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

2017 ◽  
Vol 2626 (1) ◽  
pp. 85-98
Author(s):  
Duncan Kisia
Keyword(s):  
New York ◽  
Choice Model ◽  
Mode Choice ◽  
Revealed Preference ◽  
Choice Models ◽  
Model Parameters ◽  
Preference Data ◽  
Access Mode ◽  
Analytical Strategies ◽  
Airport Access

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.

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

2021 ◽  
pp. 036119812110190
Author(s):  
Yanbo Ge ◽  
Alec Biehl ◽  
Srinath Ravulaparthy ◽  
Venu Garikapati ◽  
Monte Lunacek ◽  
...  
Keyword(s):  
Choice Model ◽  
Mode Choice ◽  
Revealed Preference ◽  
Predictive Performance ◽  
Joint Modeling ◽  
Joint Model ◽  
Access Mode ◽  
Revenue Estimates ◽  
Airport Access ◽  
Context Specific

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.

scholarly journals The Impact of Perception toward the Built Environment in Airport Access Mode Choice Using Hybrid Choice Modeling

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Mahdi Yazdanpanah ◽  
Mansour Hadji Hosseinlou
Keyword(s):  
Built Environment ◽  
Latent Variable ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Residential Areas ◽  
Education Experience ◽  
Access Mode ◽  
Airport Access ◽  
The Impact

Built environment (BE), as an objective variable, plays a substantial role in urban residents’ behavior. However, the perception toward a BE, as a subjective variable, varies among people. To identify the role of perception toward BE, we used a stated preference (SP) survey conducted in January–February 2015 at the Imam Khomeini International Airport (IKIA), Tehran, Iran. The data was drawn from 641 individuals; 359 of them were residents of Tehran. For the estimation of the model, a hybrid discrete choice model was used to capture the latent variable, in addition to mode attributes and trip conditions, with 1795 SP observations. Psychometric questions concerned the perception of ease in access to main streets or highways and good traffic conditions within their residential areas. The results showed that the latent variable (positive perception toward built environment or PBE) had a significant positive effect on people’s willingness to park at the airport. Moreover, the gender, age, marital status, level of education, experience living in a foreign country, and income level also influenced the formation of perception toward the BE and airport transportation mode choice.

Large-Scale Application of a Combined Destination and Mode Choice Model Estimated with Mixed Stated and Revealed Preference Data

2017 ◽  
Vol 2669 (1) ◽  
pp. 31-40 ◽  
Author(s):  
Michael Heilig ◽  
Nicolai Mallig ◽  
Tim Hilgert ◽  
Martin Kagerbauer ◽  
Peter Vortisch
Keyword(s):  
Large Scale ◽  
Travel Demand ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Revealed Preference ◽  
Demand Model ◽  
Agent Based ◽  
Preference Data ◽  
Mode Choice Model

The diffusion of new modes of transportation, such as carsharing and electric vehicles, makes it necessary to consider them along with traditional modes in travel demand modeling. However, there are two main challenges for transportation modelers. First, the new modes’ low share of usage leads to a lack of reliable revealed preference data for model estimation. Stated preference survey data are a promising and well-established approach to close this gap. Second, the state-of-the-art model approaches are sometimes stretched to their limits in large-scale applications. This research developed a combined destination and mode choice model to consider these new modes in the agent-based travel demand model mobiTopp. Mixed revealed and stated preference data were used, and new modes (carsharing, bikesharing, and electric bicycles) were added to the mode choice set. This paper presents both challenges of the modeling process, mainly caused by large-scale application, and the results of the new combined model, which are as good as those of the former sequential model although it also takes the new modes into consideration.

scholarly journals Allowing for Heterogeneity in the Consideration of Airport Access Modes: The Case of Bari Airport

2019 ◽  
Vol 2673 (8) ◽  
pp. 50-61 ◽  
Author(s):  
Angela S. Bergantino ◽  
Mauro Capurso ◽  
Thijs Dekker ◽  
Stephane Hess
Keyword(s):  
Public Transport ◽  
Latent Variable ◽  
Choice Model ◽  
Mode Choice ◽  
Reasonable Assumption ◽  
The Public ◽  
Transport Services ◽  
Variable Approach ◽  
Access Mode ◽  
Airport Access

Mode choice models traditionally assume that all objectively available alternatives are considered. This might not always be a reasonable assumption, even when the number of alternatives is limited. Consideration of alternatives, like many other aspects of the decision-making process, cannot be observed by the analyst, and can only be imperfectly measured. As part of a stated choice survey aimed at unveiling air passengers’ preferences for access modes to Bari International Airport in Italy, we collected a wide set of indicators that either directly or indirectly measure respondents’ consideration of the public transport alternatives. In our access mode choice model, consideration of public transport services was treated as a latent variable, and entered the utility function for this mode through a “discounting” factor. The proposed integrated choice and latent variable approach allows the analyst not only to overcome potential endogeneity and measurement error issues associated with the indicators, but also makes the model suitable for forecasting. As a result of accounting for consideration effects, we observed an improvement in fit that also held in a validation sample; moreover, the effects of policy changes aimed at improving the modal share of public transport were considerably reduced.

