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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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    <item>
      <title>Optimizing Transit Connectivity: A Synchronization Model Applied to Porto Campanhã</title>
      <link>https://trid.trb.org/View/2671059</link>
      <description><![CDATA[In the context of transport networks, synchronization techniques refer to a set of optimization approaches whose output is the timetables of different lines obtained through the minimization of transfer waiting time and vehicle bunching. Accordingly, synchronization techniques can improve the overall quality of transfers in transport systems by making them smoother for passengers. The synchronization of transport lines at strategic locations improves the system’s overall connectivity and integration and, ultimately, its attractiveness to passengers. This work aimed to synchronize strategic transport lines connecting Porto to other cities, having Porto as the only focal point. The morning peak hours were selected as the analysis period. A synchronization model already proposed in the literature was adapted and applied to this case study. The results include the comparison between the real and synchronized timetables and the sensitivity analysis of the solutions obtained by changing headway and time window parameters.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671059</guid>
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    <item>
      <title>SimPRL: A Simple Contrastive Learning for Path Representation Learning by Joint GPS Trajectories and Road Paths</title>
      <link>https://trid.trb.org/View/2672804</link>
      <description><![CDATA[Path representations are widely applied in smart-city tasks, such as travel time estimation, road classification, and trajectory search. Existing approaches effectively learn these representations by jointly utilizing multi-mode data, including GPS trajectories, road paths, and road networks. Although these methods achieve state-of-the-art performance, the theoretical understanding of the importance and effectiveness of key designs in path representation pre-training remains unclear. Moreover, these methods often rely on hard-constrained labeled data and manual design, resulting in limited performance gains and high annotation costs. In this paper, we propose SimPRL, a simple yet powerful contrastive learning framework that capitalizes on unannotated data. Building on the exploration of key factors contributing to successful path representation learning, SimPRL integrates unannotated GPS trajectories and road paths directly through contrastive self-supervised learning. Specifically, we introduce a pre-training task that predicts correspondences between trajectories from different modes using a shared encoder, without requiring labeled data. We also design an auxiliary segment imputation task and a minimal trajectory sampling technique with random offsets for data augmentation. Additionally, we employ any trajectory within the mini-batch, except for the anchor itself, as the negative sample. Extensive experiments on two large-scale, real-world datasets from Chengdu and Porto demonstrate the effectiveness of SimPRL in two downstream tasks: travel time estimation and road classification. The results show that SimPRL not only surpasses state-of-the-art methods but also achieves more stable generalization and greater efficiency in terms of runtime and memory usage. Our source code is available at https://github.com/TXLiao/SimPRL]]></description>
      <pubDate>Wed, 24 Jun 2026 11:31:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672804</guid>
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      <title>Unravelling Integrated Travel Patterns: Profiling Intermodal Travelers for Sustainable Urban Mobility Development</title>
      <link>https://trid.trb.org/View/2681768</link>
      <description><![CDATA[Promoting intermodal mobility is increasingly seen as a key strategy for reducing car dependency and advancing sustainable transport. However, research on the diversity of intermodal users is still limited. This study addresses this gap by analysing intermodal users in Porto, Portugal, through a representative mobility survey and by conducting gender and generational segmentations. The findings reveal significant differences across intermodal segments. Women and Gen Z tend to be captive users, relying on intermodality due to a lack of alternatives, with longer travel times, higher PT usage (especially bus) and a greater tolerance for waiting for a transfer. In contrast, men and older generations exhibit more characteristics of choice users, citing perceived advantages of intermodality as key motivations such as cost, flexibility, and convenience, showing greater reliance on private cars and having a lower tolerance for waiting for a transfer. Such insights highlight the need for recognizing and addressing the distinct profiles and needs of intermodal users through more targeted strategies that can lead to more inclusive, sustainable and effective intermodal transport systems.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681768</guid>
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    <item>
      <title>The 15-Minute City in Porto, Portugal: Accessibility for the elderly</title>
      <link>https://trid.trb.org/View/2622294</link>
