Airport Ground Access Research Articles

Preferences and welfare impacts of new metro serving airport access

The construction of a new rail infrastructureto connectairportswith cities plays a vital role in enhancing the accessibility of airport ground access and mitigating negative externalities resulting fromautomobiles. To identify air travelers’ preferences for airport ground access by considering a new metro line in Taiwan, we develop nested logit models, which combine revealed and stated preference data. The results reveal significant effects of travel time, travel cost, and individual characteristics; the metro and taxis are highly substituted for airport access. Consumer surplus or accessibility is not equally distributed across air travelers. Travelers who are female, young adults, lower income, and without vehicles in the household obtain considerable consumer benefits from using the new metro. Policy incentives to time and cost have a small impact on the increase in metro share, but consumer surplus surges considerably.

Multi-criteria decision-making for the selection of best airport ground access mode with a new fuzzy rough-entropy based method

In order to cope with the inherent complexities and uncertainties of settings such as transportation problems, the adoption of proper decision procedures becomes a pivotal issue. Particularly, multi-criteria group decision-making (MCGDM) uses multiple evaluations of the options based on several criteria to select the optimal choice and/or rank the alternatives. In this paper we are interested in the Entropy-REGIME method for MCGDM and its ability to handle uncertainty in the presence of fuzzy rough numbers (that allow the practitioner to represent and process imprecise data). To this end we propose a hybrid framework of the fuzzy rough-entropy based REGIME method that involves two main components: fuzzy rough-entropy for the evaluation of the objective weights of the decision criteria, and fuzzy rough-REGIME to rank the alternatives based on the weighted criteria. Its motivation is a case study that concerns the selection of the best transport mode to access Istanbul newly constructed airport. We consider four alternatives for ground access options, namely, underground metro, bus rapid transit, light rail transit, and premium bus services. Our findings show that an underground metro system is the optimal mode, followed by light rail transit, bus rapid transit, and premium bus services. Additionally, to demonstrate the superiority and effectiveness of the proposed technique, comparisons are made with existing methods.

Analysis of Traffic Organisation in the Kiss-and-Fly Zone of Kraków Airport: Eye-Tracking Study

When choosing the way to come to airports, quite a large number of passengers prefer when they are dropped off/picked up at airports using kiss-and-fly (K&F) zones. Such a travel option is associated with a special traffic organisation on the airport ground access. As there are no common regulations or standards when creating such a complex infrastructure object, it could be a challenge for drivers when searching and moving through it. Therefore, the main aim of the presented study was to assess and verify the eye-tracking technique as an objective tool, which can allow one to identify and estimate confusion points met by road users when using such an object. The field tests with 23 drivers were conducted in the K&F zone of Kraków Airport, and the data analysis focused on the traffic organisation and road signage as its key and integral parts. The eye-tracking approach allowed us to clearly find confusing situations for drivers as well as explain their reasons confirming its suitability and usefulness for the declared aim. Also, the perception of standardised and unstandardised signage of the K&F zone as well as the influence of route familiarity for drivers were discussed.

Assessing airport ground access interventions: An integrated approach combining mode choice modeling and microscopic traffic simulation

Airport ground accessibility is an important and integral part of airport planning, which significantly impacts airport attractiveness and its environmental sustainability. In this paper, we propose the combined use of road micro-simulation with meso-scope discrete choice modeling to support the evaluation of airport access interventions. The proposed integrated framework allows us to appraise mode choice and infrastructural interventions simultaneously to accurately assess the performance of airport access road networks in accommodating larger traffic. We validate and demonstrate the benefits of the proposed approach by applying it to a real-world case study based on the Milan–Bergamo Airport (BGY), in which (i) we conduct an ex-post counterfactual analysis to assess the impact of the interventions undertaken to mitigate the large growth (54.6%) in the years 2013–2019, and (ii) evaluate future scenarios up to 2030 considering the additional expected growth and introduction of direct rail services. Results indicate that BGY’s ground access interventions have contributed to effectively accommodating traffic growth by significantly mitigating road congestion and associated pollutant emissions. Results also inform on the need and effectiveness of additional interventions to meet the substantial expected future growth.

