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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>The synergistic effect between highway traffic flow and potential economic connectivity under network space in the megacity region</title>
      <link>https://trid.trb.org/View/2644224</link>
      <description><![CDATA[This study quantifies the synergistic relationship between transport flow and economic activity, as conventional methods like road accessibility and GDP are insufficient for highly mobile megacities. Synergy measures connections in complex systems, with flow data capturing the interplay between transport and economic elements. The study proposes a framework based on flow data and synergy effect theory to analyze this relationship in network space. Specifically, using highway traffic flow data and network analysis, we constructed the synergetic effects model to analyze the interplay between highway traffic flow and economy in the Greater Bay Area (GBA). The results showed that highway traffic flow exhibited significant spatial discrepancy, and primary highway traffic flow was located in the GBA in Shenzhen–Dongguan and Guangzhou–Foshan. The higher comprehensive economic indices were located on the Guangzhou–Foshan–Macao and Guangzhou–Shenzhen–Hong Kong. The potential economic connectivity strength of Guangzhou, Foshan and Shenzhen was significantly higher than that of other cities. The synergistic effect between highway traffic flow and potential economic connectivity in the GBA was highly related to the strength of highway traffic flow, and it was significantly higher in Guangzhou-Dongguan-Shenzhen than in other regions. This study can support sustained economic development and the implementation of optimized transportation layouts.]]></description>
      <pubDate>Fri, 20 Mar 2026 14:47:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2644224</guid>
    </item>
    <item>
      <title>Regional Reference Network Enhanced Tropospheric Modeling and Non-Nominal Troposphere Monitoring for GBAS in Air Transportation</title>
      <link>https://trid.trb.org/View/2591195</link>
      <description><![CDATA[The non-nominal troposphere induced by climate extremes poses a threat to the precision approach and landing of the civil aircraft in ground-based augmentation system (GBAS). However, there is currently no effective non-nominal troposphere monitoring method at both GBAS stations and aircrafts, which increases the integrity risk. This study proposes a novel approach for simultaneously modelling and monitoring ground station and aircraft non-nominal troposphere using precision point positioning (PPP) technology based on a regional reference network. The global navigation satellite system (GNSS) and meteorological data from the Hong Kong satellite positioning reference station network and numerical weather models from the European centre for medium-range weather forecasts are processed in all the year of 2017. A tropospheric correction (TC) model is used to correct station height-induced biases in zenith total delay (ZTD) obtained from PPP. By comparing the performance of 6 typical spatial interpolation algorithms in tropospheric delay interpolating, the universal Kriging algorithm is found to be the most suitable one which achieves a minimum mean absolute error (MAE) of 8.24 mm. The non-nominal troposphere is monitored using the constructed corrected ZTD map using universal Kriging method. A non-nominal troposphere up to 50 mm is observed, which can affect the integrity of the air navigation. Furthermore, the relationship between non-nominal troposphere and the rainfall is investigated. The study integrates widely distributed GNSS and meteorological data into a seamless non-nominal tropospheric monitoring service, enhancing the integrity of GBAS in air transportation.]]></description>
      <pubDate>Fri, 20 Mar 2026 14:10:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2591195</guid>
    </item>
    <item>
      <title>Electric vehicle service network design with integrated charging and battery reuse</title>
      <link>https://trid.trb.org/View/2626143</link>
      <description><![CDATA[Electric vehicles (EVs) have emerged in recent years as efficient solutions for freight transportation. This study addresses the EV service network design problem by integrating strategic transportation decisions with tactical recharging and swapping strategies throughout the logistics process. A primary contribution lies in modeling EVs and batteries as distinct resources and jointly optimizing their movements within a time-space network to enable battery swapping, reuse, and energy replenishment. We propose a practical column generation approach enhanced by a labeling algorithm that efficiently generates battery paths and accelerates convergence. Heuristics are employed to construct aggregated solutions, which are further refined using an optimization method to minimize battery swapping and derive optimal EV paths. Numerical experiments conducted in the Greater Bay Area and the Yangtze River Delta Economic Zone demonstrate the approach’s effectiveness and computational efficiency, highlighting its scalability for large-scale networks.]]></description>
