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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>Context-embedded migration networks: Regional spillovers and network interdependence in intercity migration in Hubei, China</title>
      <link>https://trid.trb.org/View/2706382</link>
      <description><![CDATA[Conventional gravity origin-destination (OD) models treat cities as independent and migration as isolated bilateral outcomes, overlooking that cities are embedded in regional rings and that flows interact. We propose a context-embedded migration framework that extends OD modeling with (1) ring-based spillovers computed from k-nearest-neighbor city rings and (2) path-dependent flow-interaction terms capturing reinforcing and competing relationships among flows. Using Baidu Huiyan intercity mobility data for Hubei Province (2023–2024) with socioeconomic indicators, we estimate baseline, spillover, and interaction-augmented models. In this study, the dependent variable captures short-term intercity mobility flows derived from consecutive location changes and is interpreted as a proxy for migration-related population movements rather than permanent migration in the demographic sense. Indicators reveal significant negative spillovers at both origins and destinations, implying that nearby developed cities can suppress local out-migration and reduce in-migration attractiveness. Adding flow-interaction terms further improves fit, increasing adjusted R2from 0.695 to 0.821, and reveals strong interdependence among migration paths: out-migration is amplified by neighboring origins' outflows, while destination-side flows exhibit significant co-movement across nearby receiving cities. Overall, intercity migration is jointly governed by regional ring structure and interactive flow behavior, offering a more realistic alternative to conventional gravity models and informing regional coordination and population governance.]]></description>
      <pubDate>Tue, 30 Jun 2026 17:04:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706382</guid>
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    <item>
      <title>Florida Intercity Passenger Rail “Vision Plan”: Executive Report</title>
      <link>https://trid.trb.org/View/2711603</link>
      <description><![CDATA[The Florida Intercity Passenger Rail “Vision Plan” Executive Report presents a 2006 framework for developing a statewide intercity passenger rail system in Florida through incremental investment in existing freight rail corridors, highway rights-of-way, and new dedicated passenger infrastructure. Prepared for the Florida Department of Transportation, the report responds to rapid population growth, rising intercity travel demand, and increasing constraints on highway and airport expansion. It evaluates two principal alternatives: an Inland Route using mainly CSX and the South Florida Rail Corridor to connect Miami, Orlando, Tampa, and Jacksonville; and a Coastal Route using the Florida East Coast Railway corridor, the South Florida Rail Corridor, the Beachline Expressway, and I-4 to serve East Coast markets while linking Jacksonville, Orlando, Tampa, and Miami. The report ultimately concludes that the strongest statewide system would combine feasible elements of both alternatives rather than treat them as mutually exclusive. The study is historically significant because major elements of its Coastal Route anticipated the corridor logic later used by Brightline. Brightline’s Miami–Orlando service follows the FEC corridor for much of South Florida and the East Coast, and uses the Beachline/SR 528 corridor for the Orlando connection, although Brightline uses the FEC tracks south of West Palm Beach into Miami rather than the South Florida Rail Corridor assumed in the 2006 Vision Plan. Brightline’s contemplated Tampa extension also parallels the report’s use of the I-4 right-of-way between Orlando and Tampa. The Vision Plan estimated that a phased system operating at 79, 110, and 125 mph could achieve positive operating and benefit-cost ratios while improving passenger mobility, freight capacity, grade-crossing safety, energy efficiency, emissions, and station-area development. Its recommended next steps included environmental review, preliminary engineering, freight railroad negotiations, local partnerships, and funding development.]]></description>
      <pubDate>Sat, 27 Jun 2026 15:40:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711603</guid>
    </item>
    <item>
      <title>Young people preferences about enhanced transportation services for intercity trips: An integrated choice and latent variable approach</title>
      <link>https://trid.trb.org/View/2614572</link>
      <description><![CDATA[With rapid urbanization, the demand for intercity travel is increasing, along with the variety of travel options due to technological advancements. However, prior studies on intercity travel mode choice have rarely considered functional amenities and psychological factors, often relying on revealed preference (RP) or stated preference (SP) data. This study designed an RP and SP questionnaire based on a trip chain integrating intra- and intercity mobility, focusing on the Hefei metropolitan area in China. Utilizing RP-SP fusion data, an Integrated Choice and Latent Variable framework incorporating random taste heterogeneity and psychological characteristics was developed to investigate travelers' mode choice behavior for conventional train, high-speed rail, intercity bus, private car, and intercity ride-hailing. Findings indicate that intercity in-vehicle time and cost are the most influential factors, with significant heterogeneity among travelers. There is lower satisfaction with the in-vehicle time of trains and buses, and the costs associated with buses and ride-hailing services. Intra-city access time is also crucial, while service attributes like catering and hygiene conditions, Wi-Fi availability show minimal impact. Psychological traits, including safety concern, hedonism, and social anxiety, significantly affect intercity travel preferences. Elasticity analysis suggests that intercity buses’ market growth potential comes mainly from train and ride-hailing consumers.]]></description>
