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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>
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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>Multi-activity accessibility by public transit: Regional disparities in daily access to essential services</title>
      <link>https://trid.trb.org/View/2689884</link>
      <description><![CDATA[Public transit (PT) is crucial for equitable low-carbon access to essential services, particularly for nondrivers. However, daily mobility is often multipurpose, and transit users frequently rely on completing several tasks within walking distance of a reachable anchor destination. To capture this dimension, we propose a multi-activity accessibility framework that quantifies how many distinct essential activities can be bundled around a reachable anchor destination. First, transit inequity is driven mainly by uneven initial coverage, and many cities fail to connect residents to any feasible anchor within established travel-time standards. Second, clinics and grocery destinations are more often embedded in dense activity bundles, whereas parks, senior centers, and public service centers are less consistently co-located with other services, resulting in lower bundling potential even when they are reachable. Third, multi-activity deficits follow a clear core-periphery pattern, as deficit cities concentrate on older residents and show high car ownership despite lower incomes, a pattern consistent with the notion of forced car ownership. Overall, the results indicate that improving multi-activity transit equity requires aligning PT services with the spatial clustering of essential facilities, providing an empirical basis for coordinated transport and land use interventions in underserved cities.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2689884</guid>
    </item>
    <item>
      <title>Delineating hierarchical activity space from high-resolution urban mobility flows</title>
      <link>https://trid.trb.org/View/2720666</link>
      <description><![CDATA[Current studies on activity space are limited by the conceptualization of absolute physical space that fails to consider the heterogeneity of relational spaces reconstructed from spatial interactions of human movements between locations and falls short in incorporating the inherent hierarchical property of human mobility. Consequently, these approaches cannot faithfully reflect how people interact with urban spaces through travels. From the lens of relational space, this study proposes the new Hierarchical Activity Region Model (HARM) to derive the space and hierarchical properties of activity spaces perceived by various urban groups. We demonstrate the enhanced validity of our model on travel behavior in Manhattan, New York City, before, during, and after Hurricane Sandy on the basis of taxi data. Empirical results show that intra-urban travel retains clear hierarchical organization, even under disruption of a major weather event. Yet, travel undergoes a compression effect in travel hierarchies, characterized by fewer hierarchical levels and enlarged characteristic scales, followed by a rebound. Clustering the derived hierarchies reveals pronounced heterogeneity that stems from differences in population profiles; some groups sustain deeper structures or recover quickly, while others experience a persistent loss of levels. This study provides valuable insights into the functional hierarchies of urban mobility, which could inform more sustainable, resilient and equitable urban planning. The proposed methodological framework is generic for studying human mobility in broader contexts.]]></description>
      <pubDate>Thu, 16 Jul 2026 16:38:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720666</guid>
    </item>
    <item>
      <title>Multiscalar accessibility and the activity spaces of older women: The unequal influence of individual and socio-spatial determinants</title>
      <link>https://trid.trb.org/View/2709569</link>
      <description><![CDATA[Mobility and accessibility are central to autonomy and social participation in later life, yet limited research examines how individual capacity and multiscalar accessibility shape activity spaces in highly unequal metropolitan contexts. This study investigates how functional health, labour engagement, neighbourhood socioeconomic context and urban accessibility conditions influence the activity spaces of older women in Santiago de Chile. Based on a non-probabilistic survey of 70 women aged 60 and over, three complementary mobility dimensions are analysed: weekly participation frequency (number of places visited), daily mobility intensity (accelerometer-based steps), and spatial extension beyond the neighbourhood. Negative binomial models indicate that weekly participation is primarily structured by labour engagement and functional illness: economically active women exhibit significantly higher participation rates, while functional illness is associated with reduced out-of-home activity. OLS models with log-transformed daily steps show substantial reductions in daily steps among women aged 80 or over and those reporting dependency when leaving home, with behaviourally meaningful differences in predicted values. Logistic regression results reveal that spatial extension is significantly associated with neighbourhood socioeconomic status and functional illness, suggesting that travel beyond local boundaries may reflect structural necessity in disadvantaged contexts rather than enhanced autonomy. Metro access and neighbourhood walkability display bivariate associations but do not retain independent statistical significance in multivariate specifications once controls are introduced. Overall, findings provide differentiated and partial support for accessibility-based explanations of activity spaces, and suggest that improving transport infrastructure alone may be insufficient to enhance participation and well-being in later life, highlighting the multidimensional, context-dependent and equity-sensitive nature of urban ageing and mobility in rapidly ageing cities of the Global South.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:04:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2709569</guid>