      <description><![CDATA[The concept of the 15-Minute City aims to enhance urban accessibility by ensuring that essential services are within a short walking distance. This study evaluates the accessibility of Porto, Portugal, particularly for the elderly, by assessing urban density, permeability, and walkability, with a specific focus on crossings and ramps. A five-step methodology was employed, including spatial analysis using QGIS and Place Syntax Tool, proximity assessments, and an in-situ survey of crossings and ramps in the CHP. The results indicate that while the city of Porto offers a dense and walkable urban environment, significant accessibility challenges remain due to inadequate ramp distribution. The data collection identified 80 crossings, of which only 60 were listed in OpenStreetMap, highlighting data inconsistencies. Additionally, 18 crossings lacked curb ramps, posing mobility barriers for elderly residents. These findings highlight the need of infrastructure improvements to support inclusive urban mobility. The study also proposes an automated method to enhance ramp data collection for broader applications. Addressing these gaps is crucial for achieving the equity and sustainability goals of the 15-Minute City model, ensuring that aging populations can navigate urban spaces safely and efficiently.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2622294</guid>
    </item>
    <item>
      <title>Gender differences in commuting patterns: a study of FEUP students' travel behaviour in selected academic years</title>
      <link>https://trid.trb.org/View/2604850</link>
      <description><![CDATA[Gender equity in transport systems has become a central concern in urban mobility research, particularly as societal roles evolve and new mobility paradigms emerge. University students, as both representatives of current socio-cultural dynamics and precursors of future behavioural trends, offer a unique lens through which to examine changing mobility patterns. This study presents a longitudinal analysis of gender differences in commuting behaviours among students at the Faculty of Engineering of the University of Porto (FEUP), located in the Greater Porto area of Portugal. This Faculty is an important traffic generator. The study uses personal survey data and spatial analysis from the 2006, 2012, 2017 and 2023 academic years. It employs a mixed-methods approach to examine the influence of gender equity on travel behaviour and housing choices and its evolution over time. The results explain tendencies and multifactorial gender differences in the choice of transport mode to reach the University. The researchers observed differences in transport mode preference between women and men. These findings suggest that urban planners, practitioners, policy and decision-makers should join efforts towards developing gender-sensitive strategies and integrated transport policy packages in university settings to reduce gender inequities in sustainable mobility. Promoting equitable and sustainable transport options is essential to addressing mobility-related gender disparities and fostering inclusive access to higher education.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604850</guid>
    </item>
    <item>
      <title>The growing dominance of cars in suburban areas</title>
      <link>https://trid.trb.org/View/2587265</link>
      <description><![CDATA[This study examines the patterns of car dependence in Lisbon and Porto, Portugal’s two largest metropolitan areas, utilizing an innovative framework known as the ABC of mobility. This model categorizes modes of transport into Active Mobility (A), Public Transport (B), and Car (C). Drawing from census data from 2011 and 2021, the authors assess the modal choices of commuting adults and students across municipalities. The findings reveal that central urban areas exhibit a distinct modal distribution, with car use increasing by approximately 1 % for every additional 2 km from the city center, primarily at the expense of Public Transport usage. In contrast, peripheral areas show significant reliance on cars, with over 75 % of trips made by car, whereas some central zones report car journeys at under 40 %. These results highlight the relationship between urban centrality and modal choice, emphasizing the role of Public Transport availability in shaping commuting behaviors.]]></description>
      <pubDate>Wed, 17 Sep 2025 10:55:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2587265</guid>
    </item>
    <item>
      <title>Advancing sustainable urban mobility: An empirical travel time analysis of the 15-minute city model in Porto</title>
      <link>https://trid.trb.org/View/2583278</link>
      <description><![CDATA[The Fifteen-Minute City (FMC) concept presents a transformative approach to urban planning, prioritizing accessibility to essential services within a 15-minute walk or cycling distance. This study evaluates the feasibility and practical implications of implementing the FMC model in Porto, Portugal, bridging theoretical concepts with real-world applications. Employing a Weibull hazard-based survival model, the research draws on data from over 11,000 trips to explore the relationship between travel times and urban mobility patterns. Results show that approximately 70% of trips in Porto are completed within 15 min, indicating partial alignment with FMC principles. However, significant barriers persist, including low active mobility (AM) adoption (less than 40% of trips) due to cultural preferences for motorized transport, inadequate infrastructure, and limited public awareness of AM benefits. By identifying temporal thresholds and examining influential variables shaping modal choices, the study provides actionable insights into the challenges and opportunities of FMC implementation. The findings highlight the need for targeted interventions to shift societal attitudes and reduce reliance on private vehicles, proposing strategies such as enhancing pedestrian pathways, expanding cycling networks, and promoting mixed-use zoning. These efforts aim to foster sustainable, health-conscious urban settings, reduce traffic congestion, and improve residents’ quality of life. The study concludes by suggesting directions for future research to further explore the scalability and adaptability of the FMC model in diverse urban contexts, ultimately contributing to more accessible and sustainable urban environments.]]></description>