      <pubDate>Wed, 24 Jun 2026 13:22:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2614572</guid>
    </item>
    <item>
      <title>How Much Can Backhaul Empty Electric Trucks Reduce Charging Wait Times for Private Electric Cars During Intercity Travels?</title>
      <link>https://trid.trb.org/View/2665597</link>
      <description><![CDATA[Mitigating negative user experiences in electric vehicle adoption is a crucial strategy for advancing widespread transportation electrification. To reduce the unavoidable charging wait times faced by private electric cars (PECs) during intercity long-distance travel, caused by their limited driving range and slow charging speeds, this article explores an optimization model that leverages backhaul empty electric trucks (BEETs) as temporary mobile chargers to increase the service capacity of fixed charging stations. To address the optimization of BEETs serving PECs, we first construct a model in which all BEETs are guaranteed profits, while jointly maximizing their profits and overall social benefits. Due to the inclusion of nonlinear terms, the model falls under the category of mixed-integer nonlinear programming (MINLP). To enable efficient computation, we propose a model transformation method based on time discretization, converting the original MINLP into a mixed-integer linear programming (MILP) formulation. Case study results from Sichuan, China, demonstrate that BEETs, by proactively detouring to offer charging services, can significantly reduce PECs’ cumulative waiting time. The system delivers a high social benefit-to-cost ratio, underscoring the dual role of BEETs as both profit-generating assets and effective delay-reduction tools without requiring additional infrastructure. Sensitivity analyses offer systematic managerial insights for addressing future development trends.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:13:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665597</guid>
    </item>
    <item>
      <title>The impact of intercity population mobility on intra-urban regional income disparities: A cross-scale spatial study</title>
      <link>https://trid.trb.org/View/2679961</link>
      <description><![CDATA[Although regional income disparities have drawn significant attention as a pressing practical issue for most countries, particularly developing ones, the existing literature on human mobility and regional income disparities has predominantly focused on the perspective of the migration of the floating population. To date, no research has investigated the impact of daily intercity population mobility on regional income disparities. Departing from previous research that analyzes the effect of the floating population's migration intensity, this study offers empirical evidence from a network-based perspective. Using data from China, the findings of this study demonstrate that daily intercity population mobility mitigates regional income disparities, while also exhibiting a spatial spillover effect that exacerbates regional income disparities in neighboring regions. The study also examines heterogeneity in these effects through two dimensions: transportation mode heterogeneity and network metric heterogeneity. Furthermore, this study reveals a cross-scale relationship between population mobility behavior and its economic effects—specifically, large-scale intercity population mobility influences small-scale intra-urban economic development. This research broadens the research perspective on human mobility and regional income disparities, contributing to the theoretical expansion of urban network externalities. It also offers practical implications for policymaking aimed at regional coordinated development.]]></description>
      <pubDate>Wed, 17 Jun 2026 16:13:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2679961</guid>
    </item>
    <item>
      <title>Relationship between Resilience and Topological Structure and Their Application in the Planning of Zhejiang Province Intercity Road Networks</title>
      <link>https://trid.trb.org/View/2658318</link>
      <description><![CDATA[Deteriorating global climate that contributes to increasing external disturbances involving hurricanes, floods, heavy rains, mudslides, landslides, earthquakes, and traffic accidents often causes disruptions in certain roads. However, a road network with high resilience can almost retain its global network efficiency, depending on its effective self-reorganization, even if certain roads are disrupted. By integrating complex network theory into resilient city theory, the study investigates the impact of different road network topologies on road network resilience and proposes strategies for spatial planning for resilient road networks. Firstly, the theoretical definition of road network resilience is proposed; the implications of global network efficiency, network collapse threshold, and network resilience index are expounded; the assessment method for the road network resilience indices is put forward; and simulation experiments that measure road network resilience indices under both random and directed disturbances are established. Secondly, the results of the theoretical