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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>Modal Preferences and Value of Travel Time for Autonomous Vehicles and Advanced Air Mobility: Gayrettepe–Istanbul Airport Access Case Study</title>
      <link>https://trid.trb.org/View/2784871</link>
      <description><![CDATA[Autonomous/shared autonomous vehicles (AVs/SAVs) and advanced air mobility are among emerging transport modes whose integration into existing systems require informed decisions on infrastructure, pricing, and demand management. However, uncertainties remain regarding modal preferences and the value of travel time (VTT), particularly due to limited empirical evidence across different geographic contexts. This study investigates modal preferences for emerging modes in comparison with traditional modes, focusing on socio-economic and alternative-specific attributes, and examines variations in VTT. In this context, a discrete choice experiment was conducted with 479 respondents in Istanbul. A D-efficient design was used to construct experimental setup, and a mixed logit model was employed for analysis. Findings indicate that younger and more educated individuals are associated with a higher likelihood of choosing alternatives other than PT, while car ownership increases the propensity to select car-based modes. Out of vehicle travel time (OVTT) emerges as the primary determinant for air taxi (AT), whereas no statistically significant evidence was found for an OVTT effect on SAVs within this specific sample. Multi-tasking supportive design has a positive influence on AV choice. However, the influence of such design features on SAV and AT choices was not found to be statistically significant in this study. For public transport, seating availability remains a critical factor. Contrary to conventional expectations, findings suggest that AVs are associated with higher VTT than private cars. SAVs exhibit the lowest VTT among all modes, while AT reflects a high-premium segment. The findings provide insights into individuals’ preferences and VTT within a generic airport-access context.]]></description>
      <pubDate>Tue, 06 Oct 2026 10:14:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2784871</guid>
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    <item>
      <title>Investigating the perceived quality of airport accessibility to define regional development strategies</title>
      <link>https://trid.trb.org/View/2697203</link>
      <description><![CDATA[The development of an area can be affected by the success of the air transport system serving it. A fundamental aspect characterizing an airport is its accessibility, which today assumes a comprehensive concept, involving several aspects relating to how easily and efficiently people can get to and from the airport, but also on the ease of movement and service inside the airport, for all travellers, including those with disabilities. The aim of this paper is to verify which dimensions of external and internal accessibility are the strongest predictors of overall perceived accessibility quality, and if the predictive strengths of these factors vary across different passenger demographics (e.g., age, travel purpose). The work is supported by a study case focused on the Lamezia Terme airport, placed in Calabria, a region of the southern Italy. The collected data refer to cross-sectional surveys addressed to the passengers of the analysed airport in 2022 and 2023. A Cumulative Link Mixed Model (CLMM), incorporating random effects, has been calibrated to identify the factors most influencing the quality of airport accessibility, and some other models have been calibrated relating to different groups of passengers to verify the variability of perceptions. From the models, the main predictors of perceived overall accessibility quality refer to the internal accessibility aspects, as well as the level of perceived accessibility quality increases for the air passengers using car parking and decreases for the passengers using the website. Finally, passengers’ perceptions vary more as a function of carrier type and travel purpose.]]></description>
      <pubDate>Tue, 18 Aug 2026 14:12:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2697203</guid>
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    <item>
      <title>Airport accessibility assessment and shuttle bus scheduling across socioeconomic groups</title>
      <link>https://trid.trb.org/View/2672566</link>
      <description><![CDATA[Airport accessibility is a critical factor influencing air travel behavior, particularly for low-income travelers who face both economic and transit-related constraints. This study proposes the Fairness Airport Accessibility Metric (FAAM), a novel measure that captures disparities in accessibility across income groups by incorporating variations in travel options and behavioral responses. Building on this metric, we develop a dual-perspective, two-stage Airport Bus Scheduling and Allocation Model that reflects the differing priorities of public stakeholders. The government-led model first maximizes accessibility to ensure fair transit access across income groups, then minimizes operational costs under fairness constraints. The operator-led model, in contrast, begins by minimizing costs while maintaining baseline accessibility, and subsequently improves accessibility within those budgetary limits, capturing the trade-off between fairness and efficiency from both policy and operational standpoints. To validate the framework, we conduct a case study in Hong Kong, using actual flight schedules from Hong Kong International Airport (HKIA) combined with a synthetically constructed public transit network. The case study confirms significant spatial and income-based disparities in current airport accessibility and demonstrates the necessity of differentiated planning for diverse socioeconomic groups. Numerical experiments reveal that over-prioritizing low-income users can lead to underutilized system capacity, while favoring high-income users may improve overall efficiency but widen accessibility gaps. A balanced, fairness-driven weighting scheme provides inclusive service delivery without compromising operational feasibility. The findings highlight the importance of integrating income-responsive transit planning, fairness-aware scheduling algorithms, and targeted fare policies. Together, these strategies provide a scalable and adaptable framework for designing airport ground access systems that are both socially inclusive and operationally sustainable.]]></description>
