Article

Symmetrical design of strategy-pairs for enplaning and deplaning an airplane

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Abstract

Enplaning and deplaning processes are two main activities that passengers experience in an airplane. They are also the main factors contributing to the airplane turn time. Thus, both processes need to be carefully considered when designing a new strategy. The main contribution of this paper is twofold. Firstly, we propose a symmetrical design of deplaning strategies to match three typical grouped enplaning strategies (back-to-front, windows-to-aisle and reverse pyramid), in which the groups are organized in a LIFO (Last In First Out) manner. Secondly, we present an integrated cellular automaton model to describe the dynamic characteristics of passengers in the enplaning and deplaning processes. Numerical evaluation results indicate that the proposed windows-to-aisle and reverse pyramid strategies perform better in the following aspects: (i) the total operation time decreases; (ii) the two strategies are less sensitive to the load condition, e.g., luggage distribution and cabin occupancy rate; (iii) passengers’ satisfaction is enhanced since both individual waiting time and processing time lower down; (iv) the two strategies are fairer for the passengers since the difference among the groups remarkably shrinks.

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... The other is seat interference, which happens when a window or middle seat passenger is blocked by other passengers who are already sitting in the same half-row. Efforts have been made to reduce those two interferences in boarding time, and most of them are based on simulation works, either by discrete modeling [3][4][5][6] or by continuous modeling [7,8]. Various optimal boarding strategies are proposed to reduce boarding time. ...
... Seven strategies were selected, including Random, Free, Back-to-front, Window-to-aisle, Steffen, Steffen-lug, and CRBF (column rotated in a back to front order, see Section 2.3 for details). In addition, we evaluated two structured deboarding strategies proposed in [6,14], as the authors claimed that deplaning passengers in a structured manner reduces the deboarding time. Moreover, how the passengers' seat preference influences the free boarding time is another interest of our work. ...
... Unstructured deplaning is the most used strategy adopted by airline companies, in which passengers leave the airplane without any instruction. It has been suggested in [6,14] that structured deplaning strategies may reduce the deplaning time. To what extent these structured deboarding strategies will quicken the deplaning process was also the focus of our attention. ...
Article
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Optimally organizing passengers boarding/deboarding an airplane offers a potential way to reduce the airplane turn time. The main contribution of our work is that we evaluate seven boarding strategies and two structured deboarding strategies by using a surrogate experimental test. Instead of boarding a real or mocked airplane, we carried out the experiment by organizing 40 participants to board a school bus with ten rows of four seats, symmetrically distributed on a single, central aisle. Experimental results confirm that the optimized strategies, i.e., Steffen and Steffen-lug, are superior to the traditional ones, i.e., Back-to-front, Window-to-aisle, and Random in time-saving and stability. However, the two structured deboarding strategies failed to reduce the deboarding time, and this result strongly suggests the prerequisites of applying such strategies only when, on average, passengers have a large amount of luggage. Besides, we further carried out a questionnaire survey of participants' preferences on seat layout and discussed how those preferences influence the boarding time.
... As stated by the authors themselves, it is a major drawback, since it cannot lead to a deeper understanding of the boarding problem. In Qiang et al. (2016b), an agent-based model is used to propose a strategy with group behaviour to study boarding and deboarding. In fact, the authors claim that potential optimisation might be achieved by considering the boarding and deboarding processes in a integrated way. ...
... As far as the model limitations are concerned, it does not take into account the saturation of overhead bins, which may deeply affect the final boarding/deboarding time (Milne et al., 2018;Milne and Kelly, 2014;Milne and Salari, 2016), the effect of groups (Qiang et al., 2016b;Tang et al., 2018) and passengers' individual properties (Qiang et al., 2014) in boarding/deboarding, and does not implement a specific detailed model to accurately estimate ground operations. Despite its limitations, which also represent an opportunity for future studies, SimBaD seems to be a versatile tool, capable of handling different cabin layouts, thus allowing also for sensitivity and comparative analyses of the internal cabin design. ...
