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Small-scale trials on passenger microbehaviours during aircraft boarding and deplaning procedures
... The default nobags profile is described in Table 2. We apply space-specific modifiers (i.e., multipliers) to passenger free speed; for open "lobby" spaces (i.e., the wider areas in the region of the main exit), this takes the value 1.542, for aisles it takes the value 1.0, and for seat rows we use the value 0.71 (all modifier values are based on [22] noting the alarm and removing a seatbelt) and move to their assigned exit. The range of initial delay times was determined by combining "seatbelt unfasten" ...
... and "leave seat" timings taken from [22] (mean 4.4s, s.d. 1.52s, min 2s, max 16s). ...
... For the specific baggage collection experiments, we introduce an additional passenger characteristic profile, withbag, which has exactly the same attribute set as the nobags profile, only the Speed range is reduced to a uniform distribution between 0.419-1.916 m/s, as specified in [22]. The only major issue here is that we cannot spatially account for the items carried by passengers, as the software platform does not allow for coupled/carried objects. ...
Recent reports of emergency aircraft evacuations have highlighted an increasing tendency amongst evacuees to ignore clear safety warnings and to collect and carry personal items of baggage during egress. However, relatively little work has so far been done on quantifying the impact of such behaviour on the evacuation process. In this paper, we report the results of validated simulation experiments (using the Boeing 777 wide-body aircraft), which confirm that even a relatively low level of baggage collection can significantly delay evacuation. Our platform provides one possible framework for the investigation of processes and mitigation tactics to minimise the impact of baggage collection behaviour in future.
... The speed of passengers is restricted in the cabin, and the physiological limitations of personnel are not yet reached. Therefore, this article's setting of personnel speed is based on the distribution of a cabin evacuation experiment [51], as shown in Table 4, which presents that passengers' speed is not related to human physiological factors but related to luggage. ...
... Passengers' combined Ailse Movement[51]. ...
... Parameters setting for different scenarios[51]. ...
The irrational behaviors of passengers due to panic and anxiety during actual evacuations are challenging to be fully controlled by the crew. These behaviors may lead to the inefficiency of actual evacuation. This research builds a cabin evacuation model considering passengers’ luggage retrieval and overtaking behaviors based on cellular automata to improve the safety of aviation passengers.. The model introduces disaster levels to describe passengers’ anxiety and implements the “faster-is-slower” effect. Two possible overtaking routes are proposed, and we explored the effect of overtaking and retrieving luggage. The result shows that both overtaking and luggage retrieval negatively impact evacuation efficiency, and the impact of baggage retrieving is greater than overtaking. However, overtaking can essentially eliminate the influence of baggage retrieving. The effect of prohibiting irrational behaviors in different cabin compartments is analyzed to simulate crews’ guidance. The results show that the crew's enhanced guidance of the second part is the most effective.
... To answer this question, a series of assumptions have been made regarding passengers boarding, such as the passengers' movement inside the aircraft [13,14], passengers' personal characteristics [15][16][17], the presence or absence of passenger groups [18], the type and the quantity of the hand luggage [13,[17][18][19][20], the occurrence of boarding interferences-namely the situations in which either the passengers are blocking the aisle while loading luggage in the overhead compartment (also called aisle interference) or the passengers are interacting with other passengers already seated on the same row as their allocated seat, when they need to make space to allow the other passengers to occupy their allocated seats (known as type-1, type-2, type-3, or type-4 seat interferences-as presented later on in this paper) [16,18,[21][22][23]. In addition to these assumptions, some research papers have extracted data from field trials [24,25], which have been used in calibrating the models for comparing different boarding methods in terms of boarding time. The boarding time has been the performance metric employed in the pre-COVID-19 situations in which improvements of the classical boarding methods have been proposed in the scientific literature [13,[18][19][20]22,23,[26][27][28][29]. ...
... For comparing the considered airplane boarding methods, we created an agent-based model in NetLogo and calibrated it using the measurements made in the literature from field trials [24,25]. A narrow airplane, Airbus A320, with 30 rows and 6 seats per row is used in the simulations as suggested by [21,23,29,[35][36][37]. ...
... We assume that the airplane is occupied at its maximum capacity, being able to accommodate 180 passengers, as presented in Figure 1. in the case of COVID-19, when some airlines have not respected the imposed social distancing measures inside the aircraft-e.g., America Airlines, which has announced that their seats will be filled as much as they can in these times, not keeping the middle seats empty [9,10]. For comparing the considered airplane boarding methods, we created an agent-based model in NetLogo and calibrated it using the measurements made in the literature from field trials [24,25]. A narrow airplane, Airbus A320, with 30 rows and 6 seats per row is used in the simulations as suggested by [21,23,29,[35][36][37]. ...
The COVID-19 pandemic has produced changes in the entire aviation industry, including adjustments by airlines to keep the middle seats of airplanes empty to reduce the risk of disease spread. In this context, the scientific literature has introduced new metrics related to passengers’ health when comparing airplane boarding methods in addition to the previous objective of minimizing boarding time. As the pandemic concludes and the aviation industry returns to the pre-pandemic situation, we leverage what we learned during the pandemic to reduce the health risk to passengers when they are not social distancing. In this paper, we examine the performance of classical airplane boarding methods in normal times but while considering the health metrics established during the pandemic and new metrics related to passenger health in the absence of social distancing. In addition to being helpful in normal times, the analysis may be particularly helpful in situations when people think everything is normal but an epidemic has begun prior to being acknowledged by the medical scientific community. The reverse pyramid boarding method provides favorable values for most health metrics in this context while also minimizing the time to complete boarding of the airplane.
... A. Review of state of the art Comprehensive overviews are provided for passenger boarding research [6][7][8] and aircraft ground operations [9]. Only a few aircraft boarding and disembarkation tests have been conducted to provide data for the calibration of input parameters and validation of simulation results: using a mock Boeing 757 fuselage [10], time to store hand luggage items in the overhead compartments [11], small-scale laboratory tests [12], evaluation of passenger perceptions during boarding and disembarkation [13], operational data and passenger data from field trial measurements [14], field trials for real-time seat allocation in connected aircraft cabin [15], and using a B737-800 mock-up (1/3 size) to explore the factors affecting the time of luggage storage [16]. Although these field data are used for simulation experiments, they only cover regular behavior in a pre-pandemic situation. ...
... x i j kh , ∀i, j, k, h (11) p kh + p k h − 1 ≤ u kk hh , ∀k, k , h, h (12) q ijkh ≥ h + λ ij + 500(x ijkh − 1) , ∀i, j, k, h (13) q ijkh ≤ 500x ijkh , ∀i, j, k, h (14) In addition, constraints (10)- (11) guarantee that all members of each group leave their place in the same period. To calculate the decision variables for the shedding rates of two different groups, we define the constraint (12), which is implemented in the transmission risk function. ...
... x i j kh , ∀i, j, k, h (11) p kh + p k h − 1 ≤ u kk hh , ∀k, k , h, h (12) q ijkh ≥ h + λ ij + 500(x ijkh − 1) , ∀i, j, k, h (13) q ijkh ≤ 500x ijkh , ∀i, j, k, h (14) In addition, constraints (10)- (11) guarantee that all members of each group leave their place in the same period. To calculate the decision variables for the shedding rates of two different groups, we define the constraint (12), which is implemented in the transmission risk function. The constraints (13)-(14) represent the disembarkation time of each passenger in each group sitting in row i and column j, and the corresponding decision variable takes the value of zero if the seat was not occupied. ...
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.
... To model the boarding process, researchers have considered a number of factors including: airplane characteristics, [11]- [15], airplane occupancy [2], [9], [11], [12], [16]- [18], passenger movement [19], [20], passengers' personal characteristics [9], [15], [16], group behavior [1], [21]- [23], seat selection [13], [20], the presence and type of the carry-on hand luggage [11], [16], [19], [22], [24], boarding interferences [9], [10], [14], [22], [25]. Some other studies have focused on extracting data from the field [9], [12], [15], [26], [27],so much needed in testing, calibrating and validating the proposed approaches. ...
... Decision variables X gb 1 if group g is assigned to bus b; 0 otherwise; X is a binary variable; S r Amount short of TARGET r for row r of the first apron bus; E r Amount in excess of TARGET r for row r of the first apron bus; F Amount that the number of passengers in the first half of the airplane (rows 1-15) assigned to the first bus is more than the number of passengers in the rear half of the airplane (rows [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] that are assigned to the first bus; Z Amount that the number of passengers in the first half of the airplane (rows 1-15) assigned to the first bus is less than the number of passengers in the rear half of the airplane (rows [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] that are assigned to the first bus; ...
