A passenger distribution analysis model for the perceived time of airplane boarding/deboarding, utilizing an ex-Gaussian distribution

https://doi.org/10.1016/j.jairtraman.2016.11.010Get rights and content

Highlights

  • This study focuses on modeling the perceived time of airplane boarding/deboarding.

  • An ex-Gaussian distribution is employed to develop a model.

  • An experiment analyzes passengers' assessment of boarding/deboarding times.

  • A ratio between perceived time and measured time as a variable is positively skewed.

Abstract

This study focused on modeling the perceived time of boarding/deboarding. We conducted an experiment to understand how passengers in the study assessed boarding/deboarding times. According to the results of the analysis, the passenger distribution that took a ratio between perceived time and measured time as a variable was positively skewed. This distribution indicated that the proportion of the passengers for whom perceived time was longer than measured time varied depending on the experimental conditions. Based on this analysis, we have employed an ex-Gaussian distribution to develop a model. The model has revealed that the parameter τ, which expressed the length of the ex-Gaussian distribution tail, varied depending on the load factor, seat pitch, and boarding/deboarding methods. By changing these factors, it will be possible to shorten perceived time for certain passengers whose perceived time of boarding/deboarding is longer than measured time.

Introduction

Airplane movements at airports worldwide have been on an increasing trend lately, and airline companies are implementing various measures to reduce the time between flight arrival and departure to ensure timeliness. Within the flow of events from the time the airplane reaches the airport, the passengers disembark, the airplane's interior is cleaned and prepared, supplies are replenished, the next passengers board, to when the airplane departs again, boarding and deboarding take a long time, mainly because the passenger aisle is narrow and gets congested. Therefore, airline companies must reduce passenger boarding time for timely departure of flights. Consequently, airlines have developed various passenger boarding methods, such as boarding by row or giving priority boarding for passengers seated from back to front (Marelli et al., 1998, Van Landeghem and Beuselinck, 2002). Modifying the boarding time using boarding methods has been modeled in computer simulations in the past (Marelli et al., 1998, Van Landeghem and Beuselinck, 2002, Briel et al., 2003, Ferrari and Nagel, 2005, Bachmat et al., 2006; and Steffen, 2008). These methods have also been confirmed through experiments that used a mock-up of airplanes (Steffen, 2012). These studies confirm that the back-to-front boarding method does not necessarily minimize airplane boarding time.

On the other hand, in recent years, research related to perceived time is attracting attention in the field of travel behavior research. For example, a study on public transportation travel time found that the perceived time for traveling is longer for car drivers with regard to public transportation than the actual public transportation travel time, which explains why the modal shift from cars to public transportation has been difficult (Van Exel and Rietveld, 2010). Also, if the waiting time at the station was long, the perceived travel time of public transportation became longer, which again impacted the choice of public transport (González et al., 2015). Because the level of satisfaction greatly impacts airline selection, reducing actual boarding and deboarding times is critical for the airlines to increase passenger satisfaction. In addition to shortening the physical boarding time, shortening perceived time is also effective in improving passenger satisfaction.

This study focused on modeling the perceived time of boarding/deboarding, a topic presently unexplored in the literature. Moreover, it attempted to understand how passengers evaluate boarding and deboarding times, using an ex-Gaussian distribution enabled to determine the proportion of passengers whose perceived time was longer than the actual physical time it took for them to board and deboard. This will be useful in developing measures to improve passengers' level of satisfaction.

Section snippets

Experiments

We conducted an experiment that compared perceived time with measured time, where the latter is the physical time taken to board and deboard. The experiment was conducted using tables and chairs placed in a room and were made to resemble the interior of an airplane. Participants acting as passengers were handed boarding passes and instructed to go to their allotted seats. A stopwatch was used to measure the duration from the time the first passenger entered the airplane to the time that the

The model

In Fig. 2, the passenger distribution that takes Tp/Tm as the variable is positively skewed. With respect to constructing the passenger distribution model, positively skewed distributions, such as a log-normal distribution, an ex-Gaussian distribution, a Weibull distribution, and a Gumbel distribution, are considered appropriate. As is clear from the results of the experiment, there is a difference with respect to the proportion of Tp/Tm > 1 for each case. Therefore, formulating a model using