    </item>
    <item>
      <title>A Dynamic Analysis of the Built Environment-Travel Behavior Relationship Using Three Activity-Travel Surveys in the Austin, Texas Region</title>
      <link>https://trid.trb.org/View/2712626</link>
      <description><![CDATA[This study investigates the dynamic effects of the built environment on travel in Austin, Texas, over a 20-year period. Using three waves of household travel surveys from 1997, 2006, and 2017, the research employs a repeated cross-sectional approach to address the limitations of traditional longitudinal and cross-sectional studies, and to more accurately estimate effect sizes. Methodologically, we introduce a novel integration of machine learning and inferential modeling to uncover non-linear relationships and threshold effects of the built environment characteristics on travel. Using Gradient Boosted Decision Trees (GBDT) and Partial Dependence Plots (PDPs), we first identify optimal threshold points in the relationships, which are then incorporated into piecewise multilevel models. Findings from the study reveal that the built environment serves as a sustainable tool for managing travel in the long term, contributing 50% or more to the total feature importance in predicting individual travel—surpassing the combined effects of personal and household characteristics. Improved transit accessibility, enhanced local and regional accessibility, higher population and employment densities, and greater diversity are all associated with significant reductions in travel— particularly within their identified thresholds—though the magnitude of their influence varies across time periods and shows diminishing marginal returns. These findings highlight the potential of smart growth policies—such as expanding transit accessibility, promoting high-density and mixed-use development, and discouraging single-use development and peripheral sprawl—as effective strategies to reduce car dependency and manage travel demand. Moreover, the study demonstrates that the proposed integrated approach can effectively capture complex non-linear effects while enhancing flexibility and interpretability, reducing researcher bias, and enabling statistical inference—ultimately providing more robust and policy-relevant insights.]]></description>
      <pubDate>Mon, 15 Jun 2026 08:40:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712626</guid>
    </item>
    <item>
      <title>A systematic review of regression models for street vitality</title>
      <link>https://trid.trb.org/View/2670211</link>
      <description><![CDATA[Street vitality represents complex phenomena, influenced by multiple interacting factors, but increasingly considered as a mark of successful built environments. Despite the proliferating vitality modelling in urban areas over the past decade, there has been a lack of critical assessment of results’ replicability, particularly concerning whether there are consistent predicting factors and determinants. This systematic review focuses on regression-based studies of street vitality, aiming to comparatively assess the models used, the factors most frequently employed, and their implications. From 62 articles, 155 regression models were extracted, featuring 16 proxies for vitality and 536 significant independent variables. The most robust were the spatial regression models, which successfully predicted 72% of vitality proxies on average. The identified proxies capture the presence of people, user-generated content, street view perceptions, mobility metrics, and other built environment metrics. While the significance of functional diversity and road density as independent variables is reinforced, the relationship between street vitality proxies and other factors is not always consistent, potentially due to contextual and cultural dissimilarities, besides variations in the factors’ measurement or data quality. The emphasis on physical aspects and the high goodness-of-fit observed in certain models may inadvertently diminish the importance of temporal or tactical interventions. Having certain variables serve as both dependent and independent variables in separate models underscores an ambiguity surrounding the vitality notion, while the extent to which different proxies reflect the actual street vitality remains unanswered.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670211</guid>
    </item>
    <item>
      <title>The impact of rail transit station construction characteristics on urban vibrancy: an integrated approach based on the node-connection-place model and the explainable machine learning</title>
      <link>https://trid.trb.org/View/2672007</link>