research are applied to the analysis of the structural resilience of intercity road networks in Zhejiang Province of China: (1) various factors, including existing intercity road network infrastructure, urban distribution, population growth, industrial structure change, and urban–rural integration in Zhejiang Province, are taken into account for comprehensive analysis, and the forecast of demands for the intercity road network in Zhejiang Province from 2021 to 2035 is proposed by qualitative and quantitative methodologies; (2) with the patterns of morphological growth and density distribution as spatial planning variables, four road network planning schemes are proposed for Zhejiang Province, and the corresponding road network topological models are then established; (3) the network resilience indices of the four planning schemes are measured by simulation experiments under random and directional disturbances; (4) the characteristics of the four planning schemes under random and directed disturbances are analyzed. The results are as follows: (1) the pattern of growth morphology is the primary factor influencing network resilience, where the growth shape of a grid is favorable for resisting both random and directed disturbances. Under random disturbance, the change in global network efficiency is primarily influenced by the pattern of density distribution, which then serves as the main influencing factor of the network collapse threshold under directed disturbance. (2) It is recommended that the intercity road planning scheme of “grid growth morphology plus collective increase of road density distribution” be adopted for Zhejiang Province from 2021 to 2035. (3) In light of the time-lag issue between population growth and the development of intercity road networks, this study proposes corresponding planning strategies for intercity road networks from two perspectives: spatial growth patterns and construction prioritization. The study findings provide references for the analysis of the correlation between road network structure and resilience.]]></description>
      <pubDate>Wed, 29 Apr 2026 09:10:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658318</guid>
    </item>
    <item>
      <title>Investigating intercity commuting using distance decay in a two-stage regression framework: A case study of Shenzhen Metropolitan Area in China</title>
      <link>https://trid.trb.org/View/2670397</link>
      <description><![CDATA[Metropolitan areas are the most concentrated spaces of population and economic activity. Intercity commuting is not only a core driver of metropolitan operations but also an important indicator of metropolitan integration. However, existing studies lack a systematic framework to characterize intercity commuting and compare it with intracity commuting. This study uses mobile phone signaling data from the Shenzhen Metropolitan Area and proposes a two-stage regression framework. In the first stage, a flow-based geographically weighted regression model is used to estimate distance decay coefficients; in the second stage, random forest combined with SHAP analysis is applied to examine the influence of the built environment. The results show that intercity commuting decays faster than intracity commuting and exhibits spatial heterogeneity. Along city boundaries, short-distance intercity commuting shows quick decay due to limited transport supply and administrative barriers; along the perpendicular direction, medium- and long-distance intercity commuting is influenced by cross-border coordination, high-level transport infrastructure, and housing price differences, which reduce decay, but poor connectivity or high combined costs of housing and transport can still increase it. This framework systematically reveals the distance sensitivity and spatial heterogeneity of intercity commuting, enabling comparison with intracity commuting and providing empirical evidence for metropolitan integration and sustainable development]]></description>
      <pubDate>Tue, 28 Apr 2026 17:06:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670397</guid>
    </item>
    <item>
      <title>High-speed rail and the spatial economy</title>
      <link>https://trid.trb.org/View/2652546</link>
      <description><![CDATA[High-speed rail (HSR) is expanding rapidly worldwide. This review identifies three defining features of HSR: its strong appeal to high-value business travelers, the presence of long-haul economies whereby costs per kilometer decline with distance, and its capacity to enable intercity commuting between cities. These characteristics lead to non-trivial implications for the spatial economy. While HSR infrastructure is costly, travel-time savings and induced economic spatial reallocation can be substantial. We review both cost–benefit analyzes and empirical evidence, and argue that general equilibrium effects are central to understanding the full economic impact of HSR.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652546</guid>
    </item>
    <item>
      <title>Research on intercity green travel strategy based on tripartite evolutionary game</title>
      <link>https://trid.trb.org/View/2655916</link>