scholarly journals Do millennials value travel time differently because of productive multitasking? A revealed-preference study of Northern California commuters

2021 ◽  
Author(s):  
Aliaksandr Malokin ◽  
Giovanni Circella ◽  
Patricia L. Mokhtarian
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Willingness To Pay ◽  
Travel Time ◽  
Choice Model ◽  
Mode Choice ◽  
Revealed Preference ◽  
Northern California ◽  
Factors Affecting ◽  
The Impact

AbstractMillennials, the demographic cohort born in the last two decades of the twentieth century, are reported to adopt information and communication technologies (ICTs) in their everyday lives, including travel, to a greater extent than older generations. As ICT-driven travel-based multitasking influences travelers’ experience and satisfaction in various ways, millennials are expected to be affected at a greater scale. Still, to our knowledge, no previous studies have specifically focused on the impact of travel multitasking on travel behavior and the value of travel time (VOTT) of young adults. To address this gap, we use an original dataset collected among Northern California commuters (N = 2216) to analyze the magnitude and significance of individual and household-level factors affecting commute mode choice. We estimate a revealed-preference mode choice model and investigate the differences between millennials and older adults in the sample. Additionally, we conduct a sensitivity analysis to explore how incorporation of explanatory factors such as attitudes and propensity to multitask while traveling in mode choice models affects coefficient estimates, VOTT, and willingness to pay to use a laptop on the commute. Compared to non-millennials, the mode choice of millennials is found to be less affected by socio-economic characteristics and more strongly influenced by the activities performed while traveling. Young adults are found to have lower VOTT than older adults for both in-vehicle (15.0% less) and out-of-vehicle travel time (15.7% less), and higher willingness to pay (in time or money) to use a laptop, even after controlling for demographic traits, personal attitudes, and the propensity to multitask. This study contributes to better understanding the commuting behavior of millennials, and the factors affecting it, a topic of interest to transportation researchers, planners, and practitioners.

scholarly journals Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari
Keyword(s):  
Discrete Choice ◽  
Public Transportation ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Choice Analysis ◽  
Mode Choice Model

Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Logit Model. The research data obtained through Stated Preference (SP) techniques. The model using the attribute influences such as tariff, travel time, headway and walking time. The models obtained are reliable and validated. Based on the results of the analysis shows that the most sensitive attributes affect the mode choice model is the tariff.

scholarly journals The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis

2014 ◽  
Vol 26 (2) ◽  
pp. 109-119 ◽  
Author(s):  
Chuan Ding ◽  
Chao Liu ◽  
Yaoyu Lin ◽  
Yaowu Wang
Keyword(s):  
Co2 Emissions ◽  
Mixed Method ◽  
Latent Variables ◽  
Choice Model ◽  
Mode Choice ◽  
Car Ownership ◽  
Simultaneous Estimation ◽  
Model Parameters ◽  
Employer Attitudes ◽  
The Impact

Reducing car trips and promoting green commuting modes are generally considered important solutions to reduce the increase of energy consumption and transportation CO2 emissions. One potential solution for alleviating transportation CO2 emissions has been to identify a role for the employer through green commuter programs. This paper offers an approach to assess the effects of employer attitudes towards green commuting plans on commuter mode choice and the intermediary role car ownership plays in the mode choice decision process. A mixed method which extends the traditional discrete choice model by incorporating latent variables and mediating variables with a structure equation model was used to better understand the commuter mode choice behaviour. The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process. The results found in this paper provide helpful information for transportation and planning policymakers to test the transportation and planning policies effects and encourage green commuting reducing transportation CO2 emissions.

scholarly journals Understanding Attitudes towards Proenvironmental Travel: An Empirical Study from Tangshan City in China

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaoping Fang ◽  
Yajing Xu ◽  
Weiya Chen
Keyword(s):  
Travel Behavior ◽  
Mode Choice ◽  
Revealed Preference ◽  
Individual Characteristics ◽  
Survey Method ◽  
Model Parameters ◽  
Travel Mode ◽  
Preference Theory ◽  
Travel Mode Choice ◽  
Revealed Preference Theory

Understanding people’s attitudes towards proenvironmental travel will help to encourage people to adopt proenvironmental travel behavior. Revealed preference theory assumes that the consumption preference of consumers can be revealed by their consumption behavior. In order to investigate the influences on citizens’ travel decision and analyze the difficulties of promoting proenvironmental travel behavior in medium-sized cities in China, based on revealed preference theory, this paper uses the RP survey method and disaggregate model to analyze how individual characteristics, situational factors, and trip features influence the travel mode choice. The field investigation was conducted in Tangshan City to obtain the RP data. An MNL model was built to deal with the travel mode choice. SPSS software was used to calibrate the model parameters. The goodness-of-fit tests and the predicted outcome demonstrate the validation of the parameter setting. The results show that gender, occupation, trip purpose, and distance have an obvious influence on the travel mode choice. In particular, the male gender, high income, and business travel show a high correlation with carbon-intensive travel, while the female gender and a medium income scored higher in terms of proenvironmental travel modes, such as walking, cycling, and public transport.

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