      <pubDate>Mon, 01 Jun 2026 09:02:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672566</guid>
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    <item>
      <title>Accessing the airport by car or train in the case of a weekend trip using a random forest modeling approach: an analysis of respondents from Serbia</title>
      <link>https://trid.trb.org/View/2682112</link>
      <description><![CDATA[Airport access represents a significant segment оf overall travel, affecting passenger satisfaction and the efficiency оf transport systems. Different factors are valued differently by specific segments of passengers. This paper focuses on the hypothetical scenario of choosing a car or train to access the airport in the case of a weekend trip, with the aim to identify the most influential factors. The data were collected through the online survey conducted on the European level; however, this paper analyses only Serbian respondents. Results indicate that key factors influencing mode choice are cost, reliability, and demographic characteristics, with the random forest model demonstrating the best performance.]]></description>
      <pubDate>Mon, 27 Apr 2026 15:01:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2682112</guid>
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    <item>
      <title>Social-psychological determinants and nonlinear thresholds: behavioral insights into urban air mobility adoption as an airport shuttle</title>
      <link>https://trid.trb.org/View/2654642</link>
      <description><![CDATA[Urban Air Mobility (UAM) is an emerging mobility service increasingly proposed by cities worldwide. Among its various applications, UAM as an airport shuttle offers particularly strong early-stage commercial potential. However, understanding of the key factors influencing the adoption of UAM as an airport shuttle service remains limited, particularly regarding the role of social-psychological factors and their tolerance thresholds from a nonlinear perspective, where critical points in factors such as time or cost may shift the decision from declination to acceptance. Using a stated-preference survey of 1250 respondents from South Korea, this study identifies the primary determinants of UAM adoption and examines their decision thresholds using a newly proposed hybrid approach that combines automated machine learning (AutoML) and statistical models in a complementary manner. The results show thatt: (1) Previously overlooked social psychological factors, such as individuals seeking time savings, environmental benefits, and openness to new technologies, play adominant role, accounting for 55.4 % of explanatory power in predicting adoption decisions. (2) Threshold effects emerge in airport trip chains, with first-mile and in-vehicle durations under 15 min or over one hour marking critical adoption points; and (3) UAM holds strong substitute potential for car use for long-distance airport access. These findings provide actionable insights for policymakers and service providers aiming to promote UAM adoption, emphasizing the need to align service design and marketing strategies with users’ psychological motivations and to improve access environments for UAM connectivity within urban areas.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2654642</guid>
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    <item>
      <title>A support to vertiport micro-location selection at airport for urban air mobility airport shuttle service</title>
      <link>https://trid.trb.org/View/2652313</link>
      <description><![CDATA[Urban Air Mobility (UAM) services employing electric Vertical Take Off and Landing vehicles (eVTOL) will likely start in the next few years, and numerous research efforts are directed toward creating the necessary conditions for their successful implementation. Although vertiport location and vertiport capacity are recognized as key factors influencing UAM service performance, a notable research gap still remains in both areas. The vertiport location problem is addressed in the literature predominantly from the demand perspective, focusing on approximate macro-locations, e.g. centroids of the postal codes. Very limited research has addressed the micro-location level - determining the exact locations where vertiports should be built - which requires integrating other factors beyond demand. We aim to contribute to vertiport micro-location decisions by focusing on the hub nodes of the UAM airport shuttle network - vertiports at airports. Taking the airport operator’s perspective, who will be responsible for planning and investing in such vertiports, we propose a framework for vertiport site selection that includes: selecting candidate sites, identifying relevant criteria, evaluating candidates against each criterion, and ranking them using a selected multi-criteria decision-making method. The study also contributes to capacity and cost estimation by introducing an online vertiport sizing and capacity tool that proposes the most favorable vertiport configuration(s) for any given area. The proposed framework is demonstrated through a case study of Madrid Airport. Beyond delivering a final ranking of ten candidate sites, a transparent evaluation process enables airport operators to understand the capacity-area trade-off, capacity capping in a single layout, and capacity increase by combining two layouts, the impact of vertiport type on cost, or landside/airside position on vertiport-to-terminal accessibility, as well as limitations with the current regulatory framework.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652313</guid>