      <pubDate>Wed, 25 Feb 2026 09:11:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2626143</guid>
    </item>
    <item>
      <title>Analysis of Injury Severity of Bus Crashes: A Random Parameters Logistic Model with Heterogeneity in Means Approach</title>
      <link>https://trid.trb.org/View/2613264</link>
      <description><![CDATA[Urban bus crashes in China have become a growing concern due to the expansion of bus systems, leading to increased injuries, fatalities, and property damage. Nonetheless, existing research has given limited attention to a comprehensive analysis of the bus crash severity in terms of heterogeneity, which may suffer from a biased and incorrect result. This study addresses this gap by analyzing bus crashes in Hong Kong from 2009 to 2019 using a random parameters logistic model with heterogeneity in means, confirming its necessity for interpreting crash severity through AIC indicators. Particularly, special junction and driver age under 45 variables produce heterogeneity, as well as careless maneuver, illegal maneuver, cross-roads, two ways, dual carriageway, more than 2 carriageways, speed limit over 80 km/h, multiple involved vehicles, vehicle age, and time of crash 21:00–6:59 significantly affect the crash severity level. The findings provide important insights for policymakers to enhance urban bus safety.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613264</guid>
    </item>
    <item>
      <title>Behaviour Model of Hong Kong Residents about Price Incentives on Shared Electric Scooters</title>
      <link>https://trid.trb.org/View/2613236</link>
      <description><![CDATA[Shared electric scooter service is going to operate in Hong Kong in the coming years. However, there is a lack of research about Hong Kong residents’ acceptance of shared e-scooter services. Besides, the degree to which they are willing to accept user incentives for picking up or returning bikes is unknown as well. This study adopted a field survey to obtain data from residents, combined with linear regression analysis to find the relationship between the minimum reward amount and walking distance under different maximum reward amounts. This study also conducted a cross-analysis on topics related to demographic characteristics and found the relationship between them and the minimum reward amount, walking distance. This study obtained the service pricing, suggestions on service operation, usage intentions, and potential travel patterns of Hong Kong residents and provided a forward-looking analysis of the operation of shared e-scooter services in Hong Kong.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613236</guid>
    </item>
    <item>
      <title>Calculation Method and Case Verification of Expressway Actual Capacity Based on ETC Gantry Data</title>
      <link>https://trid.trb.org/View/2613132</link>
      <description><![CDATA[A generative adversarial network (GAN) is used to repair the missing expressway section flow data, and a method of calculating expressway capacity based on electronic toll collection (ETC) gantry data is proposed. Taking 27 expressways in the Guangdong-Hong Kong-Macao Greater Bay Area as examples, the results show that under the condition of speed limits, some expressways near the city have higher traffic efficiency, and the capacity can be improved by more than 15% in a more stable operating environment. The proportion of trucks will have an effect of first increasing and then decreasing on the actual capacity of expressways. Reasonable control of the proportion of trucks to less than 21.54% during peak hours can help improve the traffic efficiency of expressways.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613132</guid>
    </item>
    <item>
      <title>A Functional Requirement Analysis for the Construction of Mobility-as-a-Service Platform Based on the Kano Model: A Case of the Guangdong-Hong Kong-Macao Greater Bay Area</title>
      <link>https://trid.trb.org/View/2613021</link>
      <description><![CDATA[This study explores the optimization of transportation services in the Guangdong-Hong Kong-Macao Greater Bay Area through the lens of Mobility-as-a-Service (MaaS). By surveying local residents’ mobility preferences and analyzing the unique transportation features of the Bay Area, this research identifies the essential functional requirements for an effective MaaS platform. The investigation encompasses extensive data collection to map out the region’s traffic infrastructure and discern distinct travel patterns across various locales. Utilizing the KANO model, the study conducts a comprehensive user survey, followed by meticulous data analysis to categorize features and rank them by importance. The findings culminate in a tailored MaaS platform model designed for the Bay Area, encapsulating strategic planning elements crucial for the integrated advancement of transportation services.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613021</guid>