      <pubDate>Tue, 09 Sep 2025 08:44:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2583278</guid>
    </item>
    <item>
      <title>Assessment of integrated rail and bus transport network design: Equity and efficiency perspectives</title>
      <link>https://trid.trb.org/View/2549278</link>
      <description><![CDATA[Recognizing the vital role of public transport (PuT) in accessibility, inclusivity, and quality of life, its planning must balance efficiency with equitable service coverage. This study examines PuT network design, integrating rail and bus services while incorporating equity considerations for a more efficient and socially equitable system. Despite extensive research on PuT network design (PTND), balancing these objectives remains a key challenge in transit planning. This paper presents a methodological framework that integrates PTND with Data Envelopment Analysis (DEA) to design and evaluate multiple PTND scenarios. These scenarios are assessed using equity-based perspectives: potential demand (PD), adjusted demand (AD), and transport needs (TN). The approach identifies efficient designs that maximize service coverage and social equity, addressing varying population demands and needs. The methodology is demonstrated through a case study in the metropolitan area of Porto (AMP), offering policymakers insights into PuT equity implications for the infrastructure planning and decision-making process. Two output-oriented DEA models were developed: one using service coverage adequacy (SCA) as output and another incorporating both SCA and the GINI coefficient (equity) to assess the impact of different equity perspectives on system efficiency. Results indicate that network designs based on AD performed better with higher efficiency scores than PD and TN, suggesting that AD better captures PuT demand needs and supports equitable service distribution. The findings emphasize the need to integrate population equity perspectives and multimodal transport to create more balanced and efficient PuT systems, ensuring fair access to mobility for diverse populations in the region.]]></description>
      <pubDate>Wed, 28 May 2025 16:23:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2549278</guid>
    </item>
    <item>
      <title>Intermodal mobility: A psychometric and behavioural analysis of public transport users in Porto Metropolitan Area</title>
      <link>https://trid.trb.org/View/2522106</link>
      <description><![CDATA[As a consequence of the several negative externalities associated with car usage, there is a growing pressure to promote more sustainable mobility habits through supporting transport alternatives. An increasingly attractive solution is the concept of intermodal mobility, i.e., the combination of different modes of transport in a single trip, leveraging the strengths of each mode to provide a more sustainable and efficient transport option.Despite its potential, research on intermodal mobility remains limited with studies focusing on the travel behaviour of intermodal users being especially rare. However, to gain a comprehensive understanding of intermodality and its potential role in promoting sustainable mobility, it is crucial to explore the intermodal travel behaviour from the user’s point of view, including their patterns and motivations.Accordingly, the goal of this study was to analyse the travel behaviour of intermodal users, focusing particularly on those that combine public transport (PT). Using a representative mobility survey conducted by the Portuguese National Statistics Institute to the Porto Metropolitan Area (with 40 393 respondents, 1868 of whom intermodal PT users), the authors have identified and characterized distinct profiles of intermodal PT users through marketing segmentation.The market segmentation analyses have revealed two profiles of intermodal PT users based on their motivations and perceptions of using PT (i.e., psychometric segmentation) and four profiles based on their main modes of intermodal travel (i.e., behavioural segmentation). Notably, a connection between the psychometric and behavioural segments has been found: choice riders are significantly more likely to use rail options such as metro and train, while captive riders are much more dependent on buses. These findings hold significant policy implications for the promotion of intermodal PT systems, including by highlighting the competitiveness of rail against the private car and the reliance of the most socially disadvantaged groups on the bus.]]></description>
      <pubDate>Mon, 31 Mar 2025 16:15:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2522106</guid>
    </item>
    <item>
      <title>Deep neural network for damage detection in Infante Dom Henrique bridge using multi-sensor data</title>
      <link>https://trid.trb.org/View/2485357</link>
