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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Enhancing gravity model predictions of Malaysian freight trade using machine learning integration</title>
      <link>https://trid.trb.org/View/2727337</link>
      <description><![CDATA[This paper proposes a hybrid approach combining the Gravity Model (GM) with machine learning (ML) techniques to improve predictions of Malaysia's international freight exports and imports. The study evaluates GM and three ML models; Random Forest (RF), Artificial Neural Network (ANN), and Support Vector Machine (SVM), with RF emerging as the most robust performer based on RMSE, MSE, and R-squared metrics. Four hybrid approaches were developed by combining GM and RF predictions with residual modeling. Results demonstrate that hybrid models consistently outperform standalone approaches. Notably, Hybrid Approach 2, which uses GM predictions adjusted by RF-modelled residuals with RF features, delivered superior performance, achieving RMSE values of 0.226 for exports and 0.162 for imports. This confirms the hybrid model's enhanced capability to capture complex trade patterns, offering a valuable forecasting tool for Malaysia's international freight transport planning.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727337</guid>
    </item>
    <item>
      <title>Assessing the impacts of metro loop lines on transit accessibility and equity</title>
      <link>https://trid.trb.org/View/2701795</link>
      <description><![CDATA[Metro loop lines improve travel efficiency by connecting radial lines and improving the transport environment, but their impacts on accessibility and equity remain underexplored. This study examines these impacts by comparing changes in transit accessibility before and after the opening of metro loop lines in Guangzhou. Transit accessibility to destinations is measured using travel data from the Amap API and a gravity-based accessibility model. On this basis, transport equity is assessed by the Gini coefficient, the Palma ratio, and the bivariate local indicator of spatial autocorrelation (BiLISA). The analysis is conducted under five travel time thresholds to consider the boundary effect of the Modifiable Temporal Unit Problem (MTUP). Results show that loop lines improve accessibility, especially in peripheral regions, benefiting vulnerable groups and reducing social-spatial inequities. Accessibility gains exhibit sensitivity to travel time threshold selection, peaking between 45 and 75 min. Overall, the loop line is shown to be an equitable transit investment from the perspective of accessibility-based distributive justice.]]></description>
      <pubDate>Fri, 07 Aug 2026 09:21:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701795</guid>
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    <item>
      <title>Price Elasticities in Aviation: Novel Estimates from Structural Gravity Modelling and Instrumental Variables Approach</title>
      <link>https://trid.trb.org/View/2665836</link>
      <description><![CDATA[This paper provides updated estimates of price elasticities of air passenger demand, using a comprehensive 10-year dataset from Sabre Market Intelligence (2010–2019). It expands the scope of previous research by incorporating global demand and price data at both the country and the city level and addressing key methodological issues, such as air fare endogeneity, using econometric techniques like Two-Stage Least Squares (2SLS) and fixed effects panel data analysis. The study reveals significant variation in price elasticity estimates, influenced by the choice of estimator, inclusion of fixed effects, and treatment of endogeneity of demand and ticket prices. While the global price elasticity is estimated at -0.87, travel originating from Europe exhibits a higher price sensitivity with an elasticity of -1.27. Moreover, medium-haul routes show a greater price elasticity than short-haul or long-haul routes. The findings offer valuable insights for policymakers to evaluate the impact of regulatory measures, for researchers to understand the cost sensitivity of demand for new technologies, and for airlines to optimize pricing strategies. Ultimately, this research contributes to a better understanding of the characteristics of air transport demand and its sensitivity.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:15:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2665836</guid>
    </item>
    <item>
      <title>GLUM Guidebook/Training Materials</title>
      <link>https://trid.trb.org/View/2582252</link>
      <description><![CDATA[Long-term traffic forecasts require long-term land use forecasts, which may be affected by mid- and near-term transportation infrastructure decisions, as well as traveler choices and associated changes in travel times and the relative access of competing locations. A long-standing methodology (Steve Putman’s ITLUP ®) for land use forecasting relies on a system of gravity-based equations, with proprietary code managed by consultants. To this end, the Gravity-based Land Use Model (G-LUM) has been coded and made accessible via freeware to facilitate greater use of land use models, under local control, with more transparency in the forecasting process.]]></description>
      <pubDate>Sat, 22 Nov 2025 17:17:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2582252</guid>
    </item>
    <item>
      <title>Commuting flow patterns across a triad of Chinese megacities: Evidence from Poisson gravity modeling using mobile device data</title>
      <link>https://trid.trb.org/View/2583123</link>