Preprint
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This work deals with the problem of estimating the turnaround time in the early stages of aircraft design. The turnaround time has a significant impact in terms of marketability and value creation potential of an aircraft and, for this reason, it should be considered as an important driver of fuselage and cabin design decisions. Estimating the turnaround time during the early stages of aircraft design is therefore an essential task. This task becomes even more decisive when designers explore unconventional aircraft architectures or, in general, are still evaluating the fuselage design and its internal layout. In particular, it is of paramount importance to properly estimate the boarding and deboarding times, which contribute for up the 40% to the overall turnaround time. For this purpose, a tool, called SimBaD, has been developed and validated with publicly available data for existing aircraft of different classes. In order to demonstrate SimBaD capability of evaluating the influence of fuselage and cabin features on the turnaround time, its application to an unconventional box-wing aircraft architecture, known as PrandtlPlane, is presented as case study. Finally, considering standard scenarios provided by aircraft manufacturers, a comparison between the turnaround time of the PrandtlPlane and the turnaround time of a conventional competitor aircraft is presented.
... As stated by the authors themselves, it is a major drawback, since it cannot lead to a deeper understanding of the boarding problem. In Qiang et al. (2016b), an agent-based model is used to propose a strategy with group behaviour to study boarding and deboarding. In fact, the authors claim that potential optimisation might be achieved by considering the boarding and deboarding processes in a integrated way. ...
... As far as the model limitations are concerned, it does not take into account the saturation of overhead bins, which may deeply affect the final boarding/deboarding time (Milne and Kelly, 2014;Milne et al., 2018;Milne and Salari, 2016), the effect of groups (Qiang et al., 2016b;Tang et al., 2018) and passengers' individual properties (Qiang et al., 2014) in boarding/deboarding, and does not implement a specific detailed model to accurately estimate ground operations. Despite its limitations, which also represent an opportunity for future studies, SimBaD seems to be a versatile tool, capable of handling different cabin layouts, thus allowing also for sensitivity and comparative analyses of the internal cabin design. ...
Article
This work deals with the problem of estimating the turnaround time in the early stages of aircraft design. The turnaround time has a significant impact in terms of marketability and value creation potential of an aircraft and, for this reason, it should be considered as an important driver of fuselage and cabin design decisions. Estimating the turnaround time during the early stages of aircraft design is therefore an essential task. This task becomes even more decisive when designers explore unconventional aircraft architectures or, in general, are still evaluating the fuselage design and its internal layout. In particular, it is of paramount importance to properly estimate the boarding and deboarding times, which contribute for up the 40% to the overall turnaround time. For this purpose, a tool, called SimBaD, has been developed and validated with publicly available data for existing aircraft of different classes. In order to demonstrate SimBaD capability of evaluating the influence of fuselage and cabin features on the turnaround time, its application to an unconventional box-wing aircraft architecture, known as PrandtlPlane, is presented as case study. Finally, considering standard scenarios provided by aircraft manufacturers, a comparison between the turnaround time of the PrandtlPlane and the turnaround time of a conventional competitor aircraft is presented.
... Moreover, for most strategies, an almost linear correlation was observed between the occupancy level and the boarding time;however, there was a tendency for a disproportionate increase in boarding time. The same result was obtained from the simulation performed byQiang et al. (2016b).In simulation experiments, Schultz(2010), Fonseca i Casas et al. (2013), and Mas et al. (2013) all observed not only a linear relationship between the occupancy level and the boarding time for random boarding, but also a disproportionate, positive relationship for back-to-front boarding. Mas et al. (2013) also assessed boarding strategies using different airplane types. ...
... The direction of most influences is expected to be the same as when analyzed separately. However, the larger the capacity (ceteris paribus, hence not more passengers), the less time that should be necessary for boarding because more space is available in the aisle, allowing for more parallel stowing of carry-on baggage and leading to less congestion (see,Mas et al. (2013), andQiang et al. (2016b)).Hypothesis 1B (H1B): The more passengers boarding an airplane, ceteris paribus, the longer the total boarding time.Hypothesis 2B (H2B): The larger the total capacity of an airplane, ceteris paribus, the shorter the total boarding time.Hypothesis 3B (H3B): The higher the average amount of carry-on baggage per passenger in an airplane, ceteris paribus, the longer the total boarding time. ...
Thesis
Die Arbeit beschäftigt sich mit dem Einsteigeprozess von Passagieren in ein Flugzeug und beleuchtet diesen zunächst allgemein, bevor empirisch untersucht wird, ob sich der Boardingprozess auf dem kritischen Pfad des Flugzeug-Turnarounds befindet und welche Einflussfaktoren auf die Boardingzeit wirken.