Use mobile location data to infer airport catchment areas and calibrate Huff gravity model in the New York metropolitan area

Mobile location data have emerged as a pivotal asset for analyzing travelers' spatial behaviors and movement patterns. In the context of air travel, the data empower researchers to gain empirical insights into travelers' choices of airports. This study employs mobile location data to scrutinize the market shares and infer catchment areas of three primary hub airports within the New York Metropolitan Area. Our study, together with Teixeira and Derudder (2021), helps contribute to a better understanding of competitive airport dynamics in the New York Metropolitan Area. In addition, the mobile location data allow us to calibrate the two key components of the Huff Gravity Model, which is frequently used in existing studies focusing on airport competition and catchment areas in Multiple Airport Regions (MARs). Our investigation underscores that the application of the Huff Model should not follow a uniform approach across different scenarios. The dynamics of airport competition and ground access alternatives exhibit unique characteristics within each MAR. Furthermore, our study unveils inherent quality challenges associated with mobile location data. Future studies intending to incorporate mobile location data are advised to conduct preliminary assessments of data quality before embarking on empirical analyses.

The Impacts of Low-Carbon Incentives and Carbon-Reduction Awareness on Airport Ground Access Mode Choice under Travel Time Uncertainty: A Hybrid CPT-MNL Model

Developing strategies to incentivize travelers towards adopting sustainable mobility options is one of the effective approaches to mitigate carbon emissions. Using Xi’an Xianyang International Airport as a case study, this study aims to explore the effects of low-carbon incentives and carbon-reduction awareness on airport ground access mode choices. In addition, to account for the complex road environment, an innovative stated preference choice experiment was designed, integrating the factor of travel time uncertainty. Then, a hybrid cumulative prospect theory–Multinomial Logit (CPT-MNL) model was also developed. The estimated results revealed that travelers increasingly prioritize emissions reduction and consciously prefer sustainable mobility options to reach the airport. Furthermore, the potential of low-carbon incentives to encourage public transport usage over private vehicles has been highlighted. Notably, travel time uncertainty had a significant impact on the choice of private cars. When the travel time to the airport is uncertain, travelers exhibit a greater inclination towards selecting public transport. The findings of this study offer nuanced insights for transportation authorities, aiding them in fostering the adoption of sustainable mobility options and achieving carbon reduction objectives.

Investigating the recovery of For-Hire-Vehicle, Taxi, and AirTrain at two New York City airports during the COVID-19 pandemic

For operators of large-scale infrastructure systems such as airports, predicting landside access demand amid constant exogenous changes that modify travel volumes and preferences is immensely challenging. COVID-19 disrupted travel behavior and mode preferences, making it even more challenging for airport operators to plan infrastructure and design strategies to accommodate landside access. We use time series regression discontinuity to explore to what extent the volumes of airport ground access modes changed during the pandemic, how the recovery differed across modes, and how the pandemic changed the established relationship among access modes. We do so by examining the change in the three main airport access modes at two large New York City airports, John F. Kennedy International Airport and LaGuardia Airport (traditional taxis; for-hire ride-hailing services such as Uber; AirTrain, the public transit system, at JFK only). We find the mismatch between taxi pick-up and drop-off trips that predates the pandemic widened and persisted during the pandemic; the pandemic diminished taxis’ role and exacerbated the replacement of taxis by for-hire-vehicles. For-hire-vehicle trips recovered at both airports, possibly at the expense of taxis. AirTrain continued to function as an important and resilient airport access mode during the pandemic. Our research helps to inform the airport operators’ resource allocation and traffic management strategies while showcasing the usefulness of time series regression discontinuity in examining changes in travel behavior for future planning in the aftermath of a major shock.

Airport Ground Access Choice Between Transportation Network Companies and Parking: A Case Study of Hartsfield-Jackson Atlanta International Airport

Airport Ground Access Choice Between Transportation Network Companies and Parking: A Case Study of Hartsfield-Jackson Atlanta International Airport

The role of security in passengers' airport ground access choices: A statistical evaluation

The choice of how passenger access the airport by land involves several objective and subjective factors that can be exemplified, respectively, as the cost of access and the particular situations that the passenger has already experienced. However, the ways found in the literature do not include the “security” variable as a decisive part of this process of choice. Thus, through a survey of Declared Preference carried out at the International Airport of Guarulhos/São Paulo (SBGR), the variable “security” was incorporated based on a conjoint analysis, which contemplated attributes of greater consensus in the literature related to the choice of getting to the airport by ground. Based on the results of the statistical analysis, it is possible to affirm that security is as decisive a factor in choosing the kind of transportation as the time taken to arrive at the airport. Among these findings, it can be said that the concern with security is greater among lower-income passengers, but there is no evidence that men and women have different concerns about the subject.