      <description><![CDATA[Understanding commuting flow patterns is crucial for effective urban planning in rapidly growing Chinese megacities. Utilizing mobile device data, point-of-interest (POI) data, road network data, house price data, and 1 × 1 km grids, this study systematically investigates the relationship between commuting flows and land use, transportation accessibility, and house price differences. A Poisson pseudo-maximum likelihood (PPML) gravity model is used to fix zero-value and overdispersion issues, and spatial heterogeneity is analyzed by origin- and destination-specific models. Three typical megacities in China, Beijing, Shanghai, and Shenzhen, are selected as case studies. The city-level regression results indicate that network distances, number of commercial POIs, house price differences, and distance to the city center are the main determinants of commuting flow distribution. The effects of industrial and public service land uses show significant differences across cities. Compared to Beijing and Shanghai, Shenzhen's industrial land is more mixed with residential and commercial land. Distance to the city center shows significant positive and negative effects at the origin and destination, respectively, revealing these megacities' morphological polycentricity and functional monocentricity. Specifically, Shenzhen's city center has a weaker influence, reflecting a more balanced functional structure. The results of local models highlight the spatial heterogeneity of the attractiveness of the city center and the distance decay effect. Residents between 10 and 30 km from the city center are most attracted by the center, and the distance decay effect is weaker in high-density areas. These findings emphasize the impact of industrial structure on land use patterns, the undeveloped functional polycentricity in Chinese megacities, and the limitations of high-density development in reducing commuting distances.]]></description>
      <pubDate>Wed, 22 Oct 2025 09:16:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2583123</guid>
    </item>
    <item>
      <title>Determinants of air cargo volumes within airport networks: Insights from an augmented gravity model with economic distance and geographic threshold effects</title>
      <link>https://trid.trb.org/View/2573095</link>
      <description><![CDATA[This study analyzed the determinants of air cargo volumes between airports using an augmented gravity model. Data from 115 airport pairs in China spanning 2009–2020 were utilized. The findings reveal that economic disparity significantly influences air cargo volumes, with greater economic differences between airports' host cities leading to reduced cargo flows. Geographic distance also plays a crucial role and exhibits a nonlinear effect. By extending the panel gravity model into a threshold regression model, this study finds that when the distance is less than 430 km, air cargo connectivity weakens as the distance increases. Beyond 430 km, however, geographic distance positively impacts air cargo volumes, indicating that air cargo frequency increases with longer distances. Population size in airport host cities affects cargo volumes, with departure city populations having a stronger influence. Additionally, airport-specific factors such as available tonnage, flight schedules, and regular shift load factors are significant determinants, with the regular shift load factor being particularly impactful. By incorporating time-varying economic distances and geographic threshold effects, this study improves upon the traditional gravity model, offering a more nuanced approach for analyzing airport cargo flows. The findings provide valuable insights for policymakers, enabling them to better understand the factors influencing air cargo volumes and implement effective strategies to foster sustainable growth in the air cargo industry.]]></description>
      <pubDate>Mon, 11 Aug 2025 09:12:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2573095</guid>
    </item>
    <item>
      <title>Unveiling the hidden effects of multilevel administrative boundaries on human mobility</title>
      <link>https://trid.trb.org/View/2567228</link>
      <description><![CDATA[Multilevel administrative boundaries create various forms of political and institutional influences on human mobility. However, quantitative evidence for these influences are absent. The authors examine this using mobile phone data of 107.48 billion trips across 2844 administrative units in China, a typical case experiencing significant transitions in administrative system. An extended gravity model, incorporating these boundaries, achieved 92.75 % precision and 0.23 improvement in adjusted R-squared over the classic model. Results show second-level (municipal) administrative boundaries impact mobility 3.86 times more than first-level (provincial) administrative boundaries on average. Municipal boundaries exert stronger effects in developed areas, while provincial boundaries show relatively balanced effects across regions. Municipal boundaries are linked to fiscal revenue decentralization, while provincial boundaries relate more to fiscal expenditure. Administrative boundaries influence social differentiation in mobility, with a stronger effect on females and younger populations. These findings contribute to the development of more accurate transportation models and reasonable mobility-management policies.]]></description>
      <pubDate>Thu, 10 Jul 2025 16:40:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2567228</guid>
    </item>
    <item>
      <title>Integrating gravity models and network analysis in logistical strategic planning: a case of the India Middle-East Europe Economic Corridor (IMEC)</title>
      <link>https://trid.trb.org/View/2519207</link>