      <description><![CDATA[Transit-oriented development (TOD) promotes population agglomeration around rail transit stations, enhances urban vibrancy, and contributes to sustainable urban development. A key objective of TOD is the creation of vibrant communities around these stations. This study measures the vibrancy of 245 rail transit station areas (RTSAs) in Hangzhou, constructs an indicator system for rail transit station construction characteristics, and investigates their complex relationships using explainable machine learning methods. The research's findings indicate that: (1) the characteristics of station construction contribute to approximately 20% of the variation observed in the vibrancy of RTSAs; (2) there are significant local nonlinear and threshold effects of station construction characteristics on the vibrancy; (3) a certain amount of interaction exists among various construction characteristics; (4) In terms of the impact of rail transit station construction characteristics on the vibrancy of RTSAs, there are significant differences among these stations, which exhibit distinct typologies and regular spatial distributions. During the rail transit construction process, it is crucial for both the city government and private sector stakeholders to understand the unique characteristics of each station and the varying contributions of different construction elements to urban vibrancy. This understanding is essential for promoting the development of rail transit and ensuring the sustainable development of the city as a whole.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672007</guid>
    </item>
    <item>
      <title>Do nearby activities result in short trips? Examining the relationship between spatial accessibility and travel behaviour in 15-minute neighbourhoods</title>
      <link>https://trid.trb.org/View/2698536</link>
      <description><![CDATA[Creating 15-minute (15-min) neighbourhoods is crucial for achieving mobility justice, promoting urban vitality, and reducing traffic congestion, air pollution, and energy consumption. However, limited research has examined whether these goals align with current travel behaviour. This paper presents a comprehensive framework for evaluating travel behaviour within 15-min neighbourhoods using mobile phone signalling data and point of interest (POI) data in the central area of Nanjing, China. First, the differences between commuting and non-commuting travel behaviour are analysed. Non-commuting travel behaviour is then used to reveal the relationship between i) the proximity of activities (i.e. spatial accessibility) and ii) travel distance and cumulative travel frequency. The results show that, compared with non-commuting travel, commuting travel has higher travel distances but lower cumulative travel frequencies, with consistently greater variability in both indicators. Within 15-min neighbourhoods, there is no statistically significant correlation between the spatial accessibility of daily service facilities and non-commuting travel distance or cumulative travel frequencies. Furthermore, rose diagram of travel behaviour and accessibility exhibit significantly different spatial distributions. These findings are valuable for informing the planning of 15-min neighbourhoods, as well as for promoting liveability, accessibility and walkability.]]></description>
      <pubDate>Fri, 15 May 2026 10:44:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698536</guid>
    </item>
    <item>
      <title>Being somewhere with someone: Understanding social segregation across activity space contexts and temporal variations in Wuhan China</title>
      <link>https://trid.trb.org/View/2689454</link>
      <description><![CDATA[Social segregation has long been a challenge to achieving social equality and fostering social integration. Despite the growing research on activity space segregation, few studies examined spatiotemporal variations from both place-based and people-based perspectives. We aimed to investigate spatiotemporal characteristics of social segregation by activity types from both placed-based and people-based perspectives using citywide mobile phone data in Wuhan. Regarding place-based social segregation, we found residential areas, workplaces, and leisure activity locations remained more segregated, while locations of education and eating & drinking were less segregated. Further, segregation was higher in residential areas at night, higher in workplaces during the day, dropped during morning rush hours in transportation locations, and showed only minor variation elsewhere. At the individual level, people tend to visit non-residential activity locations aligned with their socioeconomic status (SES), thereby reinforced their isolation, especially for people with higher SES. Our findings advance our understanding of how place-level social segregation unfolds across multiple activity locations and across different time periods of day through a dynamic activity space perspective. It further enriches nuanced understanding of social segregation by integrating place-based and people-based perspectives simultaneously. Our findings could help inform location-specific desegregation strategies and guide people-center policies tailored to individuals with different SES to promote social inclusions.]]></description>
      <pubDate>Mon, 27 Apr 2026 14:58:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2689454</guid>
    </item>
    <item>
      <title>Capacity Vehicle Routing Problem with Time Windows: Simulation Tool for Footprint Network Design</title>
      <link>https://trid.trb.org/View/2579235</link>