... Decision variables X gb 1 if group g is assigned to bus b; 0 otherwise; X is a binary variable; S r Amount short of TARGET r for row r of the first apron bus; E r Amount in excess of TARGET r for row r of the first apron bus; F Amount that the number of passengers in the first half of the airplane (rows 1-15) assigned to the first bus is more than the number of passengers in the rear half of the airplane (rows [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] that are assigned to the first bus; Z Amount that the number of passengers in the first half of the airplane (rows 1-15) assigned to the first bus is less than the number of passengers in the rear half of the airplane (rows [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] that are assigned to the first bus; ...
This paper proposes a method for reducing the time to complete the boarding of a two-door airplane when its passengers are transported from the airport terminal to the airplane using two apron buses. In contrast to other methods that assign passengers to apron buses, our method considers groups of passengers traveling together (e.g. families). In particular, we propose a mixed integer programming (MIP) model that assigns each group of passengers (including each single-passenger group) to one of the two apron buses based on their seating assignments. We assume that all seats on the apron buses and the two-door airplane are occupied. We conduct stochastic simulation experiments with the proposed MIP-based method and with a baseline method that assigns groups of passengers with seats furthest from one of the airplane doors to the first apron bus and assigns remaining groups to the second apron bus. Numerical results indicate that the proposed MIP-based method reduces the boarding time by up to 27.31% when compared with the baseline approach.
... This is due to a lack of data exchange and the commercial sensitivity of data of organizations such as aircraft operators or manufacturers. Gwynne et al. call for data to be published and broadly available to better understand and quantify forthcoming challenges [32]. ...
... A wider seat pitch [54] reduces the time to stow and collect baggage underneath as well as the time to access and leave the seat. On the contrary, it reduces capacity [32]. Additionally, foldable seats [3] would also allow for more manoeuvring space when sowing luggage [25]. ...
Rising air travel demand, airport capacity issues, and schedule disruptions form part of the challenges that aviation stakeholders have to face in the upcoming decades. Minimizing ground times is one of their recent objectives as extended ground times induce operational, economic, and environmental risks. The flow of ground operations has a high impact on the overall air transportation system. Therefore, the impact and risks of extended ground times in passenger air transport were thoroughly compared, weighed, and compared based on pre-selected individual literature sources. Several studies deliver solution approaches to reduce ground times. The turnaround especially is a key element of any flight operation and impacts the competitive advantage of airlines and airports. Next to infrastructural changes, technological advancements, and operational performance improvements, the cooperation of stakeholders is a measure to shorten ground times. Special focus lies on the improvement of boarding procedures. They are essential for passenger air transport and reducing ground times.
... Data from small-scale laboratory tests (cf. Gwynne et al., 2018) or field measurement campaigns (Schultz, 2018a) only provide input to calibrate models for simulation of aircraft boarding. Therefore, a developed and validated stochastic boarding model (Schultz, 2018b) is used to provide a comprehensive set of data from inside the aircraft cabin (Schultz, 2017c). ...
... Kierzkowski and Kisiel (2017) provide an analysis covering the time needed to place items in the overhead bins depending on the availability of seats and occupancy of the aircraft. Gwynne et al. (2018) perform a series of small-scale laboratory tests to help quantify individual passenger boarding and deplaning movement considering seat pitch, hand luggage items, and instructions for passengers. Schultz (2017b) 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. ...
Reliable and predictable ground operations are essential for punctual air traffic movements. Uncertainties in the airborne phase have significantly less impact on flight punctuality than deviations in aircraft ground operations. The ground trajectory of an aircraft primarily consists of the handling processes at the stand, defined as the aircraft turnaround, which are mainly controlled by operational experts. Only the aircraft boarding, which is on the critical path of the turnaround, is driven by the passengers' experience and willingness or ability to follow the proposed procedures. We used a recurrent neural network approach to predict the progress of a running boarding event. In particular, we implemented and trained the Long Short-Term Memory model. Since no operational data of the specific passenger behavior is available, we used a reliable, validated boarding simulation environment to provide data about the aircraft boarding events. First predictions show that uni-variate input (seat load progress) produces insufficient results, so we consider expected passenger interactions in the aircraft cabin as well. These interactions are aggregated to a prior-developed complexity metric and allow an efficient evaluation of the current boarding progress. With this multi-variate input, our Long Short-Term Memory model achieves appropriate prediction results for the boarding progress.
... This approach eliminates delays caused by seated passengers leaving their seats to make room for other passengers to sit down. A number of researchers have recently used stochastic simulation [15][16][17][18][19][20][21][22] and field tests [23][24][25][26][27] to compare the performance of boarding strategies. Schultz [28] estimates the improved boarding performance resulting from a "slip seat" configuration that enables aisle seats to temporarily move closer to the windows, thereby extending the aisle width, permitting passengers to pass others waiting ahead of them in the aisle. ...
... These boarding times are averaged for each scenario (and for the prior method) for each average number of bags case in Table 3. For a given row of Table 3, the percentage improvement in the average time to board, using the proposed method, is calculated using Equation (24). ...
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.
... In the context of input data for boarding models, there are only limited datasets available to provide reliable input for boarding models. These datasets are from experimental mock-ups [38], observations during boarding operations [39,40], and small scale experiments [41,42]. Therefore, this ...
... The regular grid consists of equal cells with a size of 0.4 m × 0.4 m, whereas a cell can either be free or contain exactly one passenger. observations during boarding operations [39,40], and small scale experiments [41,42]. Therefore, this paper provides a reliable dataset for calibrating models for aircraft boarding and covers a broad range of input factors. ...
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%.
... However, setting up an actual aircraft accident experiment is expensive, inflexible in attribute variation, and dangerous to participants. Although some researchers have set up small-scale trials on passenger micro behaviors during aircraft boarding and deplaning procedures (Gwynne et al., 2018), people's reaction in emergencies is still hard to obtain in field experiments. Another challenge is that actual observations obtained from real-world emergency contexts that can serve as modeling benchmarks are extremely rare (Haghani et al., 2014;Haghani and Sarvi, 2016;Shahhoseini et al., 2016;Xu and Witlox, 2022). ...
... Comprehensive overviews are provided for passenger boarding research (Schultz 2018c;Delcea, Cotfas, and Paun 2018;Jaehn and Neumann 2015) and aircraft ground operations (Schmidt 2017). Only a few aircraft boarding and disembarkation tests have been conducted to provide data for the calibration of input parameters and validation of simulation results: using a mock Boeing 757 fuselage (Steffen and Hotchkiss 2012), time to store hand luggage items in the overhead compartments (Kierzkowski and Kisiel 2017), small-scale laboratory tests (Gwynne et al. 2018), evaluation of passenger perceptions during boarding and disembarkation (Miura and Nishinari 2017), operational data and passenger data from field trial measurements (Schultz 2018b), field trials for real-time seat allocation in connected aircraft cabin (Schultz 2018a), and using a B737-800 mock-up (1/3 size) to explore the factors affecting the time of luggage storage (Ren, Zhou, and Xu 2020a). Although these field data are used for simulation experiments, they only cover regular behavior in a pre-pandemic situation. ...
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.
... Airbus and Boeing) can be considered, passengers boarding and deboarding operations need a different approach, since the large variance of their behaviour. A wide range of works on this aspect confirms the issues of simulating/evaluating boarding and deboarding phases (Gwynne et al., 2018;Qiang et al., 2014) in the turnaround process and the consequent TAT estimation. ...
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.
... Airbus and Boeing) can be considered, passengers boarding and deboarding operations need a different approach, since the large variance of their behaviour. A wide range of works on this aspect confirms the issues of simulating/evaluating boarding and deboarding phases (Qiang et al., 2014;Gwynne et al., 2018) in the turnaround process and the consequent TAT estimation. ...
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.
... Notomista et al. (2016) allocated seats to passengers only after they cross the boarding gate, based on the person's speed and size of hand luggage, to achieve a significant decrease in the boarding time. Gwynne et al. (2018), through a series of laboratory trials, found that luggage and seat pitch had a notable impact on the overall boarding speed. Schultz (2018b) showed that a slight reduction of hand luggage per passenger can significantly increase the boarding speed. ...
The quest for efficient aircraft boarding strategies continues to generate lots of business and scientific discussions.
Boarding strategies define rules and procedures aimed to reduce boarding time and operational cost. Most
of the proposed strategies do not account for passengers’ non-compliance with boarding rules. Non-compliance is
one of the major non-deterministic problems that can degrade any performance improvement to be expected
from adopting a boarding strategy. To that, it is of paramount interest to shed light on this problem and introduce
approaches for mitigating any related performance degradation in the boarding process. Although some recent
research investigations considered the effect of non-compliance on the overall boarding time under different
strategies, there was a lack of remedial actions. This paper dissects the operational characteristics of the noncompliance
activity, proposes two different intervention approaches to deal with non-complying passengers,
and analyzes the resulting impact under different categories of boarding strategies using a cellular-automaton based
simulation.