      <description><![CDATA[The India Middle-East Europe Economic Corridor (IMEC) was introduced by US President Joe Biden in September 2023 in India, during the G-20 meeting. By creating commercial connections along the southern border of Eurasia, an expanding, multi-faceted IMEC trade corridor has the potential to alter trade patterns between the Middle East, Europe, and the Indian Ocean region. The project’s goal is to build a railway network that would travel via Saudi Arabia and Jordan to connect the United Arab Emirates with Israel and, from there, through a final sea-leg towards the Mediterranean EU ports, notably Piraeus, with continental Europe. Therefore, it is critical to assess trade potential among IMEC countries while paying attention to this corridor's function. Examining IMEC’s function in promoting international trade among initiative stakeholders while taking the geographic context into account, is the objective of this study. The analysis of IMEC members’ historical trends has been attempted as well. To calculate trade potential, a sophisticated gravity model is developed. Since this shows port connections to the hinterland, the integration of GIS-based network analysis; service area modelling; and road density modelling are also undertaken, in our objective to estimate trade potential. By integrating the gravity model (GM) with Geographic Information Systems (GIS), it becomes feasible to create visual depictions of the trade potential of IMEC to interested parties. We employ metrics like population, GDP, trade volume, road density per square kilometer, and service coverage as inputs to the GM, spanning from 2000 to 2021. Based on the panel data of a gravity model among IMEC members between 2000 to 2021, and using ordinary least squares (OLS) and generalized method of moments (GMM) modelling, our findings indicate that economic improvements in these countries, as well as efforts to decrease distances and improve connectivity among ports, will enhance interaction, as well as the processes of economic, social and political integration amongst them. The corridor also decreases (economic) distances and improves connectivity among ports, enhancing the overall globalization index of a country. Interestingly, we also find that having more than eight official languages has a negative effect on a country’s globalization index.]]></description>
      <pubDate>Tue, 29 Apr 2025 09:22:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2519207</guid>
    </item>
    <item>
      <title>Aggregate crash prediction model based on gravity model: Introducing crash risk distribution concept</title>
      <link>https://trid.trb.org/View/2481718</link>
      <description><![CDATA[Crash prediction models (CPMs) can be valuable for future transportation planning decisions. This study aims to develop CPMs based on the trip distribution step of the common four-step demand models. For this purpose, the Gravity Model is used. For model calibration, the frequency of severe crashes (including the total of fatal and injury crashes) between each origin-destination (OD) pair of traffic analysis zones (TAZs) in the city of Qom in Iran has been used as the dependent variable. The number of trip distributions by purpose, traffic characteristics on the links, and road network characteristics has been used as the explanatory variables. The model validation results show a significant relationship between the mentioned variables. Therefore, in addition to predicting the crash frequency according to trip number changes in the future, the developed model in this study determines the relationship between the crash frequency with the OD characteristics of the trips that lead to crashes. This makes it possible to evaluate the impact of different travel demand management scenarios on safety so that the crash risk (i.e., crash occurrence probability) of trips distributed between TAZs is identified and prioritized and can be planned to improve or reduced them.]]></description>
      <pubDate>Tue, 18 Feb 2025 10:56:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2481718</guid>
    </item>
    <item>
      <title>Accessibility Via Public Transport through Gravity Models Based on Open Data</title>
      <link>https://trid.trb.org/View/2487379</link>
      <description><![CDATA[Efficient urban facility access is crucial for enhancing residents' well-being and quality of life. This study examines public transport accessibility to essential facilities in Rome, such as high schools and hospitals, using gravity models based on open data sources, like OpenStreetMap and GTFS. Two versions of the gravity model are compared: an origin constrained and a doubly constrained. The latter can consider the capacity of facilities as a strict constraint, offering thus a more realistic assessment of accessibility. The findings highlight the correlation of public transport quality and urban accessibility, showing how variations in public transport supply affect the weighted average time to reach services like healthcare, education, and leisure. This approach reveals specific zones needing improvement and provides a valuable tool for predicting the impact of future changes in the transport network with respect to social equity. An online platform has been developed to allow a readily available application of this methodology to boost active citizenship and proactive decision making.]]></description>
      <pubDate>Mon, 27 Jan 2025 08:55:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2487379</guid>
    </item>
    <item>
      <title>Exploring Temporal Variations in Urban Attractiveness Using Location-Based Services Data Set</title>
      <link>https://trid.trb.org/View/2475445</link>
      <description><![CDATA[Recently, the construction of urban agglomerations has led to growing intercity connectivity. The criticality of intercity mobility system has become increasingly evident. Intercity mobility undergoes complex transformations over time, emphasizing the crucial importance of a comprehensive analysis of the attractiveness variation in intercity mobility. Previous studies have neglected to investigate the day-to-day variations in the urban attractiveness, especially during holidays. To fill the gap, the authors obtained the Location-based Service Data set across different periods. Then, the day-to-day urban attractiveness of Yangtze River Delta Urban Agglomeration in different periods was calculated using the inverse gravity model. Finally, general patterns of temporal variations in urban attractiveness within different periods were investigated. The authors' findings demonstrate that urban attractiveness follows individual variation trends across cities with diverse urban characteristics, spanning different time periods. These novel insights can provide beneficial support for accurate traffic forecasting and management within the realm of intercity transportation.]]></description>