      <description><![CDATA[The paper focuses on a decision support system designed for logistic experts and aimed at addressing Vehicle Routing Problem that includes multi-vehicles and multi-depot with time constraints and considers the capacities of vehicles and logistic nodes too. The paper proposes a novel solution featuring a three-layer architecture and a system able to simulate the behavior of the network. Therefore, the paper proposes a tool to assess the impact of changes in volumes and capacities on overall delivery times. The integration of information about sorting nodes, delivery nodes, travel distances, and daily item demands is crucial for simulating accurate arrival times at each destination point. Computational experiments are depicted for validating the model and showing its effectiveness and its application.]]></description>
      <pubDate>Tue, 31 Mar 2026 16:34:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579235</guid>
    </item>
    <item>
      <title>Assessing street vitality using functional density as a proxy</title>
      <link>https://trid.trb.org/View/2569610</link>
      <description><![CDATA[Maintaining street vitality, understood as a concentration of human activity, is a key priority for urban agendas, yet predicting and understanding it remains challenging. This paper examines street vitality in 10 European cities using functional density as a proxy, measured as the number of unique points of interest (POI) classes per street segment length. Leveraging OpenStreetMap (OSM) data and a spatial lag regression model with a log-transformed dependent variable, the analysis accounts for spatial dependencies while examining the determinants of functional density across cities and within street segments characterised by high functional density. Findings show that morphological factors influence functional density more consistently than transport-related ones. Higher clustering of functional density in city-wide models indicates the need for strategic planning around vitality, whereas the weaker clustering observed in models focused on streets with high functional density indicates greater consideration needed for local street-level attributes. Long street segments appear to enhance functional density at the city level, while compact urban forms support vitality in already vibrant areas. Commercial density enhances functional density city-wide, while residential presence is more significant in streets with high functional density. Transport infrastructure explains better street vitality clustering at the city level, but its role weakens among other variables in already dense areas.]]></description>
      <pubDate>Tue, 15 Jul 2025 09:47:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569610</guid>
    </item>
    <item>
      <title>Railway-station-area vitality in response to COVID-19: A case study of diverse Japanese cities</title>
      <link>https://trid.trb.org/View/2534669</link>
      <description><![CDATA[This study examines the impact of COVID-19 on the number of visitors weighted by their time spent at facilities within and nearby railway stations, analyzing short-term demand losses and long-term recovery trends at 69 major stations in diverse Japanese cities using aggregated mobile phone data. The authors refer to this as “station area vitality”. They extend previous research by integrating external variables, such as land use and Points of Interest (POIs), to explain vitality drops and forecast recovery over two years. The findings reveal that multifunctional station areas - those combining leisure shopping, daily-needs shopping, and transport purposes - showed greater resilience during the pandemic. This underscores the value of mixed-use development and flexible zoning for enhancing station resilience. Furthermore, the forecasting models, particularly ARIMAX and LSTM, can to some degree predict long-term recovery trends during or after the pandemic when external variables and extended learning periods are included. The authors hence suggest that this can offer critical insights for urban planners and policymakers to build more resilient station areas and to forecast their performance during a new pandemic.]]></description>
      <pubDate>Mon, 21 Apr 2025 12:12:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2534669</guid>
    </item>
    <item>
      <title>Assessing the space-use efficiency of French cities by coupling city volumes with mobile data traffic</title>
      <link>https://trid.trb.org/View/2527184</link>
      <description><![CDATA[In light of climate change, resource scarcity, and population growth, it becomes increasingly important to use the existing built-up space of cities efficiently. However, the degree to which the available three-dimensional (3D) urban space is actually being utilized by human activities has never been studied systematically at a high spatial and temporal resolution. Here, the authors explore the space-use efficiency across 20 major French cities, measured by the dynamic occupancy rates of their volumes. The occupancies (number of people present) are predicted by a random forest model trained on fine-grained mobile data traffic from 2019, while the urban volumes are derived from detailed 3D city models. The results show a surprisingly common ‘donut-like’ organization of cities, where the space occupancy is low in the city center, becomes high in the immediate surroundings, and then low again in the suburbs. This hitherto hidden regularity is associated with the distribution of urban amenities and reveals a potential to increase the utilization of under-used spaces especially in the city centers.]]></description>
      <pubDate>Fri, 18 Apr 2025 12:25:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2527184</guid>
    </item>
    <item>