    </item>
    <item>
      <title>Examining airport intermodal access mode choice behaviour using interpretable machine learning</title>
      <link>https://trid.trb.org/View/2659514</link>
      <description><![CDATA[Understanding the ground access travel behaviour of airport users is essential for improving airport services. While previous studies largely focus on unimodal travel, limited attention has been paid to door-to-airport intermodal access. This study examines ground intermodal access mode choice behaviour, using Beijing Daxing International Airport as a case study. We apply Extreme Gradient Boosting (XGBoost) to model mode choice behaviour, and utilise interpretable machine learning techniques including SHapley Additive exPlanation (SHAP) values and Accumulated Local Effects (ALE) plots to capture nonlinear behavioural patterns. Findings reveal that intermodal choices are strongly shaped by traveller characteristics and access/feeder travel time thresholds. The metro-private vehicle intermodal is attractive when metro travel time is 43–62 or 75–105 min, and feeder time exceeds 7 min. The airport coach-private vehicle intermodal is appealing when the feeder time is under 16 min and the coach line-haul time exceeds 79 min. Although the effect is modest, the high-speed rail–private vehicle intermodal is facilitated by a feeder time of 14–33 min. Key policy implications include time- and threshold-specific strategies, with integrated bundles and real-time coordination of feeder and line-haul services. The study advances understanding of threshold-sensitive intermodal decisions and provides insights for developing sustainable and traveller-oriented airport ground transport services.]]></description>
      <pubDate>Wed, 25 Feb 2026 09:10:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659514</guid>
    </item>
    <item>
      <title>Public Acceptance of Electric Air Taxis for Airport Travel: An Extended Technology Acceptance Model with Theory of Planned Behavior and Diffusion of Innovation Constructs</title>
      <link>https://trid.trb.org/View/2640244</link>
      <description><![CDATA[Electric Air Taxis (EATs) represent a transformative innovation capable of redefining urban and regional mobility. Yet, technological advancement alone cannot guarantee feasibility; public perception and acceptance are equally critical. To understand these factors, this study extends the Technology Acceptance Model (TAM) with constructs from the Theory of Planned Behavior (TPB) and characteristics of innovation from Diffusion of Innovation (DOI) theory. Based on the response from 910 long-distance airport travelers in United States, we tested and refined a hypothesized structural model. Findings reveal that perceived ease of use and perceived usefulness significantly influenced attitudes toward EAT, which (along with social influence) shaped the intention to adopt. Compatibility and observability emerged as significant predictors of usage intention and influenced perceptions of social influence, behavioral control, usefulness, ease of use, and attitude. Trialability before adoption was found to increase social influence, perceived usefulness, and behavioral control, while perceived complexity negatively impacted ease of use. Furthermore, younger individuals, frequent air travelers, and those who typically use TNCs for airport trips exhibited higher adoption intentions. In contrast, older adults, women, low-income individuals, graduate degree holders, households with more private vehicles, and public transit users demonstrated lower intentions to adopt EATs. Business travelers, on the other hand, reported higher perceived ease of use for airport travel. The study concludes with implications for airlines, airport operators, EAT providers, and policymakers to design interventions that could enhance the public acceptance of EATs for airport travel.]]></description>
      <pubDate>Tue, 17 Feb 2026 13:12:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640244</guid>
    </item>
    <item>
      <title>Airports and Bicycles: what are the obstacles and incentives for operators to improve bicycle access?</title>
      <link>https://trid.trb.org/View/2628399</link>
      <description><![CDATA[In this paper we use a case study approach to examine how airport operators are addressing bicycle access to their properties and the motivations and obstacles they face, in light of new policies to integrate bicycles, along with transit and walking, into transportation planning, design and construction, and to increase bicycles’ role in the transportation system. Eight influential elements emerged from our review of policy documents and research literature. We used them to guide interviews with key informants. The eight elements are: governance structure, location, access roads, self-perceived environmental stewardship, spending restrictions on non-aviation transportation improvements, proximity to transit, policies and mandates to reduce environmental impacts and land use constraints. We report on seven cases, selected on the basis of inclusion in studies on key aspects of airport ground access and, for one, identification as exemplary. They are: Oakland International Airport, San Francisco International Airport, Los Angeles International Airport, Seattle-Tacoma International Airport, Boston Logan International Airport, Minneapolis-St. Paul International Airport, and Portland International Airport, an exemplar recommended by several key informants. We limit our discussion to employee bicycle access because that has been the focus of airport operators that have made these investments and programs to reduce single-occupancy vehicle travel at airports. In aggregating the interviews, we identified replicable approaches to improving bicycle access. We also identified examples of innovative funding for multi-modal access using revenues generated by airport Passenger Facilities Charges. Finally, we identified areas for additional research: airport employee commute needs, ground access mode choice and operator costs and benefits of bicycle access investments.]]></description>