... Notomista et al. (2016) allocated seats to passengers only after they cross the boarding gate, based on the person's speed and size of hand luggage, to achieve a significant decrease in the boarding time. Gwynne et al. (2018), through a series of laboratory trials, found that luggage and seat pitch had a notable impact on the overall boarding speed. Schultz (2018b) showed that a slight reduction of hand luggage per passenger can significantly increase the boarding speed. ...
The quest for efficient aircraft boarding strategies continues to generate lots of business and scientific discussions. Boarding strategies define rules and procedures aimed to reduce boarding time and operational cost. Most of the proposed strategies do not account for passengers’ non-compliance with boarding rules. Non-compliance is one of the major non-deterministic problems that can degrade any performance improvement to be expected from adopting a boarding strategy. To that, it is of paramount interest to shed light on this problem and introduce approaches for mitigating any related performance degradation in the boarding process. Although some recent research investigations considered the effect of non-compliance on the overall boarding time under different strategies, there was a lack of remedial actions. This paper dissects the operational characteristics of the non-compliance activity, proposes two different intervention approaches to deal with non-complying passengers, and analyzes the resulting impact under different categories of boarding strategies using a cellular-automaton-based simulation.
... The impact of different aircraft cabin layouts on passenger boarding were focused on the following studies: aircraft interior design (seat pitch and passengers per row) (Bachmat et al., 2009), aircraft seating allocation and alternative designs single and twin-aisle configuration Chung, 2012), impact of aircraft cabin modifications (Fuchte, 2014), novel aircraft configurations and seating concepts (Schmidt et al., 2015(Schmidt et al., , 2017, and dynamic change of the cabin infrastructure (Schultz, 2017b). Only a few experimental tests have been conducted to provide data for the calibration of input parameters and validation of simulation results: using a mock Boeing 757 fuselage (Steffen and Hotchkiss, 2012), time to store hand luggage items in the overhead compartments (Kierzkowski and Kisiel, 2017), small-scale laboratory tests (Gwynne et al., 2018), evaluation of passenger perceptions during boarding/deboarding (Miura and Nishinari, 2017), operational data and passenger data from field trial measurements (Schultz, 2017a(Schultz, , 2018b, field trials for real-time seat allocation in connected aircraft cabin (Schultz, 2018a), and using a B737-800 mock-up (1/3 size) to explore the factors affecting the time of luggage storage . ...
The corona pandemic significantly changes the processes of aircraft and passenger handling at the airport. In our contribution, we focus on the time-critical process of aircraft boarding, where regulations regarding physical distances between passengers will significantly increase boarding time. The passenger behavior is implemented in a field-validated stochastic cellular automata model, which is extended by a module to evaluate the transmission risk. We propose an improved boarding process by considering that most of the passengers are travel together and should be boarded and seated as a group. The NP-hard seat allocation of groups with minimized individual interactions between groups is solved with a genetic algorithm. Then, the improved seat allocation is used to derive an associated boarding sequence aiming at both short boarding times and low risk of virus transmission. Our results show that the consideration of groups will significantly contribute to a faster boarding (reduction of time by about 60%) and less transmission risk (reduced by 85%) compared to the standard random boarding procedures applied in the pandemic scenario.
... As for methods proposed in the literature, a series of elements have been considered to allow their testing in similar conditions to those encountered practice including: airplane characteristics [1], [20], [25]- [27], airplane occupancy [21], [23], [25], [26], [28]- [30], passengers movement [17], [18], passengers' personal characteristics [27]- [29], number and size of the hand luggage [18], [25], [29], [31], [32], time to store the luggage in the overhead compartment [33], [34], the presence of jet-bridges [35]- [39], the use of apron buses for passengers transport between the airport terminal and the airplane [34], [40]- [43], the occurrence of interferences between passengers either while proceeding down aisle or because of needing to depart a seat to clear space for a later boarding passenger assigned a seat closer to the window [1], [24], [28], [32], [44]. Other studies in the research literature focus on improving boarding methods [1], [18], [23], [25], [31], [32], [36], [44]- [46] and on conducting field trials to estimate data to be used in computer simulations [21], [47], [48]. ...
Airlines have recently instituted practices to reduce the risk of their passengers becoming infected with the novel coronavirus (SARS-CoV-2). Some airlines block their airplanes’ middle seats to preserve social distancing among seated passengers. In this context, we present six new boarding methods and compare their performance with that of the two best boarding methods used to date with social distancing. We evaluate the eight boarding methods using three performance metrics related to passenger health and one operational metric (airplane boarding time) for a one-door airplane. The three health metrics reflect the risks of virus spread by passengers through the air and surfaces (e.g. headrests and seat arms) and consider the amount of aisle social distancing between adjacent boarding passengers walking towards their seats. For an airline that highly values the avoidance of window seat risk, the best method to use is one of the new methods: back-to-front by row – WilMA, though it will result in a longer time to complete boarding of the airplane. Airlines placing greater emphasis on fast boarding times— while still providing favorable values for the health metrics—will be best served by using new methods back-to-front by row – WilMA – offset 2 and – offset 3 when aisle social distancing is 1 m and 2 m respectively.
... An important part of the scientific literature is dedicated to extracting data from field trials to use it for testing and comparing the developed airplane boarding methods. The field trials have featured small-scaled trials with participants ranging between 36 and 600 persons [36], [39], [46], [47]. ...
Social distancing reduces the risk of people becoming infected with the novel coronavirus (SARS-CoV-2). When passengers are transported from an airport terminal to an airplane using apron buses, safe social distancing during pandemic times reduces the capacity of the apron buses and has led to the practice of airlines keeping the middle seats of the airplanes unoccupied. This paper adapts classical boarding methods so that they may be used with social distancing and apron buses. We conduct stochastic simulation experiments to assess nine adaptations of boarding methods according to four performance metrics. Three of the metrics are related to the risk of the virus spreading to passengers during boarding. The fourth metric is the time to complete boarding of the two-door airplane when apron bus transport passengers to the airplane. Our experiments assume that passengers advancing to their airplane seats are separated by an aisle social distance of 1 m or 2 m. Numerical results indicate that the three variations (adaptations) of the Reverse pyramid method are the best candidates for airlines to consider in this socially distanced context. The particular adaptation to use depends on an airline’s relative preference for having short boarding times versus a reduced risk of later boarding passengers passing (and thereby possibly infecting) previously seated window seat passengers. If an airline considers the latter risk to be unimportant, then the Reverse pyramid – Spread method would be the best choice because it provides the fastest time to board the airplane and is tied for the best values for the other two health risk measures.
... Furthermore, it is possible that the limited set of volunteers led to a learning curve effect, which is why the authors admit that their results might be systematically biased. Gwynne et al. (2018) carried out small-scale tests using a mock airplane and simulating the boarding procedure with 35 test persons. Their focus was on investigating and quantifying individual passenger movement depending on factors such as seat distance or carry-on baggage. ...
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.
... The impact of different aircraft cabin layouts on passenger boarding were focused on the following studies: aircraft interior design (seat pitch and passengers per row) [46], aircraft seating layouts and alternative designs single and twin-aisle configuration [47,48], impact of aircraft cabin modifications [49], novel aircraft configurations and seating concepts [50,51], and dynamic change of the cabin infrastructure [52]. Only few experimental tests have been conducted to provide data for the calibration of input parameters and validation of simulation results: using a mock Boeing 757 fuselage [53], time to store hand luggage items in the overhead compartments [54], small-scale laboratory tests [55], evaluation of passenger perceptions during boarding/deboarding [56], operational data and passenger data from field trial measurements [57,58], field trials for real-time seat allocation in connected aircraft cabin [44], and using a B737-800 mock-up (1/3 size) to explore the factors effecting the time of luggage storage [59]. ...
We design an optimal group boarding method using a stochastic cellular automata model for passenger movements, which is extended by a virus transmission approach. Furthermore, a new mathematical model is developed to determine an appropriate seat layout for groups. The proposed seating layout is based on the idea that group members are allowed to have close contact and that groups should have a distance among each other. The sum of individual transmission rates is taken as the objective function to derive scenarios with a low level transmission risk. After the determination of an appropriate seat layout, the cellular automata is used to derive and evaluate a corresponding boarding sequence aiming at both short boarding times and low risk of virus transmission. We find that the consideration of groups in a pandemic scenario will significantly contribute to a faster boarding (reduction of time by about 60%) and less transmission risk (reduced by 85%), which reaches the level of boarding times in pre-pandemic scenarios.
... Only a few experimental tests were conducted to provide data for the calibration of input parameters and validation of simulation results, e.g., using a mock Boeing 757 fuselage [52], small-scale laboratory tests [53], or a field trial configuration to get real operational and passenger data [54]. Particular test setups were used to provide data for the time to store hand luggage items in the overhead compartments [55] or to evaluate passenger perceptions during boarding/deboarding [56]. ...
