benefits from a “Coupling Effect,” where the mode shift to low-emission travel modes stabilizes the Coin market prices, yet this triggers a “Green Logistics Paradox” by stimulating online shopping. Conversely, LoCo framework generates high Coin market prices that force decarbonization but risk a “Reverse Modal Shift,” driving cost-sensitive users back to physical stores and worsening congestion. Regarding logistics strategies, fleet electrification is cost-effective but fails to mitigate congestion. True spatial efficiency is achieved only through cargo bikes in the dense city center. We therefore propose a sequential TCS implementation roadmap: initiate sector-specific regulation to enforce technological adoption, then transition to an integrated market to maximize societal welfare.]]></description>
      <pubDate>Mon, 28 Sep 2026 16:46:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2781348</guid>
    </item>
    <item>
      <title>Formulation of energy exertion in bicycle networks and estimation of its impact on route choices</title>
      <link>https://trid.trb.org/View/2767398</link>
      <description><![CDATA[Despite strong indirect evidence that physical energy exertion shapes cycling behaviour, it has never been explicitly incorporated into route choice models. This paper introduces a generalisable, individual-specific, physics-based energy model that computes expected energy expenditure (Joules) and energy intensity (Joules per metre) for every link in the network. The model accounts for slope, individual cruising speed preferences, and acceleration losses at intersections using empirically derived, intersection-specific stopping probabilities. Calibration is performed on a large-scale GPS dataset from the Greater Copenhagen Area. Descriptive analysis of observed routes reveals that excess energy is mainly driven by frequent stopping on major roads and dedicated cycleways. We then demonstrate one key application of the model by integrating both total energy (Joules) and energy intensity (Joules per metre) into a series of route choice models (Multinomial Logit, Latent Class, and Mixed Logit). Results confirm statistically significant dispreference for energy attributes and reveal substantial taste heterogeneity: a substantial subset of cyclists exhibits strong dispreference for high-intensity links and is willing to accept considerable detours to avoid them. This study provides a methodological foundation for integrating mechanical energy into route choice models in a way that is individually calibrated, physically grounded, and adaptable to diverse contexts and datasets. By grounding route choice in a quantity that combines slope, stop-and-go dynamics, and cyclist-specific cruising speed into a single measure of effort, the framework both improves the empirical fit of route choice models and offers a more interpretable account of the mechanisms behind observed preferences. The energy model itself has applications beyond route choice, and opens the door to understanding cyclists’ behaviour through more fundamental physical quantities.]]></description>
      <pubDate>Mon, 28 Sep 2026 16:46:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2767398</guid>
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