      <pubDate>Tue, 10 Feb 2026 11:45:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/2628399</guid>
    </item>
    <item>
      <title>Incorporating built environment features in Air Passenger Demand forecasting: A spatial econometric approach for enhancing transport policy and planning</title>
      <link>https://trid.trb.org/View/2653087</link>
      <description><![CDATA[This study explores the determinants of Air Passenger Demand (APD) in India, with a special focus on the role of built environment features alongside geoeconomic and service-related variables. For spatially distributed data of APD, the study attempts to incorporate the spatial interaction effects in the APD model development using spatial econometric techniques with the Bayesian Markov Chain Monte Carlo approach. First, the spatial patterns and intensities of APD are visualized using a desire line diagram, and the cities are classified as low, medium and high to understand the rationale behind APD. Then, Moran's I statistics is used to confirm the presence of spatial autocorrelation of determinants with clustering patterns, and significant variables are used as spatial indicators in the development of the APD model. Also, Local Indicator of Spatial Autocorrelation (LISA) analysis is utilised to understand the dynamic localised spatial information. APD models are developed, and how individual, interaction and combined effects influence APD are explained. The Spatial Durbin Model (SDM) outperformed with a 0.622 posterior model probability for combined interaction effects (geoeconomic, service-related and built environment). The model's significant spatial autoregressive coefficient (α = 0.358) confirms strong spatial interdependence, and the study uses impact decomposition to separate the determinants' direct (own-city) and indirect (spillover) effects. Strategic policies based on this decomposition are proposed to capitalize on these study insights and drive sustainable APD growth in the aviation sector.]]></description>
      <pubDate>Mon, 02 Feb 2026 09:32:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2653087</guid>
    </item>
    <item>
      <title>Towards simulation-based assessment of CCAM Airport Access Services</title>
      <link>https://trid.trb.org/View/2572583</link>
      <description><![CDATA[Self-driving cars and their deployment as a transport service have been studied extensively in the Cooperative, Connected, and Automated Mobility (CCAM) concept. Increasingly, more specific use cases and deployment scenarios are studied in the literature. One of those concepts are CCAM Airport Access Services (CCAMAAS) that may facilitate and robustify first and last mile access to airports by the use of automated shuttles. Our goal is to gain insights into the operational benefits and challenges of such services, as well as on their economic and ecological impact. The paper presents a first step towards a novel simulation-based assessment framework for such services, by introducing a first use case example of a comparative analysis between classic taxi services and CCAMAAS for the Paris CDG and ORY airports.]]></description>
      <pubDate>Wed, 31 Dec 2025 10:55:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572583</guid>
    </item>
    <item>
      <title>Examining the introduction of transportation network companies (TNCs) and ridesharing services for airport ground access in Australia</title>
      <link>https://trid.trb.org/View/2588384</link>
      <description><![CDATA[Ground access mode choice directly impacts an airport's commercial income generation, imposes a range of environmental externalities and requires often-considerable capital investment and infrastructure development. Historically, these revenue planning, environmental management and capital investment decisions were predicated on the knowledge that airport ground access occurred via private vehicles or by conventional public transport modes. However, the introduction of new forms of ride-hailing and ridesharing mobility services by Transportation Network Companies (TNCs) is disrupting the status quo and posing new revenue and infrastructure planning challenges for airports. Australia is one country experiencing this new business model. The aim of this paper is to examine the situation in Australia and explore the extent to which major passenger airports in the country are adapting to the advent of TNCs and ridesharing services. The situation at the 10 busiest passenger airports is examined. The findings show that while these airports still routinely plan for conventional forms of ground access, TNC's represent a trend breaker which demands new ground access management strategies. Recommendations to help airport management respond to the introduction of widespread ridesharing and the arrival of TNCs in terms of landside asset configuration and the potential for regulatory and financial strategies are proposed.]]></description>
      <pubDate>Wed, 31 Dec 2025 10:55:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2588384</guid>
    </item>
    <item>
      <title>Modelling future of airport accessibility: synthetic population and discrete choice model approach to UAM and CCAM demand at Brussels airport</title>
      <link>https://trid.trb.org/View/2622062</link>