Assessing Equitable Accessibility Based on Total Travel Cost and Multiple Options: Case Study of Airport Ground Access in Hong Kong

In recent decades, transit equity has become a recurrent topic within the domain of sustainable transportation, where accessibility is a crucial indicator. However, the measurement of accessibility and equity in existing studies is usually based on the route with the shortest travel time, whereas multiple travel routes and corresponding travel costs remain unexamined. Taking the ground access to Hong Kong International Airport (HKIA) as an example, this study aims to fill the previous research gaps by examining the equity of accessibility by public transport simultaneously considering different sets of route options and corresponding total travel costs. These routes have either the shortest travel time or the maximum time-saving benefit–monetary cost ratio. Results reveal spatial variation in the total travel cost, which reflects considerable horizontal inequity. The results, however, indicate that vertical equity exists because the total travel cost is positively correlated with median income level across different locations. In addition, the route that provides a reasonable benefit–cost ratio further improves the equity in accessibility to HKIA. The study illustrates the significance of simultaneous consideration of total travel costs and multiple routes in the assessment of accessibility equity. It also provides transferrable methods for evaluating transit equity.

The Carbon Footprint of Airport Ground Access as Part of an Outbound Holiday Trip

In this paper, greenhouse gas (GHG) emissions derived from airport surface access of outbound German tourists travelling to the Canary Islands have been estimated. It is argued that carbon footprint estimations in tourism must be improved to incorporate the transport to the airports within the country of origin. To do so, statistical data from the Tourism Expenditure Survey of the Canary Islands have been used. In particular, the postcodes of a large sample of German tourists visiting the archipelago from 2012 to 2014 are used to identify their residence and the distances travelled to their chosen airport. The findings of the paper contribute to the literature on tourism carbon footprints, including an estimate of the share of airport surface access emissions in a typical outbound sun and beach holiday trip. Airport ground access accounted for 8.17% of transport-related emissions. These results have implications for urban planners, transport firms, and tourism management.

Impact of Transportation Network Companies on Ground Access to Airports: A Case Study in Austin, Texas

This study proposes using intelligent transportation systems (ITS) and open-data sources to evaluate the impact of transportation network companies (TNCs) on ground access to airports. The unexpected interruption of the TNCs services in Austin, Texas, U.S., in 2016, is used as a natural experiment to provide a before-and-after analysis of the changes in the traffic conditions of the access area to the Austin-Bergstrom International Airport (ABIA). An analysis of variance (ANOVA) is implemented to determine whether the difference in speeds across periods is statistically significant, and the value of time for TNC-induced delay is estimated, using values of passengers’ willingness to pay for airport access travel time savings. Furthermore, a speed linear model is developed to assess the impact of TNC demand on ground access areas using trip information from an Austin-based TNC service. The main results suggest that airport ground access speeds were higher during the period that the TNCs were out of the city. The re-introduction of the services resulted in a speed reduction of 9% for the airport morning and 18% for the afternoon peak hours, translating to a total passenger cost of approximately $150+ (morning) and $400+ (afternoon) per hour. Furthermore, it was found that the number of TNC pick-up trips is a predictor of airport access speed and that the flight schedule can potentially be used to develop predictive speed models.

Investigation of Employee Related Airport Ground Access Strategies from a Post-COVID Perspective

Until recently, addressing the environmental externalities associated with the use of the private car and single occupancy vehicles has been the focus of the airport ground access policies worldwide. However, with the emerging unprecedented challenges of the COVID-19 pandemic, which have already changed the way we live, work, and travel, encouraging a change in commuter behavior has become even more important. This has necessitated that existing strategies be reconsidered in favor of adapting to a highly uncertain “COVID-19 world.” Historically, there has been a dearth of literature relating to airport employees’ ground access even though as a group employees represent an important segment of airport users with complex access requirements. This paper therefore focuses on airport employee related airport ground access strategies considering an emerging understanding of the future impacts of COVID-19 on global air travel. Pre-COVID strategies are investigated by conducting a documentary analysis of the most recent ground access strategies of 27 UK airports. The findings reveal that airport ground access strategies were mainly focused on setting targets and producing policy measures in favor of reducing car use and increasing the use of more sustainable transport modes including public transport, car sharing, and active travel (walking, cycling). However, measures encouraging public transport and car sharing will be more difficult to implement because of social distancing and fear of proximity to others. Instead, initiatives encouraging remote working, active travel, and improved staff awareness will be at the forefront of the future ground access strategy development.