      <title>A quantified planning method of local public transport services for expanding residents’ activity opportunities</title>
      <link>https://trid.trb.org/View/2445515</link>
      <description><![CDATA[The purpose of public transport is to expand activity opportunities of residents. Many public transport planning methods focus on the needs of residents. However, residents can adapt to the environment and form limited needs in areas with low public transport service levels, such as rural areas. Therefore, it is important to focus on activity opportunities (various states of people (being) and actions (being able)) rather than needs. The authors constructed a method for local public transport planning that focuses on activity opportunities; however, the variables and solutions of the model were abstract and thus did not reach the stage of practical application. Therefore, this study aimed to put into practical use a supporting method for local public transport planning. This method consists of a “measurement model for activity opportunity,” in which a given bus service and the ability to use it are variables, and an “evaluation model for planning alternatives” that incorporates a social relationship function and disparity principle. Through a case analysis in a rural area to which this method was applied, its usefulness was verified, and it was confirmed that it can contribute to public transport planning to increase activity opportunities.]]></description>
      <pubDate>Wed, 27 Nov 2024 13:44:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2445515</guid>
    </item>
    <item>
      <title>FDOT Land Use Analysis to Enhance Successful Logistics Activity Center Development in Florida</title>
      <link>https://trid.trb.org/View/2389248</link>
      <description><![CDATA[Florida’s massive population growth brings higher emphasis on the freight and logistics aspect in Florida and the challenge of maximizing the economic development potential by attracting more companies to the State. Above mentioned challenge necessitated this project to find optimal areas which are most suitable for logistics activities to be located within Florida as a solution. In this study, the research team performed a literature review, conducted surveys and interviews with experts to validate survey results, developed crucial factors and final weighing scheme for Logistics Activity Center (LAC) development potential. The authors acquired Geographic Information System (GIS) Data from trusted sources owned by U.S/ Florida Govt. entities and created a LAC development potential and a corresponding heatmap for the entire State of Florida. All undevelopable lands were removed and then, on the final heat map, spot checks were prioritized based on the development potential of the land parcel and its land use type at the county level based on the combination of final LAC potential of the spot and the Land Use Type (Industrial/Vacant/Commercial/Agricultural, etc.) shapefiles. Final spots were validated using Google Earth and ArcGIS Pro, and GIS mapping was performed to build a total of five maps for each county: one for validation, two for suitable land use, two for conflicting land use, all parcels with a very high/high or moderate LAC development potential. In this report, five spots are presented for each of the 67 counties of Florida, i.e., a total of 335 maps out of which, for each county; three maps are for suitable land use with successful LAC potential and two maps are for conflicting land use with successful LAC potential which lie near Industrial areas and can be rezoned for Industrial purposes and make them shovel ready. The maps identified all parcels with a very high/high or moderate LAC development potential. Results showed that the methodology used in this study is extremely useful in locating/determining optimal spots at the county level, which can help towards rezoning of future land parcels (which have very high/high/moderate LAC development potential) to attract emerging businesses and maximize the economic development potential of the State.]]></description>
      <pubDate>Mon, 24 Jun 2024 09:22:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389248</guid>
    </item>
    <item>
      <title>Examining the directionality of mobility patterns in activity spaces: Introducing the ‘mobility snowflake’ visual analytic and measurement framework</title>
      <link>https://trid.trb.org/View/2359475</link>
      <description><![CDATA[Activity spaces characterise an individual's mobility patterns and provide critical insights important to a broad suite of applications. Emergent forms of disaggregate space-time data offer new opportunities to exploit a more granular approach to measuring and visualising activity spaces. Drawing on individual GPS trajectories for 365 participants covering a seven-day period the current paper presents a new measurement and visualisation framework examining the directionality of mobility patterns. This framework moves beyond existing work that measures activity spaces via a simple geometric shape (traditionally a convex hull) to introduce a new metric and associated visual analytic capturing a new dimension of the concept. Results have important consequences for policy and planning, with the hope that the framework can be redeployed across various situational and cultural contexts, leading to the creation of an expanding collection of comparative studies.]]></description>
      <pubDate>Tue, 30 Apr 2024 11:23:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2359475</guid>
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