Ground Access Mode Choice Research Articles

Unraveling passengers’ preferences: investigating airport access mode choice in Tehran, Iran

Airports are imperative elements in fueling the economic growth of a country by reducing the distances between origins and destinations for the movement of both passengers and goods. Managing ground access modes of travel has become essential as the majority of trips are made by private cars, leading to increased environmental issues and congestion. To alleviate these problems, it is vital to identify the factors that shape air passengers' choice of ground access mode. In this work, we utilized inclusive Revealed Preference data (RP) collected through face-to-face interviews and applied a Multinomial Logit (MNL) model to study passengers' ground access mode choice behavior at Mehrabad International Airport, the busiest airport in Iran. The results showed that different factors such as socioeconomic status, travel characteristics, and distance to the airport affect the mode choice behavior of passengers in reaching the airport.

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.

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.

Modelling of Ground Access Mode Choice: Empirical Evidence from Mehrabad International Airport, Tehran, Iran

Abstract The aim of this study is to investigate air travellers’ behaviour with regard to choices for ground access to this airport. Questionnaire data were collected from 684 respondents. Multinomial logit modelling was employed for this purpose. These findings indicate that in families with at least one car of their own, the tendency for using bus and carpooling was decreased. In addition, it was found that those in the 36 - 40 age group were more inclined to take the taxi. Finally, the results of this study suggest that with the growing price of the private car, the tendency to use it was diminished. Therefore, if transportation authorities seek to reduce the use of personal cars, it is possible to make the use of private cars expensive with increasing the parking cost in the airport. This may lead to the reduction of using private cars in land access to Mehrabad airport.

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.

MODELLING TRAVELLER’S GROUND ACCESS MODE CHOICE OF DUBAI INTERNATIONAL AIRPORT, UNITED ARAB EMIRATES

With increased demand for air travel, airports have become economic engines of the regional development that connect aviation systems with other modes of transportation facilitating the movement of people and cargo. Originating air passengers account for the majority of passenger trips to and from an airport and have different ground access needs. Since the air transportation is interrelated to ground transportation, studying ground access mode choice of airport users is a crucial part of airport management and system planning. The purpose of this study is to identify Dubai International Airport (DXB) ground access mode characteristics and users located in the United Arab Emirates (UAE), which has not been studied previously. Although there are many different modes of transportation serving the airport, yet personal vehicles are the main mode used to arrive to the airport. Binary logistic regression models are developed to evaluate access mode choice for originating air travelers focusing on the mix between private vehicle and public transportation system (taxi, limousine, bus network, and Dubai metro) using data collected specifically for this study. A total of 1012 air travelers were interviewed and completed the questionnaire in December 2014. Models result showed that access mode choice is significantly affected by different socio-economic characteristics of travelers including income, nationality, household size, vehicle ownership; and different trip characteristics that include number of travelers and how often air travelers use public ransportation in their community.

Modeling ground access mode choice behavior for Hamad International Airport in the 2022 FIFA World Cup city, Doha, Qatar

The Hamad International Airport (HIA) in Doha, Qatar is the only international airport operating in the country. The airport was officially opened in 2014 to function as the engine of the country's economic growth. Due to the anticipated high passenger demand of this airport, especially to account for the 2022 FIFA World Cup and in support of Qatar National Vision (2030), it is important to analyze, model, and evaluate the current and future airport ground access and traveler's modal choice. As such, the aim of this study is to analyze the current HIA ground access mode choice characteristics and users, examine the importance of introducing the Doha Metro to airport mode choice, and identify the preference of air travelers for this new mode. A revealed- and stated preference face-to face interview survey was conducted at the airport to collect data related to trip and user characteristics. Quantitative and qualitative methods were used to analyze the data. Binary logit mode was used to the current access mode choice, and a multinomial logit model was used to model the future access mode choice after introducing the Doha Metro. The models results showed that current and future access mode choice is significantly affected by the trip and socioeconomic characteristics of the HIA users.

Understanding Issues in Airport Ground Access Modeling: Lessons from a Revealed Preference Study of New York Metropolitan Area Airports

Airport ground access mode choice models can provide a great deal of utility for airport facility managers tasked with landside access planning. However, the absence of definitive standards to guide the development of these airport planning tools often results in wide variations in methodological approaches that in turn generate counterintuitive mode choice model parameters and that often leads to improper understanding of the air passenger ground access trip. A new regional airport ground access model was developed in support of the New York City Department of Transportation’s LaGuardia Airport Access Alternatives Analysis Study. The air passenger model developed for the study included a set of market-segmented ground access mode choice models, developed by using revealed preference data from a 2005 survey commissioned by FAA. The model estimation process tested a number of analytical strategies to address some of the challenges typically encountered with revealed preference data and, in the process, uncovered some findings that should both aid future airport ground access mode choice modeling efforts and further illuminate the modeling community’s understanding of the value of time, particularly as it interacts with household income levels and various dimensions of business travel.