Air travel appears as particularly hazardous in a pandemic situation, since infected people can travel worldwide and could cause new breakouts in remote locations. The confined space conditions in the aircraft cabin necessitate a small physical distance between passengers and hence may boost virus transmissions. In our contribution, we implemented a transmission model in a virtual aircraft environment to evaluate the individual interactions between passengers during aircraft boarding and deboarding. Since no data for the transmission is currently available, we reasonably calibrated our model using a sample case from 2003. The simulation results show that standard boarding procedures create a substantial number of possible transmissions if a contagious passenger is present. The introduction of physical distances between passengers decreases the number of possible transmissions by approx. 75% for random boarding sequences, and could further decreased by more strict reduction of hand luggage items (less time for storage, compartment space is always available). If a second door is used for boarding and deboarding, the standard boarding times could be reached. Individual boarding strategies (by seat) could reduce the transmission potential to a minimum, but demand for complex pre-sorting of passengers. Our results also exhibit that deboarding consists of the highest transmission potential and only minor benefits from distance rules and hand luggage regulations.
... 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. ...
The boarding process is on the critical path of the turn-around. Reduction in boarding time can benefit airline carriers and airports and improve passenger satisfaction. However, aisle interference caused by passengers placing their luggage during boarding is a key factor leading to cabin congestion and low boarding efficiency. Therefore, the storage time for the carry-on luggage and its influencing factors is analyzed in this study. An experiment was conducted in a B737-800 model (1/3 size) to explore the factors effecting the time of luggage storage, and a new effective model of luggage storage time is proposed through a significance test and data fitting. The results show that the age of passengers, the type and quantity of luggage, and the existing luggage in the luggage bin have a significant impact on the luggage storage time; the rule of the variation in luggage placing time is similar between young adult passengers and middle aged passengers; the impact of the existing luggage in the overhead bin on the luggage storage time shows a stable trend in the initial period, but with the quantity of the luggage increasing to a certain point, the luggage storage time begins to increase sharply, which is known as a “jump”; and the luggage type has a great influence on the threshold value of jump. The results of the study can provide a reference for airlines to manage cabin luggage to improve boarding efficiency and improve passenger experience.
... However, setting up an actual aircraft accident experiment is expensive, inflexible in attribute variation, and dangerous to participants. Although some researchers have set up small-scale trials on passenger micro behaviors during aircraft boarding and deplaning procedures (Gwynne et al., 2018), people's reaction in emergencies is still hard to obtain in field experiments. Another challenge is that actual observations obtained from real-world emergency contexts that can serve as modeling benchmarks are extremely rare (Haghani et al., 2014;Haghani and Sarvi, 2016;Shahhoseini et al., 2016;Xu and Witlox, 2022). ...
Civil aviation navigation equipment system has many weaknesses, which easily causes serious problem to air transportation safety. This paper focuses on a support system for civil aviation navigation equipment security management. Firstly, a sustainability assessment platform was constructed to analysis and find out the weaknesses of equipment network. Next, one network expansion planning platform was built to improve the reliability and business continuity of the whole navigation system. Experiments were carried out based on these two platforms. Also, the equipment network of China’s eastern part was expanded based on the business continuity assessment. Results proved that the network business continuity and node efficiencies of new equipment network can satisfy the lowest requirement of economic consumption. Finally, the optimal network expansion planning method has been achieved, proving the effectiveness of the civil aviation navigation equipment security management support system.
... Other aspects considered in the studies within the field include, but are not limited to: passenger movement [14], [20], seat selection [3], [20], airplane characteristics, [3], [4], [12], [15], [21], airplane occupancy [12], [15], [16], [22]- [25], the presence and type of the carry-on hand luggage [11], [12], [14], [23], [26], boarding interferencespassengers blocked while waiting for other passengers to move out of their way- [4], [22], [26]- [28], passengers' personal characteristics [21]- [23], group behavior [26], [26], extracting data from the field [29], [30], while other studies focus on improving upon existing boarding methods to reduce the boarding time [1], [2], [4], [11], [12], [14], [16], [26], [28], [31]. ...
The use of apron buses for transporting passengers from the airport terminal to the airplane has become common practice for a series of airports worldwide. Airline companies have become increasingly aware of this practice and have added information to their boarding passes to suggest the airplane door passengers should use while boarding the airplane. In contrast, many of the literature’s methods to reduce boarding time assume the presence of a jet-bridge connecting the airplane to the terminal. These boarding methods are “by seat” and “by group” methods. The use of the apron buses for passengers’ transport limits the usage of these methods because, in most cases now, only two apron buses are needed for transporting the passengers. With two apron buses, boarding control is limited to deciding on which passengers to assign to each of the two buses. We propose 15 new methods that we tested against the previously published Back-to-front method adapted for the apron buses case, by considering 7 luggage situations. An agent-based model in NetLogo is created based on field trials and considerations made in the literature, and we used this model for simulations. Experimental results show that the best performing proposed methods combine aspects of the WilMA and Reverse Pyramid boarding methods adapted for apron buses. The best proposed method can reduce boarding time by up to 39.2% when compared to the benchmark Back-to-front method.
... Kierzkowski and Kisiel (2017) provide an analysis covering the time needed to place items in the overhead bins depending on the availability of seats and occupancy of the aircraft. Gwynne et al. (2018) perform a series of small-scale laboratory tests to help quantify individual passenger boarding and deplaning movement considering seat pitch, hand luggage items, and instructions for passengers. Schultz (2018b) 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. ...
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.
... Schultz [50] provides a comprehensive set of operational field trial 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. Gwynne et al. [51] perform a series of small-scale laboratory tests to help quantify individual passenger boarding and deplaning movement considering seat pitch, hand luggage items, and instructions for passengers. ...
We provide an overview about the research done in the field of airport and airline operations with a specific focus on a fast, reliable and sustainable passenger boarding. The reliable prediction operational processes along the aircraft air-ground trajectory demands a comprehensive consideration of economic, environmental, and handling constraints of airlines and airports. In particular, the critical process of passenger boarding is driven by passengers’ ability to follow the proposed boarding procedures and is not controlled by operational experts. In this paper we implement and compare two individual-based approaches which cover both specific passenger behavior during boarding and operational airline constraints. Both models used similar input values, but exhibit different magnitudes in the benefit evaluation. Furthermore, we demonstrate that there are still unused potentials to further improve boarding progress by using innovative infrastructural adaptations inside the aircraft cabin.
... Steffen and Hotchkiss (2012) conducted an experimental comparison of boarding strategies in a mock Boeing 757 fuselage and indicated the optimized Steffen strategy effectively reduces boarding time. Gwynne et al. (2018) performed a series of small-scale laboratory tests to investigate three factors as follows: seat pitch, luggage, and instructions. They then examined the significant albeit complex effect of luggage and seat pitch on performance. ...
... The innovative approach to dynamically changing the cabin infrastructure through a Side-Slip Seat is evaluated [36]. Gwynne et al. [37] perform a series of small-scale laboratory tests to help quantify individual passenger boarding and deplaning movement considering seat pitch, hand luggage items, and instructions for passengers. Schultz [38] 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. ...
... Kierzkowski and Kisiel [45] provide an analysis covering the time needed to place items in the overhead bins depending on the availability of seats and occupancy of the aircraft. Gwynne et al. [46] perform a series of small-scale laboratory tests to help quantify individual passenger boarding and deplaning movement considering seat pitch, hand luggage items, and instructions for passengers. Schultz [47] 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. ...
Future 4D aircraft trajectories demand comprehensive consideration of environmental, economic, and operational constraints, as well as reliable prediction of all aircraft-related processes. Mutual interdependencies between airports result in system-wide, far-reaching effects in the air traffic network (reactionary delays). To comply with airline/airport challenges over the day of operations, a change to an air-to-air perspective is necessary, with a specific focus on the aircraft ground operations as major driver for airline punctuality. Aircraft ground trajectories primarily consists of handling processes at the stand (deboarding, catering, fueling, cleaning, boarding, unloading, loading), which are defined as the aircraft turnaround. Turnaround processes are mainly controlled by ground handling, airport, or airline staff, except the aircraft boarding, which is driven by passengers' experience and willingness/ability to follow the proposed boarding procedures. This paper provides an overview of the research done in the field of aircraft boarding and introduces a reliable, calibrated, and stochastic aircraft boarding model. The stochastic boarding model is implemented in a simulation environment to evaluate specific boarding scenarios using different boarding strategies and innovative technologies. Furthermore, the potential of a connected aircraft cabin as sensor network is emphasized, which could provide information on the current and future status of the boarding process.