... In the context of deboarding, the seat interference disappears and only the interference of passengers in the aisle is important for an efficient process. Wald et al. (2014) provide a study of deplaning strategies using stochastic optimization methods, Qiang et al. (2016) use a cellular automaton approach and Miura and Nishinari (2017) conducted an experiment to understand how passengers assessed boarding/deboarding times with a model using an ex-Gaussian distribution. If research aims at finding an optimal solution for the boarding sequence, evolutionary/genetic algorithms are used to solve the complex problem (Li et al., 2007;Schultz, 2017b,c;Soolaki et al., 2012;Wang, 2009). ...
... In the context of deboarding, the seat interference disappears and only the interference of passengers in the aisle is important for an efficient process. Wald et al. (2014) provide a study of deplaning strategies using stochastic optimization methods, Qiang et al. (2016) use a cellular automaton approach and Miura and Nishinari (2017) employ a model using an ex-Gaussian distribution. ...
Thesis
Full-text available
This cumulative habilitation thesis documents my research in the field of air traffic management with a specific focus on the aircraft ground operations. My research interests aims at a seamless transport network, where the aircraft and passenger trajectories are synchronized. Thus, I started working on aircraft turnaround and in particular the passenger controlled boarding process. My research followed consequently a development process: model creation, calibration, validation, evaluation of technologies and procedures, and field trials. Finally, I developed and realized two innovative concepts: a future connected cabin, which allows to predict the boarding progress in real-time using the connected aircraft cabin as a sensor network, and the dynamic seat allocation, which provides a passenger and service focused boarding with a minimum of negative interferences. I developed a stochastic model for aircraft boarding to cover both individual passenger behavior and operational constraints from airlines and airport. In close cooperation with airlines and airports field trials were conducted and field measurements were used to calibrate input parameters of the boarding model and to validate simulation results. The stochastic model was used to evaluate a high bandwidth of different boarding strategies and innovative technologies, such as the Side-Slip Seat. The evaluation shows that the numbers of expected interferences between passengers during storage of hand luggage and seating could be used as a metric of complexity to predict the final boarding time. In the next step, a sensor concept was developed to detect the position of passengers in the aircraft cabin (seat sensor, sensor floor in the aisle). This concept was realized in a closed cooperation with Eurowings and supported by Cologne Bonn airport, where an A319 was equipped with sensors in the cabin and a field trial was conducted. In parallel, the approach of dynamic seat allocation was successfully tested.
... The costs of these delays have been estimated from $30 to $250 per minute [2]. The time to board passengers can contribute to these delays [3][4][5]. A number of researchers have created and investigated methods that board passengers by groups, with the group assignment depending upon their seat assignment [6][7][8][9][10][11][12][13][14]. ...
... Constraint (4) ensures that exactly one combination of luggage is assigned for the three passengers sitting in the aisle, middle, and window seats on each side of each row of the plane. Constraint (5) ensures that the total number of passengers carrying a specified number of bags aboard the plane equals the total number of passengers assigned to seats. Constraints (6) through (10) control passenger flow by ensuring that a passenger cannot begin to enter a row until he/she is at the beginning of that row (6) nor until that row has been cleared of all passengers who have previously boarded (7). ...
Article
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We present a method that reduces the time it takes to complete the passenger boarding of an airplane. In particular, we describe a two-stage mixed integer programming (MIP) approach, which assigns passengers to seats on an airplane based on the number of bags they carry aboard the plane. The first stage is an MIP that assigns passengers to seats to minimize the time to complete the boarding of the plane. The second-stage MIP also determines seating assignments, while constraining the total boarding time to that determined by the stage-one MIP and maximizing weighted slack times to provide a more robust assignment. Numerical results show that this two-stage approach results in lower average boarding times than the one-stage approach, when the time it takes passengers to walk and sit in their seats is random. Experiments indicate that the magnitude of the improvement is not very sensitive to variations in the slack time weights.
... Here, column-wise disembarkation was found to be more effective for narrow-body aircraft [23]. These two structured disembarkation sequences are analyzed in small-scale field trials applying inside-out (column-wise) and back-to-front (block-wise) sequences [24], but in contrast to the prior simulation experiment [25], no significant improvements of the disembarkation time could be demonstrated. ...