Mode choice behavior modeling of ground access to airports: A case study in Istanbul, Turkey

The increase in air transportation mode share, thereby the passenger traffic at airports has made the ground access to the airports more important in recent years. The aim of this study is to analyze the ground access mode choice to airports by using Multinomial Logit (MNL). In particular, our focus is on how transit areas of influence affect the mode choice for travelling to airports. Atatürk International Airport (IST) in Istanbul, Turkey was selected for the analyses and the investigated modes to access IST were automobile, drop-off, public transit, and taxi. The results showed that significant factors and variables included the trip distance to access IST, type of destination, trip cost to IST, automobile ownership status, employment status, travelling group size, location of the trip origin with respect to public transit influence, and time difference between the flight time and departure time to IST. It is also concluded that if the trip origin to IST was inside the influence areas of public transit, then public transit would be more likely to be chosen over other modes for accessing IST.

Airport ground access and private car use: a segmentation analysis

The increasing scale of, and demand for, civil air transport world-wide has resulted in a greater volume of people travelling to and from airports. The vast majority of these journeys are made by private cars, which has led to traffic congestion and raised levels of air pollution in and around airports. Subsequently, airports are re-evaluating their approach to ground access mode choice and considering how to reduce the reliance on private cars. Based on a survey of passengers at Manchester Airport in the UK, attitude statements pertaining to psychological constructs from the Theory of Planned Behaviour and the Norm-Activation Theory, combined with key factors relating to the passenger’s trip, are used to identify eight behaviourally distinct groups of passengers with varying potential to reduce their private car use. Two of these groups, described as the Conflicted Greens and the Pessimistic Lift Seekers, are identified as having the greatest potential to reduce private car use to airports. Analysis reveals the need for decision makers to address the existing attitude–behaviour ‘gap’ that can prevent positive environmental attitudes being translated into the use of more sustainable modes, as well as tackling the perceived difficulty some passengers associate with using these modes.

Forecast of Airport Ground Access Mode Choice with the Incremental Logit Model

As factors affecting airport passengers' and other travelers' transportation choices constantly change, the probability of choosing a particular mode also changes. For example, an increase in highway congestion would tend to shift auto travelers to public transport, or an increase in transit fare would make auto traveling more attractive. Although current modal share of airport ground access can be easily determined from passenger's revealed preference surveys, any forecast on mode choice is difficult because characteristics of individual travelers vary. This paper attempts to forecast airport ground access and egress trips at John F. Kennedy International Airport (JFK) with the incremental logit or pivot point model. The model is developed by using modal share data from a revealed preference survey conducted by the Port Authority of New York and New Jersey, which operates JFK. The resulting model predicts how changes in highway travel time due to traffic congestion, increases in transit fare to the airport, and changes in waiting and transfer time in the AirTrain system may affect the mode choice of air passengers and employees traveling to and from the airport.

The Impact of Travel Time Reliability and Perceived Service Quality on Airport Ground Access Mode Choice

This study makes two contributions to existing airport ground access mode choice models. The first is an assessment of travel time reliability on air passenger airport ground access mode choice decisions. Revealed preference questions were asked to determine the safety margin allowed for ground access journey to airports. The larger the safety margin allowances, the less reliable the passenger perceived the mode to be. Stated preference questions were also used to determine the impact of travel time reliability on mode choice decisions. The second contribution of this research is the incorporation of air passenger perceived service quality in the calibration of airport ground access mode choice model. With the use of the survey data, the effects of safety margin allowances, travel time reliability, and perceived service quality on ground access mode choices to Hong Kong International Airport are quantified by a multinomial logit-type mode choice model. For strategic planning, the calibrated model can be used by the airport authority and various transport operators for evaluating the changes in the service attributes on modal split pattern in international airports, hence improving the access mode services.