Narrow seated spaces with multiple exits are prevalent structures in public buildings, underscoring the paramount importance of facilitating swift evacuation in such constrained environments. In this study, we first conducted evacuation experiments in a realistic narrow seated area. By manipulating different availability conditions for two exits located at the ends of the long aisle, we studied the effects of unpredictable exit failures, specifically, how the exit switch and explicit guidance influence the evacuation process. The movement characteristics are explored in several aspects, such as pre-evacuation time, aisle conflicts, speed, distance headway, evacuation time, and time lapse. We found that once people have encountered the exit failure condition, they would demonstrate enhanced preparedness in subsequent trials, leading to expedited exit switches. With explicit guidance, people would be less hesitant and move faster in the main aisle. The fine-grid cellular automata model is extended based on the experimental observations to verify its feasibility in simulating this process. Conflict resolution and turning behavior are incorporated for a more nuanced description. The effects of the exit switch are parameterized through the informed probability and the speed reduction.
When boarding an aircraft, it is often assumed that minimizing the total boarding time meets economic objectives and passenger satisfaction. However, there are indications that not only the total boarding time should be considered in order to satisfy passengers. In “Air passenger preferences: an international comparison affects boarding theory,” a large survey among airplane passengers, which was conducted in Germany, Israel, and the United States, confirms that a significant share of passengers prefers short individual boarding times.
Interestingly, if boarding is restricted to two boarding groups that differ by the passengers’ speed of taking their assigned seat (e.g., passengers with and without hand luggage), “slow-first” is best for minimizing the total boarding time, but “fast-first” is best for minimizing average individual boarding time. Thus, the paper presents a new boarding strategy called “slow-back-first,” where the resulting total boarding time and the resulting average individual boarding time are both close to their respective optimum.
It is difficult to observe people's actual evacuation behavior in case of a real aircraft accident. For one, luckily, because aircraft incidences have very low probabilities, and for another, because when faced with such extreme situations people often resort to very unexpected behavior. A way to obtain people’s responses to an airplane emergency is then to estimate people’s perceptions of the total evacuation time. In this paper, a stated preference analysis containing eight airplane evacuation attributes was carried out by nine hypothetical aircraft accident scenarios. The experiment adopted a fractional factorial design to reduce the survey size and obtained 192 effective responses. A cumulative odds ordinal logistic regression with proportional odds was performed and results showed the model has a good data fit. The following findings were revealed from this study. First, for the onboard safety briefings, the efficiency of safety broadcasting is better than crew demonstrations and safety cards, but the overall attention from passengers to the cabin safety announcements is still inadequate. Second, in passengers’ perception, the lack of crew guidance would slow the evacuation the most while more available exits reduce the evacuation time primarily. Third, being knowledgeable about and more experienced in flying has a significant effect in reducing people’s perception of evacuation time. Finally, higher self-reported levels in the ability to stay calm are associated with a shorter estimation of the evacuation time. These findings may help optimize the understanding of air passengers’ behavior in emergencies and improve the preparedness for aircraft emergency evacuation.
Commercial airlines are exposed to a highly competitive international market environment. Cost has to be reduced and efficiency has to be increased constantly. At the same time, customer satisfaction needs to be increased. Otherwise, the airline in question would face loss of market share. One area of improvement is the airplane boarding process, which has been subject to many simulation-based research projects resulting in significant reduction of boarding time. However, those models neglected the customer's wishes regarding sitting or boarding in groups. Using a simulation approach, this paper presents a model for a reduction of boarding time with consideration of customers' expectations. The achieved boarding times are found to be higher than previously reported minimum times, but show a boarding time reduction in comparison with conventional boarding strategies.
In this paper we address the prediction of aircraft boarding using a machine learning approach. Reliable process predictions of aircraft turnaround are an important element to further increase the punctuality of airline operations. In this context, aircraft turnaround is mainly controlled by operational experts, but the critical aircraft boarding is driven by the passengers’ experience and willingness or ability to follow the proposed procedures. Thus, we used a developed complexity metric to evaluate the actual boarding progress and a machine learning approach to predict the final boarding time during running operations. A validated passenger boarding model is used to provide reliable aircraft status data, since no operational data are available today. These data are aggregated to a time-based complexity value and used as input for our recurrent neural network approach for predicting the boarding progress. In particular we use a Long Short-Term Memory model to learn the dynamical passenger behavior over time with regards to the given complexity metric.
The topic of airplane boarding is receiving increasing attention in practice and in the scientific literature. Shorter boarding times can reduce the time an airplane spends at the gate (the airplane turn-around time), resulting in annual cost savings of several hundred thousand dollars per airplane. Although several researchers have analyzed the boarding process purely theoretically or with simulation models, little empirical research has been performed, even though empirical research is the basis for any theoretical or simulation model. In this paper, we provide the fundamentals for this research area by presenting the results of an empirical study conducted at a large European airport. The aim of this study is to determine whether and to what extent certain factors, such as the number of passengers, the capacity of the airplane, and the amount of carry-on baggage, influence boarding times. Boarding times and additional data for short- and medium-haul flights with single-aisle airplanes have been manually collected in a field study and analyzed. The analyses yield the counter-intuitive result that a significant effect on the boarding time of a flight by the average amount of carry-on baggage per passenger cannot be demonstrated. Finally, we develop a regression model to predict boarding times based on the number of passengers and the capacity of the airplane. This straightforward model explains more than 85% of the variance in the boarding time and could therefore easily be used in the daily business of an airline to estimate the expected boarding times per flight. Furthermore, we compare our regression model to various simulation and analytical models as well as other empirical data for validation and out-of-sample testing.
A computer simulation to verify occupant evacuation within 90 s during aircraft emergency can supply beneficial information for the full-scale evacuation experiment in the initial airworthiness certification of the advanced regional jet (ARJ) developed by China. Based on cellular automata and multi-agent theory, a civil aircraft cabin occupant emergency evacuation model (CACOEM) was established. In the model, considering their psychology in an emergency circumstance of aircraft, occupants were classified into different roles according to their distinctive features of behavior; four sub-models, i. e., civil aircraft cabin model, occupants' characteristics model, occupants' behavior model, and occupants' movement model were involved. In addition, simulation software CabinEvacu was developed and applied to the regional commercial aircrafts with 100 seats. According to the requirements on passenger age-sex proportion in Transport Aircraft Airworthiness Standards: Transport Category Airplanes (CCAR25-R4), 1000 times of occupant emergency evacuation simulations were made in a scenario where three hatches are opened in front, middle, and rear areas, respectively. The results show that the average evacuation time is 68.7 s, which is consistent with the result obtained by the evacuation test simulation and investigation algorithm (ETSIA). © 2016, Editorial Department of Journal of Southwest Jiaotong University. All right reserved.
Previous studies defined passengers' comfort based on their concerns during the flight and a set of eight experiential factors such as 'peace of mind', 'physical wellbeing', 'pleasure', etc. One Objective of this paper was to determine whether the factors underlying the passengers' experience of comfort differ from those of discomfort. Another objective was to cross-validate those factors. In the first study, respondents provided written reports of flight comfort and discomfort experiences separately and gave ratings on the impact of the eight factors on each experience. Follow up interviews were also conducted. Significant difference was found between comfort and discomfort ratings for two factors of 'pleasure', denoted by one's concern for stimulation, ambience and exceeded expectations, and 'physical wellbeing' characterized in terms of bodily support and energy. However, there were no significant differences between the comfort and discomfort ratings on the other six factors. The evidence does not support the proposition that passenger comfort and discomfort are underline by different sets of factors. It is therefore suggested that the evaluation of overall passenger comfort experience, as a whole, employ one spectrum ranging from extreme comfort to discomfort. In study two, a pool of comfort descriptors was collected. Those that were less relevant to passenger comfort were eliminated in a number of steps. Factor analysis was used to classify the remaining descriptors, using respondents' ratings on their potential impact on passenger comfort. Seven factors corresponded to the pre-determined passenger comfort factors from previous research, validating those with an exception of 'proxemics' (concerning one's privacy and control over their situation) but it was argued that this is due to the nature of the factor itself, which is context dependent and generally perceived unconsciously.
Study on civil aircraft emergency evacuation process by using of computer model is an effective way to validate and improve the evacuation performance of aircraft. In this paper, based on the characteristics of the aircraft structure and personnel evacuation, a finer-grid civil aircraft evacuation model (FGCAEM) is built. In this model, the effect of seat area, others and fire products on escape process is considered. Simulations reproduce typical characteristics of aircraft evacuation, such as the movement synchronization between adjacent pedestrians, route choice and so on. It is indicated that evacuation efficiency will be reduced significantly in case of fire, especially in the last period of the evacuation process. Results will be helpful for the design of security auxiliary equipment of airplane and promoting management procedure to emergency case.
In order to sustain profitable growth, it is crucially important for both airports and airlines to revise possibilities to reduce tournaround time, as one of the most significant factor that highly influence total cost of airlines and efficiency of airports. Although boarding time as a part of turnaround time is not the major contributor of delay of an airplane, it is evident that has more opportunity to be altered compared to other components in turnaround time set. In this paper we developed a simulation model that investigates different boarding patterns, in order to detect the most efficient one, from different players’ perspective, by taking into consideration mainly individual boarding times. The results are analyzed with regard to airline objectives as well as to customer objectives, and some of the implementation issues are also being considered.