      <description><![CDATA[This paper proposes a data-driven approach to detect damage using monitoring data from the Infante Dom Henrique bridge in Porto. The main contribution of this work lies in exploiting the combination of raw measurements from local (inclinations and stresses) and global (eigenfrequencies) variables in a full-scale structural health monitoring application. The authors exhaustively analyze and compare the advantages and drawbacks of employing each variable type and explore the potential of combining them. An autoencoder-based deep neural network is employed to properly reconstruct measurements under healthy conditions of the structure, which are influenced by environmental and operational variability. The damage-sensitive feature for outlier detection is the reconstruction error that measures the discrepancy between current and estimated measurements. Three autoencoder architectures are designed according to the input: local variables, global variables, and their combination. To test the performance of the methodology in detecting the presence of damage, the authors employ a finite element model to calculate the relative change in the structural response induced by damage at four locations. These relative variations between the healthy and damaged responses are employed to affect the experimental testing data, thus producing realistic time-domain damaged measurements. The authors analyze the receiver operating characteristic curves and investigate the latent feature representation of the data provided by the autoencoder in the presence of damage. Results reveal the existence of synergies between the different variable types, producing almost perfect classifiers throughout the performed tests when combining the two available data sources. When damage occurs far from the instrumented sections, the area under the curve in the combined approach increases compared to using local variables only. The classificatoin metrics also demonstrate the enhancement of combining both sources of data in the damage detection task, reaching close to precision values for the four considered test damage scenarios. Finally, the authors also investigate the capability of local variables to localize the damage, demonstrating the potential of including these variables in the damage detection task.]]></description>
      <pubDate>Tue, 18 Mar 2025 09:42:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2485357</guid>
    </item>
    <item>
      <title>Active travel in the university setting: Assessing the effects of social behavior, socioeconomics, and spatial location</title>
      <link>https://trid.trb.org/View/2506281</link>
      <description><![CDATA[University campuses are pooling efforts to promote active mobility to reduce their negative impacts on the urban environment, which is significantly influenced by the overreliance on motorized modes of transport. Providing sufficient and safe accessibility conditions for active travel has been highlighted as a crucial strategy for transforming campuses into more livable and sustainable areas in cities. To further explore the likelihood of active mobility uptake at university campuses, this study explored university students’ mobility patterns over time, examining the role of social behavior, socioeconomics, and spatial location factors. The Faculty of Engineering at the University of Porto, Greater Oporto, Portugal, provided the empirical focus for this research. The data analyzed were acquired through surveys of representative samples and spatial analysis over the academic years of 2012, 2017, and 2023. The statistical analysis explained the tendencies and multifactorial influences on travel behavior among university students. Results indicated that travel distance is associated with housing options and travel costs, whereas access to a metro station was associated with walking or cycling. Hence, this study contributed to a deeper understanding of active travel behavior. It provided insights to guide planning practitioners and decision makers in creating integrated transport policy packages that address the barriers and needs of the university community and the surrounding neighborhoods.]]></description>
      <pubDate>Thu, 13 Feb 2025 17:25:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2506281</guid>
    </item>
    <item>
      <title>The Impact of CNG on Buses Fleet Decarbonization: A Case Study</title>
      <link>https://trid.trb.org/View/2407132</link>
      <description><![CDATA[By 2050, and in the context of decarbonization and carbon neutrality, many companies worldwide are looking for low-carbon alternatives. Transport companies are probably the most challenging due to the continuing growth in global demand and the high dependency on fossil fuels. Some alternatives are emerging to replace conventional diesel vehicles and thus reduce greenhouse gas emissions and air pollutants. One of these alternatives is the adoption of compressed natural gas (CNG). In this paper, the authors provide a detailed study of the current emissions from the largest bus fleet company in the metropolitan area of Oporto. For this analysis, the authors used a top-down and a bottom-up methodology based on EMEP/EEA guidebook to compute the CO₂ and air pollution (CO, NMVOC, PM₂.₅, and NOₓ) emissions from the fleet. Fuel consumption, energy consumption, vehicle slaughter, electric bus incorporation, and the investments made were taken into consideration in the analyses. From the case study, the overall reduction in CO₂ emission was just 6.3%, and the emission factors (air pollutants) from CNG-powered buses and diesel-powered buses are closer and closer. For confirming these results and question the effectiveness of the fleet transitions from diesel to CNG vehicles, the authors analysed two scenarios. The obtained results reveal the potential and effectiveness of electric buses and other fuel alternatives to reduce CO₂ and air pollution.]]></description>