Conference Paper
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Boarding and disembarking an aircraft is a time-critical airport ground handling process. Operations in the confined aircraft cabin must also reduce the potential risk of virus transmission to passengers under current COVID-19 boundary conditions. Passenger boarding will generally be regulated by establishing passenger sequences to reduce the influence of negative interactions between passengers (e.g., congestion in the aisle). This regulation cannot be implemented to the same extent when disembarking at the end of a flight. In our approach, we generate an optimized seat allocation that takes into account both the distance constraints of COVID-19 regulations and groups of passengers traveling together (e.g., families or couples). This seat allocation minimizes the potential transmission risk, while at the same time we calculate improved entry sequences for passengers groups (fast boarding). We show in our simulation environment that boarding and disembarkation times can be significantly reduced even if a physical distance between passenger groups is required. To implement our proposed sequences during real disembarkation, we propose an active information system that incorporates the aircraft cabin lighting system. Thus, the lights above each group member could be turned on when that passenger group is requested to disembark.
... Here, column-wise disembarkation was found to be more effective for narrow-body aircraft (Wald, Harmon, and Klabjan 2014). These two structured disembarkation strategies are analyzed in small-scale field trials applying inside-out (column-wise) and back-to-front (blockwise) strategies (Qiang, Jia, and Huang 2017), but in contrast to the prior simulation experiment (Qiang et al. 2016), no significant improvements of the disembarkation time could be demonstrated. ...
Article
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Passenger disembarkation takes place in the confined space of the aircraft cabin. Boarding can be regulated to a certain extent, but this does not apply to disembarking at the end of a flight. COVID-19 constraints require that cabin procedures not only be operationally efficient but also effectively reduce the risk of virus transmission to passengers. We have developed a new mathematical model that accounts for these conflicting goals. We used an already improved seat assignment for passenger groups (e.g., families or couples) and implemented a genetic algorithm that generates improved disembarkation sequences. Our use cases show a significant 40% reduction in disembarkation time when physical spacing between passenger groups is required to comply with pandemic regulations. To inform passenger groups about the disembarkation sequence, we propose to activate the cabin lights at the seats in a dedicated way. Thus, our developed methodology could already be applied to actual airline operations.
... Previous researchers investigated the pedestrian flows inside the aircraft cabin during deplaning, but most studies center on boarding/deplaning efficiency and cabin evacuation in emergencies. Some researchers have explored the pedestrian movement efficiency under non-emergency conditions by empirical data analysis (Ren, Zhou, & Xu, 2020;Ren & Xu, 2018;Schultz, 2018a;Steffen & Hotchkiss, 2012) while others used pedestrian flow models (e.g., social force (SF) model, cellular automaton (CA) model) to depict boarding/deplaning behavior (Fang, Lv, Jiang, Xu, & Song, 2016;Giitsidis, Dourvas, & Sirakoulis, 2017;Qiang, Jia, Xie, & Gao, 2014, Qiang et al., 2016Tang, Yang, Ou, Chen, & Huang, 2018;Zeineddine, 2017). It is possible to approach the passenger evacuation problem theoretically or by alternative experimentation to reflect the cabin conditions in infectious disease emergencies (Derjany et al., Derjany, & Namilae, 2018;Namilae, Derjany, Mubayi, Scotch, & Srinivasan, 2017). ...
Article
The virus 2019-nCoV rapidly crossed the globe in the first quarter of 2020, and the global civil aviation industry contributed to the spread of the virus. The aircraft deplaning process is one of the critical stages of the spread of infectious diseases and merits careful research accordingly. However, little effort has been made to tailor the civil aircraft deplaning process to the existence of patients with severe acute airborne disease. In this study, we explore a mixed patient-health pedestrian deplaning flow from a Boeing 737-300’s with a full economy-class layout as per the virus spread dynamics during the process. We develop feasible deplaning management strategies that can reduce the inflection risk to the healthy passengers during the deplaning process. We then quantitatively compare the deplaning process before and after adopting the proposed strategies. The numerical results show that the proposed strategies effectively reduce the risk of infection during the deplaning process but sacrifice deplaning efficiency. We assert that health outweighs efficiency, and find that the proposed strategy may thus have practical value and potentially be of use to administrators.
... In the context of deboarding, the seat interference disappears and only the interference of passengers in the aisle is important for an efficient process. Wald et al. (2014) provide a study of deplaning strategies using stochastic optimization methods, Qiang et al. (2016) use a cellular automaton approach and Miura and Nishinari (2017) employ a model using an ex-Gaussian distribution. ...