One major business of civil aviation is to carry passengers between airports while providing good customer services at low costs. The turn time of an airplane, i.e. broadly speaking, the time that an airplane is on ground, is crucial for its utilisation and thus for the airline’s profitability. From this it follows, that the turn time needs to be as short as possible.
In this paper we analyse various actions (inside and outside the airplane) to reduce the boarding time and hence the turn time. These actions were investigated with a specifically developed simulation tool (the Airplane Boarding Simulator (ABS)), and cover the whole process from (and including) the gate until the passengers arrive at their seats.
The simulation model was calibrated by using video data from observations of eight boardings at Zurich airport. The primary goal was to determine the impact of the following factors on the boarding time: (i) number of pieces of hand luggage, (ii) pre-boarding area (and timing), (iii) boarding (seating) strategy inside the airplane, (iv) procedures at the gate desk (power-boarding, additional staff).
Based on the experiences on-site and the results of the simulations we found, that with a reduced number of pieces of hand luggage, the use of a pre-boarding area and an appropriate boarding (seating) strategy, a reduction of the boarding time of around four minutes for airplanes of similar size than the Airbus A321 is possible. Moreover, we outline feasible actions that could lead to further improvements. In any case, a good coordination of the actions taken is of crucial importance, together with an appropriate training of the staff (airplane crew and ground) and a clear and easy to understand information of the passengers.
Optimizing the boarding process is one way for the airline industry to reduce the cost of the total air plane turn time -i.e. the time between landing and take off. For this aim, boarding strategies that control when a passenger is allowed to board the plane are developed in order to reduce the overall boarding time. These strategies should be passenger friendly and robust to all kinds of disturbances. In this paper, boarding strategies are analyzed using multi-agent based simulation. Passengers are modelled as autonomous agents with particular individual characteristics. This allows us to introduce new strategies which are, unlike traditional boarding strategies, based on individual passengers' characteristics rather than on the location of their seats. We examine the robustness of these new and other common boarding strategies against realistic disturbances such as passengers compliance, group travel and transits. The effect of the latter two types of disturbance were not reported yet in literature. Our findings suggest that characteristic based strategies can combine high performance with low overhead.
We describe a new method to assign seats and to board passengers on an airplane that minimizes the total time to board. Steffen (2008) presents an optimum boarding method that assigns passengers to a specific numerical position in line that depends upon their ticketed seat location. Our method builds upon Steffen by assigning individual passengers to seats based on the amount of luggage they carry. Our heuristic method assigns passengers to seats so that their luggage is distributed evenly throughout the plane. Simulation results indicate that with our method, the total time to board all passengers on a fully loaded airplane is shorter than that of Steffen.
The purpose of this paper is to develop a new pedestrian-following model based on the properties of the aircraft boarding
process. The passengers’ motion trail, the number of interfaces, the total aircraft boarding time, the wasted time that is
resulted by the interfaces and the effective aircraft boarding time are investigated in detail. The numerical results illustrate
that the new model can qualitatively describe some dynamic properties of the aircraft boarding process.
By minimizing boarding time, commercial airlines can improve their on-time performance and increase their aircraft/crew utilization and thereby increase profitability. Herein, we present preliminary results from combining IP and a simulation model that suggest that structured group boarding can result in boarding time reductions.
The factors that control emergency evacuation from transport aircraft are many. The physical factors include the aircraft structure and the configuration of aircraft interior components such as aisles, seating arrangements, monument placements, and crewmember assist spaces. Information factors related to emergency evacuation include safety briefing cards and videos, signs, placards, emergency lighting and marking systems, and verbal briefings by the crew. Trained crewmembers perform the functions necessary to initiate and conduct emergency evacuations, providing passenger management functions intended to produce fast and effective evacuations.
We show that aeroplane boarding can be asymptotically modelled by two-dimensional Lorentzian geometry. Boarding time is given by the maximal proper time among curves in the model. Discrepancies between the model and simulation results are closely related to random matrix theory. The models can be used to explain why some commonly practised airline boarding policies are ineffective and even detrimental.
We develop a new model for studying the phenomenon of congestion in a transient environment, focusing on the problem of aircraft landings at a busy "hub" airport. Our model is based on a Markov/semi-Markov treatment of changes in the weather, the principal source of uncertainty governing service times, together with a treatment of the arrival stream as time-varying but deterministic. The model is employed to compute moments of queue length and waiting time via a recursive algorithm. To test the model, we conduct a case study using traffic and capacity data for Dallas-Fort Worth International Airport. Our results show that the model's estimates are reasonable, though substantial data difficulties make validation difficult. We explore, as examples of the model's potential usefulness, two policy questions: schedule interference between the two principal carriers, and the likely effects of demand smoothing policies on queueing delays.
This paper examines the influence of exit availability on evacuation time for narrow body aircraft under certification trial
conditions using computer simulation. A narrow body aircraft which has previously passed the certification trial is used as
the test configuration. While maintaining the certification requirement of 50% of the available exits, six different exit
configurations are examined. These include the standard certification configuration and five other exit configurations based
on commonly occurring exit combinations found in accidents. These configurations are based on data derived from the AASK database
and the evacuation simulations are performed using the airEXODUS evacuation software. The results show that the certification
practise of using half of the available exits predominately down one side of the aircraft is neither statistically relevant
nor challenging. For the aircraft cabin layout examined, the exit configuration used in certification trial produces the shortest
egress times. Furthermore, three of the six exit combinations investigated result in predicted egress times in excess of 90
seconds, suggesting that the aircraft would not satisfy the certification requirement under these conditions.
We report new results obtained using cellular automata for pedestrian dynamics with friction. Monte-Carlo simulations of evacuation processes are compared with experimental results on competitive behavior in emergency egress from an aircraft. In the model, the recently introduced concept of a friction parameter μ is used to distinguish between competitive and cooperative movement. However, an additional influence in competition is increased walking speed. Empirical results show that a critical door width wc separates two regimes: for w<wc, competition increases egress times, whereas for w>wc it leads to a decrease. This result is reproduced in the simulation only if both influences, walking speed and friction, are taken into account.
The increase in air travel puts tremendous strain on existing airport facilities, so turnaround times for airplanes are under constant pressure to be reduced. Part of the turnaround time consists of the time required for passengers to board the plane and install themselves in their assigned seats. It seems that this boarding time for passengers is much higher than allowed, but up to now has been largely neglected in reengineering projects. This paper investigates different boarding patterns, in order to detect to what extent boarding time can be reduced. Findings indicate quite some discrepancy between current practices and optimal patterns. The results are analyzed with regard to airline objectives as well as to customer objectives, and implementation issues are considered.
In September 2003, America West Airlines implemented a new aircraft boarding strategy that reduces the airline's average passenger boarding time by over two minutes, or approximately 20 percent, for full and nearly full flights. The strategy, developed by a team of Arizona State University and America West Airline's personnel, is a hybrid between traditional back-to-front boarding and outside-inside boarding used by other airlines. Field observations, numerical results of analytical models, and simulation studies provided information that resulted in an improved aircraft-boarding strategy termed reverse pyramid. With the new boarding strategy, passengers still have personal seat assignments, but rather than boarding by rows from the back to the front of the airplane, the), board in groups minimizing expected passenger interference in the airplane. The analytical, simulation, and implementation results obtained show that the method represents a significant improvement in terms of boarding time over traditional pure back-to-front, outside-inside boarding strategies.
Common wisdom is that airplanes make money only when they are in the air. Therefore, turnaround time (turn time) on the ground should be reduced as much as possible. An important contribution to the turn time is airplane boarding time. Many different schemes are in use, from random seat selection to sophisticated boarding groups. A simulation model is described to evaluate different boarding strategies. In contrast to earlier work, it puts special emphasis on disturbances, such as a certain number of passengers not following their boarding group but boarding earlier or later. A surprising result of this work is that the typical back-to-front boarding strategy becomes improved when passengers do not board with their assigned group. Other proposed strategies still consist of small numbers of boarding groups but are both faster and more robust with regard to disturbances.
In this paper, we focus on the need for reducing boarding time for airlines. Therefore existing researches devoted to designing boarding routines and studying boarding strategies in existence. A model based on cellular automata is developed for calculating the integrated boarding time and testifies that the Reverse-Pyramid way is one of the most effective strategies. Aiming at giving an optimal boarding strategy, this paper combines a new evaluating criterion with some further analysis of Reverse-Pyramid and finally concludes that Reverse-Pyramid strategy which is divided into 5 groups and has more groups with a particular proportion is the best. Somehow the present paper solves the neglect of passengers’ satisfaction and time spent on organizing before boarding in existing researches and gives some recommendations to airlines at last.