Airport ground access mode choice behavior after the introduction of a new mode: A case study of Taoyuan International Airport in Taiwan

To improve airport ground access at Taoyouan International Airport (TIA) in Taiwan, the government of Taiwan is constructing a mass rapid transit system (TIA MRT) to connect the airport and important traffic hubs such as the Taipei train station and the Taoyouan High Speed Rail station. Using revealed and stated preference data, we investigate the airport ground access mode choice behavior of air passengers who are traveling overseas from Taiwan. A mixed logit model is estimated to identify the preferences of air passengers for the new mode. The results indicate that while out-of-vehicle travel time and in-vehicle travel time are two important factors in affecting outbound travelers’ choice of airport access mode, the amount of overall time-savings and the user-friendly nature of the modal offers are also crucial attributes. We show the extent to which travel time improvements associated with public transportation reduces the market share of private transportation and taxi.

Incorporating passenger perceived service quality in airport ground access mode choice model

This article presents the incorporation of air passenger perceived service quality in the calibration of airport ground access mode choice model. Structural Equation Modelling is used to construct a ‘satisfaction’ latent variable to relate air passenger perception on the airport ground access modes with the characteristics of the trip and of the passengers themselves. The ‘satisfaction’ latent variable is incorporated into the discrete choice model, which is used for evaluating the ground access modal split pattern at Hong Kong International Airport (HKIA). The model results indicated that satisfaction level is associated with mode utility. By incorporating the ‘satisfaction’ latent variable into the discrete choice model, air passenger ground access mode choice behaviour is then modelled more precisely. Hence, a better understanding on the demand for various ground access mode choices at HKIA can be obtained.

Air Passenger Preferences for Choice of Airport and Ground Access Mode in the New York City Metropolitan Region

In current practice, regional models are limited in their capability to analyze policies involving changes and improvements to airports (and their services) and ground access transportation. Typically, airports are treated only as employment centers or as special generators. Important and distinct features of air passenger travel affecting trip distribution and mode choice are rarely modeled explicitly. This paper presents the development of a joint airport and ground access mode choice model for the New York City metropolitan region based on an extensive survey of airport users. Unlike travel to and from most U.S. cities, air passengers flying to and from the New York region face a nontrivial choice of airports and ground access modes (including premium transit options). A nested logit model was formulated with airport choice at the upper level and ground access mode choice at the second level; however, a multinomial logit model was found to be statistically preferable. Results indicate that air passenger travel behavior is significantly different for business and nonbusiness travelers. Overall, willingness to pay for trips to and from the airport is much higher than for regular intracity trips. Average yield, access time, and access cost are the most important determinants of air passenger's choice; demographics and trip characteristics are also significant. The developed tool was used for a comprehensive study of airport development alternatives in the New York region and is seen as the platform for additional data development and model extensions for future studies of air passenger service planning in the New York megaregion.

Predictive Reliability of Airport Ground Access Mode Choice Models

Airport ground access mode choice models provide an essential analytical capability to support airport ground transportation planning studies as well as studies addressing the allocation of air travel demand among multiple airports in a region. A growing number of such models have been described in the literature: the models vary widely in functional form, explanatory variables, and estimated parameter values. However, almost no attention has been given to how reliably these models predict air passenger mode choice for time periods different from those for which they have been estimated or when available ground access services change. Both considerations are critical to the application of such models for forecasting. In attempting to rectify this situation, the predictive reliability of typical airport ground access models is addressed from two perspectives: (a) the variability of airport ground access mode use over time and implications of this variation for the application of ground access mode choice models and (b) how well models estimated on data collected at one time predict air traveler ground access mode use at other times or in different situations. The requirements for an empirical analysis that would apply an existing model to predict mode use in a later year or for a different airport are discussed, and the predicted mode use is compared with the actual mode use observed in air passenger surveys to assess the predictive reliability of the model.

Predictive Reliability of Airport Ground Access Mode Choice Models

Airport ground access mode choice models provide an essential analytical capability to support airport ground transportation planning studies as well as studies addressing the allocation of air travel demand among multiple airports in a region. A growing number of such models have been described in the literature: the models vary widely in functional form, explanatory variables, and estimated parameter values. However, almost no attention has been given to how reliably these models predict air passenger mode choice for time periods different from those for which they have been estimated or when available ground access services change. Both considerations are critical to the application of such models for forecasting. In attempting to rectify this situation, the predictive reliability of typical airport ground access models is addressed from two perspectives: ( a) the variability of airport ground access mode use over time and implications of this variation for the application of ground access mode choice models and ( b) how well models estimated on data collected at one time predict air traveler ground access mode use at other times or in different situations. The requirements for an empirical analysis that would apply an existing model to predict mode use in a later year or for a different airport are discussed, and the predicted mode use is compared with the actual mode use observed in air passenger surveys to assess the predictive reliability of the model.