    </item>
    <item>
      <title>Safety-Quantifiable Planar-Feature-Based LiDAR Localization With a Prior Map for Intelligent Vehicles in Urban Scenarios</title>
      <link>https://trid.trb.org/View/2617931</link>
      <description><![CDATA[Safety-quantifiable and accurate localization is of great importance for safety-critical applications with navigation requirements, such as intelligent vehicles (IV). LiDAR-based localization with the prior map is highly expected due to its high accuracy. However, how to reliably quantify the safety (quantify the maximum potential localization error) of LiDAR localization is still an open challenge. Integrity monitoring (IM) is one of the most stringent existing solutions to quantify the safety of satellite navigation, where usually tens of measurements are involved and interpreted by an almost locally linear model. Differently, the number of measurements involved in the LiDAR localization problem is significantly larger (e.g., 2000). Moreover, the LiDAR measurement model is highly non-linear. The convexity of the LiDAR localization is still to be quantified. To fill these gaps, this paper proposes a safety-quantifiable planar feature-based LiDAR localization method with a prior map. Specifically, the LiDAR localization framework utilizing representative planar features with maximum spectral attributes is proposed. The cardinality restriction facilitates feasible safety quantification regardless of thousands of measurements. To quantify the convexity of the LiDAR localization problem, the Hessian matrix of the planar feature measurement model is analytically derived. The local convex property during non-linear optimization of the localization model is quantified from dual perspectives. Additionally, different from existing methods, the protection level of the derived LiDAR localization is estimated for both translation and rotation to quantify the safety. The feasibility of the proposed method is validated using the datasets collected in typical urban canyons of Hong Kong.]]></description>
      <pubDate>Mon, 09 Feb 2026 08:53:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617931</guid>
    </item>
    <item>
      <title>Modeling Metro Passenger Routing Choices with a Fully Differentiable End-to-End Simulation-Based Optimization (Sbo) Approach</title>
      <link>https://trid.trb.org/View/2616187</link>
      <description><![CDATA[Metro systems in densely populated urban areas are often complicated, with some origin-destinations (OD) having multiple routes with similar travel times, leading to complex passenger routing behaviors. To improve modeling and calibration, this paper proposes a novel passenger route choice model with a metro simulator that accounts for passenger flows, queueing, congestion, and transfer delays. A novel, data-driven approach that utilizes a fully differentiable end-to-end simulation-based optimization (SBO) framework is proposed to calibrate the model, with the gradients calculated automatically and analytically using the iterative backpropagation (IB) algorithm. The SBO framework integrates data from multiple sources, including smart card data and train loadings, to calibrate the route choice parameters that best match the observed data. The full differentiability of the proposed framework enables it to calibrate for more than 20,000 passenger route choice ratios, covering every OD pair. To further improve the efficiency of the framework, a matrix-based optimization (MBO) mechanism is proposed, which provides better initial values for the SBO and ensures high efficiency with large datasets. A hybrid optimization algorithm combining MBO and SBO effectively calibrates the model, demonstrating high accuracy with synthetic data from actual passenger OD demands, where hypothesis tests are conducted for accuracies and significances. The accuracies and robustness are validated by experiments with synthetic passenger flow data, offering potential for optimizing passenger flow management in densely populated urban metro systems. Then, the SBO framework is extended for user equilibrium formulations with a crowding-aware route choice model and iterative metro simulations, calibrated by the hybrid optimization algorithm with additional matrix operations. Case studies with actual observed passenger flows are conducted to illustrate the proposed framework with multiple setups, exhibiting the heterogeneity of passenger route choice preferences and providing insights for operation management in the Hong Kong Mass Transit Railway system.]]></description>