The present paper describes a new, agent-based computer model that can simulate the evacuation of narrow body transport aeroplanes in the conditions prescribed by the airworthiness regulations for certification. The input data are extracted from a complete plan view of the cabin. The results include full egress details of all occupants, passengers and crew-members, and the most significant evacuation figures and diagrams. The model has been tuned and verified with real data of narrow body certification demonstrations. Numerical simulations of six narrow body aircraft, representative of current designs, show the capabilities of the model and provide relevant information on the relationship between cabin features and emergency evacuation results. Although the computer model has been developed for helping in the certification process it would be useful too in the design of new cabins.
Studying civil aircraft emergency evacuation process by using computer model is an effective way. In this study, the evacuation of Airbus A380 is simulated using a Finer-Grid Civil Aircraft Evacuation (FGCAE) model. In this model, the effect of seat area and others on escape process and pedestrian’s “hesitation” before leaving exits are considered, and an optimized rule of exit choice is defined. Simulations reproduce typical characteristics of aircraft evacuation, such as the movement synchronization between adjacent pedestrians, route choice and so on, and indicate that evacuation efficiency will be determined by pedestrian‘s “preference” and “hesitation”. Based on the model, an assessment procedure of aircraft evacuation safety is presented. The assessment and comparison with the actual evacuation test demonstrate that the available exit setting of “one exit from each exit pair” used by practical demonstration test is not the worst scenario. The half exits of one end of the cabin are all unavailable is the worst one, that should be paid more attention to, and even be adopted in the certification test. The model and method presented in this study could be useful for assessing, validating and improving the evacuation performance of aircraft.
The exits which passengers select in evacuation situations and the exits which are available post-crash is of great interest to aviation safety regulators who make rulings defining exit separation and aircraft evacuation certification, aircraft designers who develop the interior layout of aircraft cabins and position exits within the fuselage, cabin safety specialists who develop procedures for managing aircraft evacuation and cabin crew who must control aircraft evacuations. In this paper we examine issues associated with passenger exit selection behaviour and exit configurations frequently experienced during survivable crashes. This work makes use of the latest version of the Aircraft Accident Statistics and Knowledge database AASK V4.0. which contains information from 105 survivable crashes and over 2,000 survivors.
Conducting a real aircraft evacuation trial is oftentimes unaffordable as it is extremely expensive and may cause severe injury to participants. Simulation models as an alternative have been used to overcome the aforementioned issues in recent years. This paper proposes a new simulation model for emergency evacuation of civil aircraft. Its unique features and advantages over the existing models are twofold: (1) passengers' critical physical characteristics, e.g. waist size, gender, age, and disabilities, which impact the movement and egress time of individual evacuee from a statistical viewpoint, are taken into account in the new model. (2) Improvements are made to enhance the accuracy of the simulation model from three aspects. First, the staggered mesh discretization method together with the agent-based approach is utilized to simulate movements of individual passengers in an emergency evacuation process. Second, each node discretized to represent cabin space in the new model can contain more than one passenger if they are moving in the same direction. Finally, each individual passenger is able to change his/her evacuation route in a real-time manner based upon the distance from the current position to the target exit and the queue length. The effectiveness of the proposed simulation model is demonstrated on Boeing 767-300 aircraft.
Aircraft boarding is a very complex process. In this paper, we propose a new aircraft boarding model with consideration of passengers' individual properties. The model is then applied to explore the dynamic properties of passengers' motions under three different aircraft boarding strategies including the random boarding strategy, the boarding strategy based on passenger's seat serial number and individual properties. Our numerical results illustrate that overtaking, queue-jumping, seat conflict congestions and jams may occur under the first two boarding strategies, but these phenomena do not occur under the third boarding strategy. The results indicate that the third boarding strategy is more effective than the other two boarding strategies.
This study used queuing networks and discrete event simulation (DES) to investigate the effects of baggage volume and alarm rate at the security screening checkpoint (SSCP) of a small origin and destination airport. A queuing network was applied for theoretical modeling of the SSCP performance, and a DES model using Arena Version 12 was used for an empirical approach. Data were collected from both literature and by manual collection during the peak operating time of the airport that was modeled. The simulation model was verified and validated qualitatively and quantitatively by statistical testing before experimentation. After validation, a sensitivity analysis was performed on baggage volume of passengers (PAX) and the alarm rate of baggage screening devices, where SSCP throughput and PAX cycle time, were the dependent measures. The theoretical queuing network proved an accurate method of predicting cycle time for the system while in steady state but was subject to various assumptions. The empirical model and sensitivity analysis showed that SSCP throughput and cycle time are both highly sensitive to alarm rate. Additionally, the sensitivity analysis showed that SSCP throughput was completely resilient to baggage volume, while cycle time was moderately sensitive to baggage volume. Practical implications and future research were also discussed.
A fluid approximation model for the simulation of passenger terminals is described. It is implemented via a specially designed, high-level, passenger-terminal simulation language, TERMSIM, which is Pascal-based. TERMSIM uses three broad groups of terminal submodels: processors (such as check-in and security), storage (such as ancillary services and hold rooms), and circulation components (such as corridors). The TERMSIM language consists of seven terminal-component names, three flow-control unit names, and six command statements allowing a terminal designer to create a representation of a terminal very quickly. Terminal operations are described by the number of passengers arriving, being served and queuing at the various terminal facilities. The structure of the model is described along with the mechanics underlying some of the terminal-component models and representative parameter magnitudes required by these models. The modeling components of TERMSIM are structured in a modular way allowing the mechanics underlying each model to be rewritten and inserted into the program. A simple example is used to illustrate the programming language, and the capabilities of the model are illustrated.
This paper presents the results obtained with a new agent-based computer model that can simulate the evacuation of narrow-body transport airplanes in the conditions prescribed by the airworthiness regulations for certification. The model, described in detail in a former paper, has been verified with real data of narrow-body certification demonstrations. Numerical simulations of around 20 narrow-body aircraft, representative of current designs in various market segments, show the capabilities of the model and provide relevant information on the relationship between cabin features and emergency evacuation. The longitudinal location of emergency exits seems to be even more important than their size or the overall margin with respect to the prescribed number and type of exits indicated by the airworthiness requirements. Copyright © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
The evacuation behavior of passengers was formulated as an autonomous agent and multi-agent model (AAMAS) evolving over a two-dimensional grid cell that represents aircraft cabins and passengers. In this model, the autonomous agents are initially placed in seat squares and move toward an emergency exit after an aircraft accident occurs. The autonomous agent mimics the behavior of passengers in the cabin, who must not only view their surroundings to collect the useful information but also select a route to an emergency exit. As the situation evolves, the agents feel the mental stress or strong fear or anxiety; thereby reacting unfavorably in the situation that they panic at. This abnormal evacuation behavior of panic agents generates time delays in the evacuation flow towards the exits. Therefore, such panic and its effect on evacuation behavior should be considered as an important factor in evacuation simulations. In this paper, it is supposed that the level of panic depends on three factors: remaining time, frequency of waiting and the difficulty of finding an exit. The dependencies of these factors on the time needed to complete an evacuation and the number of the panic agents in the aircraft were determined by the simulation. Considering the simulation results and situations of the actual aircraft accident “Garuda Indonesia Airways Accident”, it was possible to develop aircraft evacuation scenarios that considered passenger emotions.
The airline industry is under intense competition to simultaneously increase efficiency and satisfaction for passengers and profitability and internal system benefit for itself. The boarding process is one way to achieve these objectives as it tends itself to adaptive changes. In order to increase the flying time of a plane, commercial airlines try to minimize the boarding time, which is one of the most lengthy parts of a plane’s turn time. To reduce boarding time, it is thus necessary to minimize the number of interferences between passengers by controlling the order in which they get onto the plane through a boarding policy. Here, we determine the passenger boarding problem and examine the different kinds of passenger boarding strategies and boarding interferences in a single aisle aircraft. We offer a new integer linear programming approach to reduce the passenger boarding time. A genetic algorithm is used to solve this problem. Numerical results show effectiveness of the proposed algorithm.
Common wisdom is that airplanes make money only when they are in the air. Therefore, turnaround time (turn time) on the ground should be reduced as much as possible. An important contribution to the turn time is airplane boarding time. Many different schemes are in use, from random seat selection to sophisticated boarding groups. A simulation model is described to evaluate different boarding strategies. In contrast to earlier work, it puts special emphasis on disturbances, such as a certain number of passengers not following their boarding group but boarding earlier or later. A surprising result of this work is that the typical back-to-front boarding strategy becomes improved when passengers do not board with then- assigned group. Other proposed strategies still consist of small numbers of boarding groups but are both faster and more robust with regard to disturbances.
The factors influencing survival in aircraft accidents can be classified into configurational, environmental, procedural or behavioural. New methodologies which have been developed in order to simulate emergency behaviour are introduced. A series of experimental programmes in which the new behavioural techniques are applied to configurational, environmental and procedural changes in the cabin are described. The results suggest that the techniques provide the behavioural and statistical data required for the assessment of design options or safety procedures for use in aircraft emergencies.