      <description><![CDATA[Developing green passenger transportation is beneficial for reducing air pollution emissions and improving the living environment of residents. However, research that comprehensively considers the two components of intercity travel, intercity transportation and intra-city connecting transportation, remains insufficient. To design an intercity green travel strategy with a continuous green guidance effect, this paper develops a tripartite evolutionary game model, with the government, high-speed rail enterprises, and intra-city public transportation enterprises as the key players. From the perspective of the entire intercity travel process, we analyze the evolutionary stable strategies of game participants and the applicable scopes of these strategies, and discuss the green travel strategies suitable for participants to adopt in different periods through case simulation. The simulation results show that (1) the cost to the government of ignoring passenger transport environmental protection significantly influences its decision-making. (2) Short-term strategy is relatively more advantageous. At this time, the government's subsidy support policy for the green passenger transport enterprises is also more effective. (3) In the long term, the government's choice of strategy will only affect itself. Green passenger transport companies will only implement green travel measures if these measures conform to the laws of the market economy—i.e., if the companies can benefit from them. This article concludes that the green travel subsidy strategy is suitable for the early intervention stage and provide corresponding policy recommendations. The research findings can provide a basis for the government to formulate implementation strategies for passenger transport environmental protection measures.]]></description>
      <pubDate>Wed, 15 Apr 2026 08:31:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655916</guid>
    </item>
    <item>
      <title>Analyzing the Nonlinear and Interaction Effects Mechanisms of Factors Influencing Intercity Travel Route Choice by Passenger Car Drivers: A Case Study from Guangxi, China</title>
      <link>https://trid.trb.org/View/2691017</link>
      <description><![CDATA[Although travel route choice analysis is abundantly conducted using statistical models, some shortcomings, such as easy neglect of nonlinear effects among factors, and subjective assumptions in modeling, are apparent. This study provides an interpretable framework based on machine learning models to better analyze the travel route decisions of intercity travelers. Four types of travel route choice behavior analysis models (i.e., extreme gradient boosting [XGBoost], Light gradient boosting machine, random forest, and the binary logit model) were conducted using travel survey data for passenger car drivers in Guangxi, China, in 2021. The model parameters showed that XGBoost achieved the highest prediction accuracy (89.8%). Based on objective data distribution, the Shapley additive explanation approach was used to explain the output of XGBoost. The results showed that vehicle types, passenger capacity, expected toll discounts, and travel frequency on freeways had nonlinear effects on travel route choice, while traditional statistical models could not identify the nonlinear effects because of the effect of data distribution. Travel route choice was affected by potential interaction effects (e.g., vehicle types and toll payers). There were differences in the contribution of the same factor (e.g., education level) to route choice for different vehicle groups. These findings help better understand the generative mechanisms of travel route choice from a more objective perspective and provide references for developing more effective strategies to alleviate intercity road congestion and improve road network capacity by guiding travelers’ route choices.]]></description>
      <pubDate>Fri, 10 Apr 2026 16:00:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691017</guid>
    </item>
    <item>
      <title>Unveiling pattern and structure of inter-urban mobility: Integrating flow space and geospatial information</title>
      <link>https://trid.trb.org/View/2655907</link>
      <description><![CDATA[With the growing prevalence of information technologies and spatial flows, network analyses have become one of the key approaches to studying interurban mobility. However, conventional models often overlook geographic contexts by simplifying flows into abstract nodes and edges. In this study, we leverage the 2018 Tencent mobile positioning data to construct an integrated “point–line–area” framework that can connect flow space with geographic space. A novel SCᵢ index is introduced to identify influential source-convergences and detect points with high-intensity radiation-like flow aggregation. Key flow corridors are extracted by using directional and distance similarity, and regional flow patterns are analyzed through nested mapping and trend surface techniques. Results not only reveal significant source-convergences in flow space, with parallel flow aggregation corridors dominated by east–west flows, but also measure the spatial evolution of flow intensity patterns across subregions. Findings highlight that, from the perspective of flow space, some planned urban agglomeration areas have yet to form multiple radiation centers, and that the key to balanced regional development lies in fostering diverse interregional connections, such as corridors.]]></description>
      <pubDate>Thu, 09 Apr 2026 10:08:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2655907</guid>
    </item>
    <item>
      <title>Spatiotemporal Patterns and Influencing Factors in Intercity Travel within Urban Agglomerations</title>
      <link>https://trid.trb.org/View/2664380</link>