      <pubDate>Mon, 09 Feb 2026 08:53:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2616187</guid>
    </item>
    <item>
      <title>Ground Treatment Associated with the Construction of Cross-Passages for the KCRC West Rail Phase I, Kwai Tsing Tunnels in Hong Kong</title>
      <link>https://trid.trb.org/View/2200138</link>
      <description><![CDATA[Ground treatment was required to consolidate soils for the formation of emergency evacuation cross passage adits between the two tubes of the Kowloon-Canton Railway Corporation, Tsing Tsuen Tunnels in Hong Kong. Jet grouting techniques were successfully employed to produce a sufficiently strong and watertight block of treated soil to permit safe and efficient excavation. The impact on the adjacent urban areas had to be considered and methods were developed to minimise the impacts to the public, traffic, services and adjacent structures, having regard to disturbance caused by excessive ground movements.]]></description>
      <pubDate>Fri, 06 Feb 2026 13:53:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2200138</guid>
    </item>
    <item>
      <title>Discovering metro passenger flow recovery patterns under unplanned disruptions: a disruption impact quantification-based clustering approach</title>
      <link>https://trid.trb.org/View/2627380</link>
      <description><![CDATA[Discovering metro passenger flow recovery patterns from historical unplanned disruptions enables operators to better prepare for a new disruption. The task is challenging as passenger flow recovery patterns are generated by different types of disruptions at different locations and times. We start with the Robust Principal Component Analysis (RPCA), a dimensionality reduction technique to calculate passenger flow change under disruption and quantify disruption impact. With this information, we modify the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) model with the tailor-made discrete input module and distance metric module, to discover the typical passenger flow recovery patterns with different shapes and sizes. Our approach is validated in the Hong Kong Mass Transit Railway system. The results show that our approach can discover interpretable recovery patterns that are easily neglected by other clustering methods, because of its ability to quantify and distinguish disruption impact on normal passenger flow.]]></description>
      <pubDate>Mon, 02 Feb 2026 09:33:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2627380</guid>
    </item>
    <item>
      <title>Impact of Climate Change on the Thermal Behavior of Long-Span Suspension Bridges</title>
      <link>https://trid.trb.org/View/2642986</link>
      <description><![CDATA[Climate change can alter environmental parameters such as air temperature, wind speed, and solar radiation, potentially leading to rising bridge temperatures and imposing additional thermal loads. This issue is not limited to specific regions or bridge types but poses a global challenge to bridges in all regions of all kinds. With the acceleration of global climate change, bridges worldwide face rising temperatures and related impacts, and therefore, evaluating their thermal performance under a future climate is critical. This study is the first to apply downscaled climate data to assess climate change impacts on bridges, specifically predicting future bridge effective temperatures and the associated displacements. Using the Tsing Ma Bridge as a case study, 22 global climate models (GCMs) under medium (SSP2-4.5) and very high (SSP5-8.5) emission scenarios with heat-transfer analysis are integrated to predict bridge effective temperatures. The results show that the predicted bridge effective temperatures will reach 45.84°C and 47.13°C by the year 2100, respectively. The effective temperature is expected to rise further to 46.37°C and 47.93°C by 2117, exceeding the design temperature value of 46.0°C by 2105 under SSP2-4.5 and 2065 under SSP5-8.5. Temperature-induced displacements are also expected to increase significantly. By 2100, vertical displacements are projected to increase by 24.5% under SSP2-4.5 and 33.3% under SSP5-8.5, while longitudinal displacements are expected to rise by 15.4% and 24.9%, respectively. Furthermore, the recent 10-year temperature observation data exceeded the GCM projections since 2015, suggesting that climate change may be accelerating and faster than expected.]]></description>
      <pubDate>Thu, 29 Jan 2026 17:02:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642986</guid>
    </item>
    <item>
      <title>Increasing flood hazards threaten metro system resilience under climate and demographic changes</title>
      <link>https://trid.trb.org/View/2615261</link>