Joint Modeling of Access Mode and Parking Choice of Air Travelers Using Revealed Preference Data

Airport ground access mode choice is distinct from everyday mode choice decisions, necessitating context-specific choice model estimation. Understanding airport ground access mode choice decisions is not only important for developing infrastructure planning strategies, but also for assessing the impacts of emerging modes on airport revenues, particularly from parking. However, parking choice is an often-overlooked dimension in airport ground access choice modeling. This paper addresses this gap through the development of a joint model of airport access mode and parking option choice using a passenger survey conducted at Dallas-Fort Worth (DFW) International Airport in 2015. Compared with a traditional conditional logit model that does not consider parking options available at DFW airport, the joint model of mode and parking decisions was found to generate more realistic values of travel time and was shown to have better predictive performance, both of which are critical for obtaining better airport parking revenue estimates and identifying traveler cohorts who may respond more strongly to potential policies targeting curb congestion and parking demand.

Modeling and Implications of Airport Ground Egress Mode Choice

Mode choice of airport ground access has been covered by several studies, but there is a lack of research in the case of airport ground egress; that is, mode choices of inbound passengers for ground trips from the airport to the city center. This study aimed to cover this gap by modeling the ground egress mode choice of passengers, employing mixed logit and comparing it with the multinomial logit model. The data for this research was collected at Istanbul’s Sabiha Gokcen International Airport (SAW) in 2015. Analyses included six modes, namely automobile, pick-up, public transit, taxi, shuttle and public transit (SP), and shuttle and taxi (ST). An important outcome was that a mixed logit model with error components outperformed the multinomial logit model. Results showed that significant variables affecting the ground egress mode choice included the income of the passenger, the cost of a ground trip from the airport, auto ownership status, number of luggage and trip purpose. Passengers are less constrained by ground travel time in their airport egress trips than in their airport access trips. By this, a significant finding was that prioritizing egress trip cost over travel time affected the mode choice.

Concept of Advanced Personal Rapid Transit at Airports

The increase in air transportation demand implies challenges on airport ground access. Using private transportation mode to reach the airport is a typical practice which results in the vast demand for parking facilities. These facilities are located farther from the terminal, increasing the access time. This research aimed to develop the concept of an advance airport Personal Rapid Transit (PRT) that connects parking facilities to the terminal as a shuttle service, and provides on-board integrated flight-related services, such as check-in and baggage handling. The system architecture and operational models were developed, thus all relevant components and functions were identified, especially focusing on information management tasks. A questionnaire survey was performed and conducted at Budapest Airport to reveal the user expectations towards an advanced PRT service at the airport. Moreover, a layout selection method was developed which was applied to Budapest Airport as a case study. The proposed PRT service provides a seamless transit by access to airport terminals from remote parking facilities conveniently and the time consumption of flight-related activities is significantly reduced too.

Analysis of airport ground access services by SP/RP model within the scope of Hasan Polatkan Airport master plan

Purpose - The airport master plan should include requirements and recommendations, demand forecasts, environmental analysis, layout plan, facility requirements, financial size, and location selection information. The biggest factor in choosing air transportation by passengers is that it is a fast and comfortable mode of transportation. Since the transportation time and ease of the airport is also a factor affecting this factor, its integration with airport access roads, intercity connecting roads and other modes of transportation is important for the passengers to choose air transportation. Therefore, the importance of airport access roads in master plan studies can be understood more clearly. Aim of the study is that analyzing to airport ground access services of Hasan Polatkan Airport within the scope of master plan. Methodology - In the first part of the research, the airport planning steps are examined in the literature. Airport ground access services data was collected with the secondary data. Revealed preferences surveys (RP) and stated preferences surveys (SP) were used to get he data of the passengers’ satisfaction. A statistical program used to analysis of survey. Total of 91 passengers were reached in 3 different flights in 2018 in the summer. The scale of the research was adapted from the Passenger Time Value, Benefit-Cost Analysis and Airport Capital Investment Decisions book Findings- Only 15.4 percent of the passengers use public transportation to access the airport. Conducted with the passengers at the Eskisehir Hasan Polatkan Airport Terminal Section, the passengers were generally satisfied with the transportation conditions to the airport. The primary mode of transportation preferred for RP in access to the airport is light rail systems. Conclusion- Survey form to evaluate the airport transportation services in terms of passengers was prepared and applied on outgoing incoming passengers. As a consequence of the analysis of the research, suggestions about Hasan Polatkan airport were completed.