Article
Full-text available
Aircraft boarding is a process mainly impacted by the boarding sequence, individual passenger behavior and the amount of hand luggage. Whereas these aspects are widely addressed in scientific research and considered in operational improvements, the influence of infrastructural changes is only focused upon in the context of future aircraft design. The paper provides a comprehensive analysis of the innovative approach of a Side-Slip Seat, which allows passengers to pass each other during boarding. The seat holds the potential to reduce the boarding time by approx. 20%, even considering operational constraints, such as passenger conformance to the proposed boarding strategy. A validated stochastic boarding model is extended to analyze the impact of the Side-Slip Seat. The implementation of such fundamental change inside the aircraft cabin demands for adapted boarding strategies, in order to cover all the benefits that accompany this new dynamic seating approach. To reasonably identify efficient strategies, an evolutionary algorithm is used to systematically optimize boarding sequences. As a result, the evolutionary algorithm depicts that operationally relevant boarding strategies implementing the Side-Slip Seat should differentiate between the left and the right side of the aisle, instead of the current operationally preferred boarding from the back to the front.
... Extant studies commonly use the sum of seat interference time and aisle interference time as opposed to boarding time for computer simulation (Ren et al., 2016), discrete modeling (Van Landeghem and Beuselinck, 2002;Ferrari and Nagel, 2005;Qiang et al., 2014Qiang et al., , 2016, and continuous modeling (Tang et al., 2012a(Tang et al., , 2012b. For most strategies as shown in Fig. 10, the sum of the time of direct aisle interference and valid seat interference does not significantly differ from the boarding time. ...
... After 8 min, for 91% of the recorded flights deboarding is finished (this level was reached after 17 min for boarding, so deboarding is 53% faster than boarding). In the context of deboarding, the seat interference disappears and only the interference of passengers in the aisle is important for an efficient process [42,46]. A study of deplaning strategies [47] used stochastic optimization methods and assumed a deboarding time of between 9 and 4.8 min, depending on the structure of the deboarding procedure. ...
Article
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Efficient boarding procedures have to consider both operational constraints and the individual passenger behavior. In contrast to the aircraft handling processes of fueling, catering and cleaning, the boarding process is more driven by passengers than by airport or airline operators. This paper delivers a comprehensive set of operational data including classification of boarding times, passenger arrival times, times to store hand luggage, and passenger interactions in the aircraft cabin as a reliable basis for calibrating models for aircraft boarding. In this paper, a microscopic approach is used to model the passenger behavior, where the passenger movement is defined as a one-dimensional, stochastic, and time/space discrete transition process. This model is used to compare measurements from field trials of boarding procedures with simulation results and demonstrates a deviation smaller than 5%.
... During the last decades, many researchers have focused on the investigation of TASEP for its importance in understanding essential nonlinear dynamics and in formulating mathematical models extracted from real physical systems [5]. On the one hand, TASEP can be constructed as a basis for the models of traffic flow [8][9][10][11][12][13][14][15], intracellular processes (e.g., cellular traffic [16], protein synthesis [17], cell division [18] et al.), granular flow [19], chains of quantum dots [20], information flow [21], the lean production of CFRP airframe components [22], etc. On the other hand, various dynamical phenomena can be revealed from these models based on TASEP. ...
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The paper studies periodic two-dimensional exclusion processes constituted by multi-lane totally asymmetric simple exclusion processes with the effect of asymmetric lane-changing rates. Particles in lane i can move forward with a rate pi{p_i} or hop into the adjacent lane i1{i-1} (i+1{i+1}) with a rate ωiu\omega _i^u (ωid\omega _i^d). Complemented by Monte Carlo simulations, exact solutions have been derived. According to the detailed balance principle, two different cases ωi1d=ωiu\omega _{i - 1}^d = \omega _i^u and ωiu=ωi+1d\omega _i^u = \omega _{i + 1}^d are studied here. Dynamics of the system can be revealed by exact solutions, which can match well with simulation ones.
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The traditional method of relieving boarding congestion is to reduce aisle and seat conflicts by optimizing the boarding strategy. Here, we focus on another way of smoothing the passenger flow for a novel cabin installed with side-slip seats. Three aspects are discussed in this work. First, we explore the characteristics of fast boarding sequences that benefit most from side-slip seats using a simulated annealing algorithm. Second, we introduce three alternative strategies and evaluate their efficiencies using a realistic aircraft boarding model. The result shows that the boarding time could be largely reduced by adopting the new strategies. Sensitivity analyses also imply that side-slip seats are tolerable to the number of inexperienced passengers who are unfamiliar with the side-slip seats. Besides, the infection risk is also discussed as a function of ticket validation time at the check desk. Third, a boarding assistant system is designed to implement the proposed strategies.
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