      <description><![CDATA[Intensification of short-duration rainfall poses an increasing threat to urban metro systems, necessitating a thorough understanding of existing infrastructure's resistance in a warmer climate. This study systematically examines how future rainfall extremes and societal changes jointly affect metro system performance, using Hong Kong as a case study. We simulated city-scale flood inundation under the current climate baseline and three future representative emission scenarios using a grid-based flood hydrodynamic model. The study quantifies and characterizes flood hazard and risk, as well as metro performance curves at both station and line scales through integrating the simulated flood dynamics with demographic projections and infrastructure characteristics. Results show a substantial increase in flood hazard in low-lying coastal urban areas from the near to the far future under the highest emission scenario, while risk profiles remain comparatively stable. Short-duration rainfall intensity dominates the deterioration rates of metro functionality, while residual functionality and recovery capacity are primarily influenced by long-duration cumulative volume. Among performance-based resilience metrics, robustness emerges as the decisive factor influencing other components. High emissions in the far future present the most challenging scenario for metro system resilience, while other emission scenarios show more manageable impacts. Compared to demographic changes, climate-induced rainfall intensification exerts more significant influence on metro system resilience, particularly through cumulative rainfall volume. This research contributes a transferable framework for assessing infrastructure resilience under combined climate and societal stressors. By comparing their impacts, the study yields generalizable insights to guide adaptation of critical urban infrastructure, supporting robust planning for a complex future.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2615261</guid>
    </item>
    <item>
      <title>Electrification of a bus system in a hilly city considering gradient impacts</title>
      <link>https://trid.trb.org/View/2655833</link>
      <description><![CDATA[Electrifying a bus system in hilly cities is challenging, as the road gradient plays a significant role in vehicular energy consumption, influencing the configuration of bus fleet and the layout of charging facilities. In response, this study developed a data-driven large-scale simulation optimization model that explicitly considers the impact of road gradients, aiming to determine the optimal electric bus fleet and charging infrastructure deployment, with Hong Kong (a typical hilly city) as the study area. Results indicated that neglecting gradient characteristics would underestimate the system cost and life-cycle emissions. Meanwhile, when accounting for gradient impacts, the required number of charging stations and fleet size increased by 27% and 3%, respectively. Moreover, the spatial distribution of charging stations could be greatly influenced. Further scenario analysis indicated that charging speed and infrastructure costs are influential in shaping bus electrification strategies. The outcomes can be helpful for bus electrification in hilly cities.]]></description>
      <pubDate>Mon, 26 Jan 2026 08:41:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655833</guid>
    </item>
    <item>
      <title>Gendered impacts of public transport on social isolation and loneliness among older adults: Evidence from a natural experiment in Hong Kong</title>
      <link>https://trid.trb.org/View/2643842</link>
      <description><![CDATA[A well-designed public transport system has the potential to support social participation and alleviate social isolation and loneliness among older adults. However, limited research has explored whether such benefits differ between older men and women. Using a natural experiment involving a new metro line in Hong Kong, the cohort study (N = 449) of older people yields a surprising finding: contrary to previous studies suggesting that women are more likely than men to experience social isolation and loneliness, the analysis reveals that older men report higher levels of both. Despite this, the new metro line has not significantly reduced social isolation or loneliness among older men. In contrast, older women have actively engaged with the new metro line, especially for those with greater social participation at the baseline, leveraging it to strengthen their social networks and mitigate social isolation and loneliness. These findings suggest that public transport may not equally benefit all groups, underscoring the importance of considering gender differences, particularly the needs of older men, in transport planning to reduce social isolation and loneliness.]]></description>
      <pubDate>Thu, 15 Jan 2026 14:31:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643842</guid>
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