      <description><![CDATA[The emergence of Urban Air Mobility (UAM) and Connected, Cooperative and Automated Mobility (CCAM) offers transformative potential for airport accessibility, promising faster and more personalised connections to major air hubs. However, accurately forecasting the demand for these future transport modes remains a key challenge due to their limited real-world presence and reliance on speculative user preferences. This paper presents a robust and flexible methodology for assessing the future modal split of airport access, integrating both current and emerging mobility options within a discrete choice modelling (DCM) framework. Using a nested logit model calibrated on survey data from over 29,000 Belgian passengers at Brussels Airport, we developed a general-coefficient-based utility specification that enables the integration of hypothetical modes such as UAM and CCAM. This model was then applied to a synthetic population of airport passengers generated via iterative proportional fitting and spatial enrichment. By incorporating realistic operational assumptions for UAM and CCAM, we estimated demand under future scenarios. The results indicate that UAM and CCAM could capture 4.7% and 6.8% of airport access trips respectively, with modal shifts primarily originating from taxi and private car users. This demand modelling framework is assumption-agnostic and adaptable, providing a versatile tool for policy analysis and infrastructure planning as these technologies approach deployment. Future applications will benefit from updated data as these services are piloted, supporting more precise and policy-relevant demand estimations.]]></description>
      <pubDate>Wed, 10 Dec 2025 08:24:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2622062</guid>
    </item>
    <item>
      <title>Access, land-use policy, agglomeration and spatial dependence in airport-area firm location: evidence from Shanghai Hongqiao</title>
      <link>https://trid.trb.org/View/2622246</link>
      <description><![CDATA[We examine how transport accessibility, land-use policy and spatial dependence shape the location of airport-related enterprises in Shanghai's Changning District. The analysis combines a firm-level multinomial logistic regression of location choice among the airport region, the central activity zone and the left areas with a grid-level negative binomial model that incorporates Moran eigenvector spatial filtering. Explanatory factors include travel times to the airport, to the central activity zone and within the district; land-use capacities and cluster designations; and agglomeration measured by lagged incumbency in the same and other industries. Results show the central activity zone remains the default attractor, but firms in science, software and technical services, especially domestic firms with regional travel needs, are more likely to choose the airport region when hub connectivity dominates central-city proximity. At the micro scale, the spatial-filtering model reveals corridor-linked clusters: business and software incumbency produce asymmetric positive spillovers that raise nearby firm counts along the airport–central belt, while land-use levers amplify these patterns. Policy should position airport economic zones where access to both the hub and the urban core can be balanced, upgrade corridor and circulator links to reduce travel-time frictions, and deploy one-stop cluster services to convert incumbency spillovers into new investment. The two-scale design clarifies “which broad area” versus “where within an area,” providing a decision-oriented basis for implementation.]]></description>
      <pubDate>Tue, 02 Dec 2025 09:53:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2622246</guid>
    </item>
    <item>
      <title>Legal Aspects of Airport Programs. Topic 18-01. Legal Responsibilities Arising Out of the Americans with Disabilities Act and Air Carrier Access Act</title>
      <link>https://trid.trb.org/View/2625813</link>
      <description><![CDATA[The Americans with Disabilities Act (ADA) and the Air Carrier Access Act (ACAA) ensure the rights and accommodations of individuals with disabilities in the United States. The ADA provides a comprehensive national mandate for the elimination of discrimination against individuals with disabilities, including in employment, public accommodations, and transportation. The ACAA addresses the rights of passengers with disabilities in air travel and requires airlines to accommodate the needs of these individuals.    

Airlines and airports play critical roles in implementing these laws. Airlines are responsible for ensuring that their services, from booking to boarding, are accessible, while airports must provide accessible facilities. The Federal Aviation Administration (FAA) and the U.S. Department of Transportation (DOT) also have regulatory authority over air travel, including consumer protections, safety, and operational standards. While FAA's primary focus is on safety and efficiency of the national airspace system, it plays a supporting role in ensuring compliance with accessibility standards through various policies and guidance. It includes collaboration with the DOT, the U.S. Department of Justice (DOJ), and other agencies to ensure that regulations and guidance related to disability accommodations are upheld. However, the intersection of the ADA and ACAA can create challenges, as the ADA covers public spaces such as airport terminals, and the ACAA governs the treatment of passengers by airlines within the airport terminal.

OBJECTIVE: The objective of this research is to examine the legal obligations for airports and airlines arising out of the ADA and the ACAA, including accommodations for visible and invisible physical and mental impairments that substantially limit one or more major life activities.]]></description>
      <pubDate>Thu, 20 Nov 2025 16:04:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625813</guid>
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