The effects of seat width, load factor, and passenger demographics on airline passenger accommodation

Miller, Elizabeth; Lapp, Samuel; Parkinson, Matthew B.

doi:10.1080/00140139.2018.1550209

Cited by 11 publications

(5 citation statements)

References 16 publications

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“…We believe that low load is an area that can reflect obvious preferences. It has been observed that the maximum cabin load factor is 99.6%, Mdn � 17.2% (12.3-31.2); the maximum occupancy of standing space is 99.1%, Mdn � 11.1% (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20); and the maximum occupancy of seats is 105.6%, Mdn � 80.6% (68.8-97.2). In addition, the growth relationship is fitted (Figure 3)-when the load factor of the cabin reaches 40%, the occupancy of seats reaches saturation (occupancy rate being 100%) in advance; furthermore, there are always passengers standing in the cabin even when there is a vacant seat.…”

Section: Cabin Loadmentioning

confidence: 99%

“…ere is still a lack of research on observing all passengers in one cabin as objects [12]. Since each person's position is fixed in planes [13], trains [14], buses [15], and cars [16], it is feasible to investigate the individual passenger's behavior. However, since passengers are allowed to stand and freely change positions in the subway cabin, passengers standing in the subway also need to be paid attention to in addition to those who are seated, and they are also included in the rated number of passengers on the subway together with those seated.…”

Section: Introductionmentioning

confidence: 99%

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Study on Occupancy Behaviors of Passengers in the Subway Cabin: An Observation in Chengdu, China

Zhi

2022

Journal of Advanced Transportation

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Insufficient attention has been paid to how subway cabins are used by passengers and especially the distribution of passengers and occupancy of facilities. In this study, passengers were observed in 133 sections from the beginning to the end of the early peak of Chengdu Metro in the working days. The differences in occupancy behaviors of passengers to different areas, seats, and standing auxiliary facilities in the cabin were analyzed by the nonparametric test. The occupancy curve was fitted by the least square method from the minimum to the maximum load factor, and the prediction and explanatory model for the use of cabin was established. As expected, the distribution of passengers in the cabin is uneven. The highest occupancy rate has been maintained at the cabin end. Female passengers accounted for the largest proportion in the door area, while male passengers accounted for a larger proportion at the end of the cabin. There is no difference in the use of different seat types by passengers. There are more seats in female passengers, and females are more likely to get the remaining seats when the seat load is nearly saturated. For the auxiliary standing facilities, there are always passengers who do not use the facilities and the proportion is increasing. The facilities that can be relied on account for a greater median proportion of the passengers with facilities, but service capacity is limited. In response to these conclusions, measures to improve the design of the cabin are proposed.

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Section: Cabin Loadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Study on Occupancy Behaviors of Passengers in the Subway Cabin: An Observation in Chengdu, China

Zhi

2022

Journal of Advanced Transportation

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“…One study investigated both seat width and legroom (Molenbroek et al, 2017), but was limited to average seat dimensions and did not analyze a range of seat dimensions. Other studies investigated either legroom (Porta et al, 2019) or seat width dimensions (Miller et al, 2019), but no studies have calculated the percentage of the general population who are accommodated by the combination of both seat width and legroom over a range of seat dimensions using a multivariate model based on recent U.S. anthropometric data.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Percentage of U.S. General Population Accommodated by Commercial Airline Seats

Rusch¹,

Marklin²

2022

Ergonomics in Design: The Quarterly of Human Factors Applicatio

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The number of seats per airplane has increased over the years, leading to a decrease in seat width and legroom. Using the HFES Multivariate Accommodation Testing Tool, the percentage of the general population accommodated in a static seated posture was calculated with respect to two important design dimensions of airline seats, seat width and legroom. Results from this article can inform seat manufacturers and airlines on how to design seats that physically accommodate the largest number of passengers. This paper does not address passenger safety and comfort, which are complex, multi-factor issues that extend beyond physical accommodation.

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“…However, the aircraft cabin is a special environment that presents some unusual characteristics, including an enclosed space, interpersonal distance that is too close, limited adjustment space, and sometimes a long flight duration. Most travelers fly in economy class [34], and thus it is significant to study how comfortable passengers are in economy class. e space in economy class cabins is very limited compared with first and business class.…”

Section: Introductionmentioning

confidence: 99%

Effect of Personal Space Invasion on Passenger Comfort and Comfort Design of an Aircraft Cabin

Wang

Fan

Chu

et al. 2021

Mathematical Problems in Engineering

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Passenger comfort is becoming an important issue with the recent increase in air travel. A common cause of passenger discomfort and distress is the invasion of the passenger’s personal space. This paper presents the results of two studies addressing the environmental psychological characteristics of passengers during personal space invasion (PSI) and how PSI affects cabin comfort design. In study 1, our survey shows that PSI has different effects on the comfort of passengers with different genders, ages, education levels, and interpersonal relationships. From these survey data, we extracted 14 factors of PSI. In study 2, a Decision-Making Trial and Evaluation Laboratory (DEMATEL) model was established, with passenger comfort as the target layer, to determine the interrelation between 14 PSI factors. The causal relationships between the 14 factors were visualized by a causal diagram. We established a priority ranking of the 14 aircraft interior design indexes based on the corresponding relationships between the indexes and PSI factors. The findings of this study contribute to the understanding of how PSI impacts passenger comfort and offer strategies to improve the comfort design of aircraft cabins.

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The effects of seat width, load factor, and passenger demographics on airline passenger accommodation

Cited by 11 publications

References 16 publications

Study on Occupancy Behaviors of Passengers in the Subway Cabin: An Observation in Chengdu, China

Study on Occupancy Behaviors of Passengers in the Subway Cabin: An Observation in Chengdu, China

Percentage of U.S. General Population Accommodated by Commercial Airline Seats

Effect of Personal Space Invasion on Passenger Comfort and Comfort Design of an Aircraft Cabin

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