      <description><![CDATA[The investigation of spatiotemporal characteristics and patterns in intercity travel within urban agglomerations constitutes a pivotal component of urban transportation planning. However, the vast spatial expanse of urban agglomerations and the high costs associated with traditional surveys pose challenges in gathering comprehensive data that reflect intercity travel dynamics accurately. This study harnesses mobile signaling data and applies an enhanced Nonnegative Matrix Factorization (NMF) technique to uncover spatiotemporal travel patterns within the Yangtze River Delta urban agglomeration. The analysis identifies three distinct spatiotemporal travel patterns: leisure and business dual-driven travel (LBT), outbound tourism and family visits (OTV), and return trips related to tourism and family visits (RTV). In addition, the Quadratic Assignment Procedure (QAP) model traditionally utilized in social network analysis is employed to examine the factors influencing these travel patterns. The findings indicate that macroeconomic factors, spatial proximity and travel convenience uniformly influence all of the identified patterns, whereas factors related to Work-life balance and tourism and leisure exhibit varying degrees of significance across the patterns. The results further demonstrate that the critical influencing factors are aligned closely with the spatiotemporal distribution characteristics of each pattern, corroborating the efficacy of the proposed methodology in mining and analyzing spatiotemporal travel patterns.]]></description>
      <pubDate>Tue, 31 Mar 2026 10:15:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2664380</guid>
    </item>
    <item>
      <title>Modeling the cancellation of inner-city leisure trips to different destinations in future pandemics: employing psychological factors based on previous personal experiences</title>
      <link>https://trid.trb.org/View/2643198</link>
      <description><![CDATA[As pandemics can be classified as crises, it is essential to develop predictions for future pandemic situations. Previous research focusing on the impact of pandemics on travel behavior was primarily conducted during crises. However, individuals may react differently to similar pandemic situations in the future based on their knowledge, experience and attitudes. Considering a hypothetical future pandemic, this paper investigates the factors that influence whether people would continue their inner-city leisure activities or cancel them. A stated preference survey, incorporating psychological and socioeconomic variables, was designed to examine individuals' travel behavior for various leisure destinations. To identify the impact of specific destinations on decision-making, a general model was first developed, followed by four binary logit models for indoor public, outdoor public and private leisure destinations. We found that psychological factors, especially personal concern about health risks, social responsibility and value-driven beliefs like altruism, play a major role in shaping people's choices. Those who strongly believed in protecting others or saw COVID-19 as a serious threat were much more likely to cancel their leisure trips. These findings may shed light on the existing literature and assist city managers in making better decisions regarding the operation of leisure destinations during future pandemics.]]></description>
      <pubDate>Wed, 25 Mar 2026 15:50:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643198</guid>
    </item>
    <item>
      <title>Optimization of Intercity Multimodal Network Considering Different Travel Behaviors Estimated via Non-negative Matrix Factorization</title>
      <link>https://trid.trb.org/View/2646028</link>
      <description><![CDATA[Efficient intercity travel networks are important for economic growth and environmental sustainability, yet traditional networks often overlook the influence of travel behaviors. Therefore, in this study, we address the knowledge gap by incorporating travel behaviors into intercity transportation networks in Japan using non-negative matrix factorization (NMF) on mobile-phone location data. The NMF analysis revealed three key travel-behavior patterns—Business, Personal reasons, and Sightseeing/Leisure, whose seasonal dynamics were examined. We modeled these variations to develop an optimized multimodal transportation network integrating rail and air services to minimize social costs. The findings show that incorporation of travel behaviors, i.e., the necessity of hybrid transportation networks, particularly for high travel volumes and significant travel-time differences, results in drastic changes in the optimal network shape. In addition, the relevance of single-modal networks under specific conditions is highlighted, demonstrating the potential of NMF for identifying travel behaviors and improving transportation network designs.]]></description>
      <pubDate>Fri, 13 Mar 2026 12:24:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646028</guid>
    </item>
    <item>
      <title>Planning of Energy Supply Facilities for Highway Networks: Methodology Research and Practical Applications</title>
      <link>https://trid.trb.org/View/2647804</link>
      <description><![CDATA[In recent years, facing the rapid growth of electric vehicles (EVs) and urgent intercity travel demand on the service area of highway network, we carry out the research on electric energy replenishment facility network planning, including: analysis of intercity EV travel decision-making behavior, sequential planning of charging facilities considering energy structure transformation, and synergistic planning of transportation and energy facilities to enhance green power benefits. Therefore, effective solutions can be gained to address the lack of coordination between traffic flow and energy supply in charging replenishment based on real-world conditions and to promote the low-carbon development of highway transportation.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2647804</guid>
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