      <pubDate>Tue, 24 Dec 2024 16:44:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2475445</guid>
    </item>
    <item>
      <title>Trip Distribution Characteristics of Railway Hubs Established from OD Data: A Case Study in Nanjing, China</title>
      <link>https://trid.trb.org/View/2475428</link>
      <description><![CDATA[As high-speed railways become more accessible in China, it is significant to clarify the travel characteristics of different station types to facilitate their planning and construction. Based on travel data from Baidu Map, this paper studies two railway hubs in Nanjing as examples. The trip distribution models were established using ordinary and spatial regression methods, respectively. Based on the principle of gravity model, the trip distribution models incorporating land use factors were established. The geographically weighted regression method was applied to form local models, which significantly improves the fitting effect in the scenarios of Nanjingnan Railway Station. The research shows that land use types, including residential, transportation, and green space, show a positive correlation with travel volumes in traffic zones, and different degrees of spatial heterogeneity were observed. The research completes the influencing factors of trip distribution of railway stations, reveals the differences related to station types, and improves the fitting effect generally.]]></description>
      <pubDate>Wed, 18 Dec 2024 12:01:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2475428</guid>
    </item>
    <item>
      <title>A New Method of High-Speed Railway Station Planning Based on Network Evolution</title>
      <link>https://trid.trb.org/View/1975906</link>
      <description><![CDATA[With the development of high-speed rail industry in various countries, it is very important to plan the network properly. The planning of the high-speed rail station affects the development of the high-speed rail network. This paper combines complex networks with high-speed rail stations as network nodes. Based on the gravity model, the authors established a network evolution rule to study the impact of new stations on overall network performance. At the end of the article, the authors use some Chinese high-speed rail stations as examples to verify the method. The authors hope to use this method to provide guidance for high-speed rail station planning.]]></description>
      <pubDate>Wed, 23 Oct 2024 09:00:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1975906</guid>
    </item>
    <item>
      <title>Evaluating Attractiveness of Newly Introduced Flights-Results of a Study for the Ostrava International Airport</title>
      <link>https://trid.trb.org/View/2384768</link>
      <description><![CDATA[The paper addresses the issue of evaluating the attractiveness of new airport connections, one of which is a global transfer hub and the other is a regional European international airport. The attractiveness of new connections expressed, for example, by predicting the demand for new flight routes has long been studied, mainly using gravity models. The aim of the presented paper is to check whether an approach based on gravity models could be replaced with other approaches, in this case by multi-criteria evaluation methods. Questions of substitution of approaches based on gravity models, compiled for demand prediction, are relevant in cases where there are not enough input data for existing gravity models. The absence of input data occurs especially in cases where either there is no historical data on the operation of flights, or historical data do not have current significance, e.g. the operation of the flight has been interrupted for a longer time. The results of a study carried out for Ostrava International Airport located in the Czech Republic, show that gravity models for which relevant data are not available can be fully replaced by multi-criteria evaluation methods.]]></description>
      <pubDate>Wed, 29 May 2024 09:35:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2384768</guid>
    </item>
    <item>
      <title>Towards Intercity Mobility System – Insights into the Spatial Interaction Gravity Model and Determination Approach</title>
      <link>https://trid.trb.org/View/2381904</link>
      <description><![CDATA[The current development of urban agglomeration greatly promotes the intercity connection and elevates the significance of intercity mobility system. However, intercity mobility often exhibits extreme spatiotemporal imbalances due to the diverse urban characteristics. This poses a huge challenge for traffic management and reveals the necessity on understanding the urban attractiveness for intercity mobility, which is represented as spatial interaction gravity in this study. While recent works have explored relevant aspects, they failed to provide insights into temporal variations in spatial interaction gravity or capture the determining factors from multiple perspectives. To fill this gap, this study proposed a two-phase framework to measure the urban spatial interaction gravity and developed determination approaches utilising the large-scale location-based services (LBS) dataset. Specifically, the inverse gravity model was adopted for the measure within multiple urban agglomerations and city sets during weekdays, weekends and holidays. Then, the authors developed the fitting equations of spatial interaction gravity by incorporating the correlated features associated with social, economic, network accessibility and land use. The findings present spatial interaction gravity across different periods and substantiate the distinct determination effects of features, with a high fitting accuracy. They provide promising supports for the intercity mobility prediction and pre-emptive traffic management.]]></description>
      <pubDate>Tue, 28 May 2024 09:17:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2381904</guid>
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