      <pubDate>Mon, 13 Jan 2025 11:12:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407132</guid>
    </item>
    <item>
      <title>What Is Leading the Choice Between Motorized and Non-motorized Transport Modes? The Case of Porto Metropolitan Area</title>
      <link>https://trid.trb.org/View/2407982</link>
      <description><![CDATA[Substantial changes are needed to combat traffic jams and improve air quality. Active and non-motorized travel choices allow more sustainable urban mobility and bring intrinsic benefits to the quality of life of each individual and public health. This study aims to understand better the characteristics that influence individuals’ preference for certain types of transport modes in their daily routines in the Porto Metropolitan Area. A mobility survey was carried out by Statistic Portugal in which about 80,000 residents in the Porto Metropolitan Area were interviewed, considering 41 relevant characteristics that can influence the type of transport chosen for a trip. In this research, it was found that about 80% of the respondents preferred to travel using motorized transport, and only 20% used soft modes for their daily trips. The method proposed in this paper considers a multinomial discrete choice model that allows the analysis of different combinations of characteristics (independent variable), having the dependent variable as the transport mode chosen by the respondents in their trips. Through subjective questions about the available data, it is intended to analyze which characteristic exerts the most significant influence on citizen decision-making.]]></description>
      <pubDate>Tue, 24 Dec 2024 16:46:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407982</guid>
    </item>
    <item>
      <title>Understanding the impact of COVID-19 on mobility behavior of public transport passengers: the case of Metropolitan Area of Porto</title>
      <link>https://trid.trb.org/View/2439948</link>
      <description><![CDATA[Public transport systems worldwide experienced significant declines in usage during the COVID-19 pandemic due to lockdowns and work-from-home mandates. While numerous studies have examined these phenomena, there is still a need for empirical evidence that not only documents what occurred but also provides actionable insights for future transport planning. This study aims to enhance understanding of public transport passengers’ mobility behaviors during different stages of the pandemic, using the Metropolitan Area of Porto, Portugal, as a case study. Automated Fare Collection data from 2020 were analyzed and compared with data from the pre-pandemic year of 2019. The analysis included temporal, spatial, spatio-temporal, and sociodemographic dimensions. Key patterns and trends identified include a rapid recovery of ridership post-restriction easing, homogenized daily travel patterns, varied impacts on different transport modes, and significant shifts in demographic travel behaviors. These findings highlight the resilience of public transport demand and suggest that adaptive scheduling, enhanced safety measures, targeted support for vulnerable groups, promotion of off-peak travel, investment in bus infrastructure, and encouragement of multi-modal transport are essential strategies. Implementing these strategies can help improve public transport planning and mitigate the adverse effects of future crises.]]></description>
      <pubDate>Wed, 30 Oct 2024 17:16:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2439948</guid>
    </item>
    <item>
      <title>The application of direct ridership models in the evaluation of the expansion of the Porto Light Rail Transit</title>
      <link>https://trid.trb.org/View/2423558</link>
      <description><![CDATA[The main purpose of this paper is to show how a direct demand ride model coupled with a transfer model was able to support the choice of alternative routes for the expansion of the light rail system serving the Porto Metropolitan Area. After an overview of the literature on direct ridership models, emphasizing some key issues such as the need for a systematic assessment of their forecasting performance, the issues related to the definition of the pedestrian catchment area and the limitations of the simultaneous consideration of demand and supply effects, the paper moves into the case study, providing some background information on current occupation densities, land uses and mobility patterns, as well as on the performance of the existing LRT in the Metropolitan Area of Porto. The development of the direct ridership model, measuring the potential attractiveness of each station, and the transfer model, measuring the number of transfers at each station, are presented in detail. A justification is provided why, in this case, a two-step modelling approach was necessary. Further details about the statistical tests for model validation are also provided. After a brief characterization of the alternative routes under analysis for the expansion of the network, the modelling results are presented enabling a comparative assessment of the potential performance of each proposed route. The paper ends with a discussion of the relevance of this modelling results vis a vis the actual final decisions on investment priorities taken jointly by the Metropolitan Council and the Metro Company.]]></description>
      <pubDate>Mon, 30 Sep 2024 17:21:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2423558</guid>
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