Tri-reference-point hypothesis development for airport ground access behaviors

Studies have applied single-reference-point or safety margin hypotheses to examine how advanced traveler information affects travel behaviors. However, these theories may fail to fully capture the trade-offs among origin departure time, airport access time, and terminal processing time in terms of airport ground access behaviors. In this study, we developed a tri-reference-point hypothesis and assumed that the rate of change of utility may change at the air passenger’s preferred (PAT), earliest acceptable (EAT), and latest acceptable (LAT) airport arrival times. With an empirical data set collected from 304 passengers at Taipei Songshan Airport, the study examined the tri-reference-point hypothesis by analyzing airport ground access mode choice behaviors with a pooled framework that combined revealed and stated preferences. Moreover, the study developed four alternative specifications for schedule delay variables, assuming that air passengers used different reference points to determine relative gains and losses of the expected airport arrival time. The specifications included selecting both EAT and LAT as the zero-utility points (an indifference-band specification) and either one of PAT, EAT, and LAT as the single zero-utility point. Regardless of which specification was employed for schedule delay variables, the tri-reference-point hypothesis was generally supported. In particular, a significant difference of the rate of change of utility around PAT, EAT, and LAT was identified in the analysis results. When managing increasing road travel times and increasingly congested terminals, air passengers were more willing to retime their origin departure time to an earlier time than to switch their ground access mode. The implications of the analysis results for airport ground access management are discussed in the study.

Selecting an airport ground access mode using novel fuzzy LBWA-WASPAS-H decision making model

Airports are critical in ensuring a fast way of transporting people and goods. Choosing a reliable, fast and comfortable access mode to the airport is vital to ensure a seamless aviation system. The aim of this study is to select the best transport mode for Istanbul’s newly constructed Istanbul Airport. One of the largest airports in the world with 150,000 passenger capacity per year, Istanbul Airport is located in the northern part of Istanbul, outside the city. However, the access to the new airport resulted in many controversies about the selection of the best mode. Underground metro, bus rapid transit (BRT), light rail transit (LRT) and premium bus services are put forward as alternative ground access modes. These alternatives are evaluated based on 4 main decision criteria including financial aspects, operating features, project characteristics and environmental sustainability, which are broken down into 14 sub-criteria. In this paper, the importance weights of the criteria are determined by novel fuzzy Level Based Weight Assessment (LBWA) which is capable of modelling human thinking. Afterwards, the traditional Weighted Aggregated Sum Product Assessment (WASPAS) method is enhanced by the integration of the fuzzy Weighted Heronian Mean (WHM) and fuzzy Weighted Geometric Heronian Mean (WGHM) functions. A hybrid fuzzy multi-criteria decision making method based on LBWA-WASPAS-H model is used to solve this ground access mode selection problem. The results show that an underground metro is the most optimal mode, followed by LRT, BRT, and premium bus services.

Impacts of Automated Vehicles on Airport Landside Terminal Planning, Design, and Operations

Income from parking, rental car facilities, and other ground access modes for most commercial airports in the United States is a significant component in revenue. With the emergence of automated vehicles (AVs), or so-called “self-driving vehicles,” these fundamentals could change. Airport stakeholders need to understand the impacts of the emerging AVs to airport planning, design, and operation. If the impact hurts the operational resilience and financial sustainability of the airports, the stakeholders should come up with countermeasures to alleviate the impacts and to ensure the smooth operation and continuous growth of the airport. To serve these needs, this study quantifies the potential impacts of AV on airport parking and ground access by building a simulation platform and applying scenario analyses. Two airports are selected for case study: Tampa, FL (TPA) and San Francisco, CA (SFO). To fill in the gaps of historical data, statistical methods are used to generate inputs for study airports based on historical information of passenger demand, ground access mode split, and parking categories and durations. Furthermore, future scenarios are developed based on reasonable assumptions of the emergence of AVs. Outcomes of the case study show that the emergence of AVs will significantly affect airport operation if nothing as of now was changed. However, the impacts could be different for airports that are more auto-dependent versus those in metropolitan areas with various ground access options. Moreover, this study discusses possible strategies that can help airports generate revenue in the era of emerging AVs.