Discussion

In the field of experimental psychology, time perception refers to the time interval that is estimated by one's own perception. Numerous studies have been conducted in this field, and several models have been constructed and proposed on the basis of the experimental results. For example, in the change model, a participant's internal clock changes depending on their metabolism (Hoagland, 1933, Hoagland, 1981); in the storage size model, perceived time changes depending on the amount of

Conclusion

This study showed that in airplane boarding and deboarding, the proportion of passengers for whom perceived time was longer than measured time can be expressed through the τ parameter of an ex-Gaussian distribution. This is possible by modeling passenger distribution using an ex-Gaussian distribution with the ratio of perceived time and measured time taken as the variable. Further, differences in the load factor, seat pitch, and boarding/deboarding methods are considered as the factors to

Acknowledgements

We sincerely appreciate the valuable discussions held with Professor Makoto Ichikawa from Chiba University, Special Associate Professor Satoru Nakajo from The University of Tokyo, and Associate Professor Daichi Yanagisawa from The University of Tokyo. This work was supported by JSPS KAKENHI Grant Number 25287026.

References (18)

There are more references available in the full text version of this article.

Cited by (27)

  • A new model of luggage storage time while boarding an airplane: An experimental test

    2020, Journal of Air Transport Management
    Citation Excerpt :

    Experimentation is an effective method for overcoming the above problems, and some scholars have adopted experimental methods for studying boarding problems. However, the main aspects of these studies are passenger check-in luggage measurements, seat interference simulation, and equivalent boarding experiments, e.g., a 72-person boarding narrow-body mock airplane experiment (Steffen and Hotchkiss, 2012), 30-person classroom experiment (Miura and Nishinari, 2017), 40-person bus experiment (Qiang, 2017), or micro-behaviors trials involving 35 subjects inside a cabin section (Gwynne et al., 2018). These experiments were conducted in less realistic test setups.

  • Bayesian network modeling explorations of strategies on reducing perceived transfer time for urban rail transit service improvement in different seasons

    2019, Cities
    Citation Excerpt :

    Fan et al. (2016) discover that the multiple regression equations with cross terms are able to explain the impacts of gender of a passenger, infrastructure of a bus stop, security of waiting environment, etc. on the perceived time spent in waiting for bus. In addition, it is affirmed by Miura and Nishinari (2017) that the boarding rate of a passenger airplane, space between the seats in the cabin, etc. affect the perceived time costs of the passengers for their boarding and getting off the airplane. Though the perceived time costs in different stages of a trip have been studied for a long time, the PTT has been seldom studied in particular for the URT trips, owing to the uncertain and complex influences of its multiple factors.

  • Customer-oriented optimization of the airplane boarding process

    2019, Journal of Air Transport Management
    Citation Excerpt :

    Unfortunately, the theoretically fastest way to board an airplane might not be accepted by the passengers for psychological reasons (Steffen, 2008), which is probably why most of the airlines adhere to a random or slightly adjusted boarding pattern. This may also be the reason for investigating the passengers' perceived boarding time (Miura and Nishinari, 2017; Ren and Xu, 2018). In addition to the boarding pattern, approaches to improving the boarding time include, for instance, seat number allocations being given to passengers when they pass the boarding gate (Notomista et al., 2016), seat assignments based on the passengers’ carry-on luggage (Milne and Salari, 2016) and infrastructural changes, such as providing a wide aisle by using Side-Slip-Seats (Schultz, 2017).

  • Machine learning approach to predict aircraft boarding

    2019, Transportation Research Part C: Emerging Technologies
    Citation Excerpt :

    Schultz (2018a) provides a set of operational data including classification of boarding times, passenger arrival times, time to store hand luggage, and passenger interactions in the aircraft cabin as a fundamental basis for boarding model calibration. Miura and Nishinari (2017) conducted an experiment to understand how passengers assessed boarding/deboarding times. If the research is aimed at finding an optimal solution for the boarding sequence, evolutionary/genetic algorithms are used to solve the complex problem (e.g. Li et al., 2007; Wang and Ma, 2009; Soolaki et al., 2012; Schultz, 2017).

  • Experimental analyses of airplane boarding based on interference classification

    2018, Journal of Air Transport Management
    Citation Excerpt :

    Perceived time is estimated by an individual's own perception, and affects passenger experience and satisfaction. Miura and Nishinari (2017) indicated that the ratio of perceived time to actual time corresponds to a Gaussian distribution. Load factor, seat pitch, and boarding strategies are factors that change perceived time.

View all citing articles on Scopus
View full text