There has been increasing interest in developing simulation models capable of analyzing commer cial aircraft-cabin egress under both non-life- threatening and life-threatening scenarios. At issue is the ability to accurately simulate human behavior within non-toxic environments, as well as the debilitating effects that toxic environments (e.g., fire and smoke) have on human-decision making. A set of criteria has been identified by the Federal Aviation Administration for developing simulation models capable of analyzing commer cial aircraft-cabin egress. These criteria are used to (a) compare the capabilities and limitations of four aircraft-evacuation models in existence to day, (b) identify the issues that need to be ad dressed when developing these types of models, and (c) propose a new paradigm for developing aircraft-cabin egress models.
The airline industry is currently under intense pressure to simultaneously increase efficiency, customer satisfaction, and profitability. The boarding process is one way to achieve this objective as it lends itself to adaptive changes. The purpose of this paper is to determine the most cost-effective way to board passengers and still maintain quality and customer satisfaction. We conclude that the best strategy is to use a non-traditional methodology of outside-in or some modification thereof. The findings suggest that airline managers should consider issues related to evenly distributing boarding activity throughout the aircraft, developing more effective policies for managing carry-on luggage, and using simultaneous loading through two doors.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1973.
This document reviews the history and current status of computer models of the evacuation of an airliner cabin. Basic concepts upon which evacuation models are based are discussed, followed by a review of the Civil Aeromedical Institute's efforts during the 1970s. A comparison is made of the three models available today (GA Model, AIREVAC, and EXODUS). The report then reviews parameters common to all models, and discusses literature available as a basis for these parameters. Finally, the report briefly discusses validation exercises for evacuation models. Computer model, Evacuation, Cabin safety.
Experimental research on issues related to emergency evacuation of a passenger aircraft cabin have tended to use existing aircraft cabins. While a great deal of useful information has been collected, these facilities have limited capabilities to be configured to investigate new or unusual cabin arrangements. A concept design for a flexible cabin simulator has been completed and is described. The proposed facility can simulate any aircraft cabin from a small, commuter category aircraft through a multi-aisle, multi-deck mega-jumbo transport. The simulator allows full flexibility in terms of exit type and placement, location and design of interior monuments, and the size and layout of the passenger cabin. Experimental control is possible of interior and exterior illumination levels, the presence of vision obscuring smoke, and the door sill height when using evacuation slides. Built from modular sections, it might be used in the future to investigate new and unusual cabin designs, such as the flying wing. The proposed simulator is described to illustrate its versatility. The associated building and project costs are also discussed.
Progress in the development of a computerized aircraft cabin evacuation model is described. The model has a two-fold purpose (i) to supplement current certification tests that use human subjects, and (ii) to serve in the investigation of aircraft accidents as a reconstruction tool and identify factors influencing survival of passengers. For the model to be a valid predictive tool when simulating aircraft accidents, the toxic and debilitating effects on passenger behavior of fire and smoke must be modeled. Other aircraft cabin evacuation models use an expert system/rule-based approach to simulate these effects. The work described here presents an object-oriented approach to modeling human behavior in aircraft cabin evacuations. Object-oriented programming (OOP) lends itself to the modeling of complex systems. OOP's foundation is modularity. OOP allows a one-to-one correspondence with the physical world, and thus, eases the burden of model validation. Validation is critical to the successful use of a model as a predictive tool and involves testing to ensure that the model accurately reflects the behavior of a real system. Easing model validation is of particular importance since the real system's environment is hazardous, and performing any tests on the real system is either impossible or not repeatable. The result of this work will help to expand the simulation's capabilities in improved passenger queuing analysis by allowing the incorporation of human behavior into class objects.
This report describes a study conducted by the Civil Aeromedical Institute to investigate potential problems related to the emergency evacuation of civil aircraft carrying handicapped passengers. The study includes an analysis of the movement of individual handicapped subjects in an aircraft cabin and the results of evacuation tests in which a portion of the test subjects either were handicapped or simulated handicaps. Data are given relative to assistance to handicapped passengers, the effects of groups of handicapped passengers, seating location, floor slope, and exit type on the evacuation time. Suggestions by handicapped subjects and a summary of recent aircraft accidents involving evacuation of handicapped passengers are included as appendices to the report. (Author)
Very Large Transport Aircraft (VLTA) pose considerable challenges to designers, operators and certification authorities. Questions concerning seating arrangement, nature and design of recreational space, the number, design and location of internal staircases, the number of cabin crew required and the nature of the cabin crew emergency procedures are just some of the issues that need to be addressed. Other more radical concepts such as blended wing body (BWB) design, involving one or two decks with possibly four or more aisles offer even greater challenges. Can the largest exits currently available cope with passenger flow arising from four or five aisles? Do we need to consider new concepts in exit design? Should the main aisles be made wider to accommodate more passengers? In this paper we demonstrate how computer based evacuation models can be used to investigate these issues through examination of staircase evacuation procedures for VLTA and aisle/exit configuration for BWB cabin layouts.
This paper examines the influence of exit separation, exit availability and seating configuration on aircraft evacuation efficiency and evacuation time. The purpose of this analysis is to explore how these parameters influence the 60-foot exit separation requirement found in aircraft certification rules. The analysis makes use of the airEXODUS evacuation model and is based on a typical wide-body aircraft cabin section involving two pairs of Type-A exits located at either end of the section with a maximum permissible loading of 220 passengers located between the exits. The analysis reveals that there is a complex relationship between exit separation and evacuation efficiency. A main finding of this work is that for the cabin section examined, with a maximum passenger load of 220 and under certification conditions, exit separations up to 170ft will result in approximately constant total evacuation times and average personal evacuation times. This practical exit separation threshold is decreased to 114ft if another combination of exits is selected. While other factors must also be considered when determining maximum allowable exit separations, these results suggest it is not possible to mandate a maximum exit separation without taking into consideration exit type, exit availability and aircraft configuration.
Predicting the collective behavior of people during evacuations from aircraft is a significant challenge, complicated by human behavioral factors such as stress and panic. This paper presents a multi-agent system for simulating the impact of individual human factors on aircraft evacuations. Based on the model, a prototype system, AvatarSim, was developed to simulate emergency evacuations from aircrafts. The simulator can be used to model situations that are difficult to test in real-life due to safety considerations.
The capacity of 35 Brazilian domestic airports was analyzed with a view to determining which of them were efficient in terms of the number of passengers processed. Data Envelopment Analysis (DEA) methodology was employed to construct the efficient frontier for the sample, to reflect which of the airports used airport resources efficiently and which offered surplus in these same facilities, and in what proportion. On the basis of passenger demand forecasts, it was possible to determine, for each airport, the periods when capacity expansions would become necessary to maintain services at standards currently perceived by passengers.
This research develops an agent based simulation model for application to the sortie generation process, focusing on a single fighter aircraft unit. The simulation includes representations of each individual maintainer within the unit, along with supervisory agents that provide direction in the form of dynamic task prioritization and resource assignment. Using a high-fidelity depiction of each entity, an exploration of the effects of different mixes of skill levels and United States Air Force Specialty Codes (AFSCs) on sortie production is performed. Analysis is conducted using an experimental design with results presented demonstrating the effects of maintenance manning decisions on the Combat Mission Readiness (CMR) of a fighter unit.
We provide bounds on the performance of back-to-front airplane boarding policies. In particular, we show that no back-to-front policy can be more than 20% better than the policy which boards passengers randomly.
We report the results of an experimental comparison of different airplane
boarding methods. This test was conducted in a mock 757 fuselage, located on a
Southern California soundstage, with 12 rows of six seats and a single aisle.
Five methods were tested using 72 passengers of various ages. We found a
significant reduction in the boarding times of optimized methods over
traditional methods. These improved methods, if properly implemented, could
result in a significant savings to airline companies.
This thesis describes the developement of a new type of simulation tool for the assessment of designs of public transport facilities (stations, airports) and other public spaces with intensive pedestrian flows. Since the available space for such facilities is increasingly under pressure, the space efficiency and walking comfort is becoming more and more important. The developed simulation tool provides designers and decision-makers with all kinds of quantitative information about the expected quality of pedestrian (traffic) flows such as travel times, waiting times, queue building, preferred routes, visits to shops and counters, etc. This information is very useful in comparing multiple designs as well as to optimise a specific design. The simulation model also is meant to improve schedules of public transport services at interchange nodes by minimising passenger transfer times. To that end, special attention is paid to the modelling of boarding and alighting processes. New insights about walking have been gained by performing unique large-scale laboratory experiments in which large groups of subjects were assigned various walking tasks, such as high volume crossing flows and walking through bottlenecks until flow breaks down. Specific walking and route choice models are developed using observations of passengers on platforms (such as in Delft) and route choice through the station (such as in Delft and Breda). The tool has proven its value in the analysis of new designs of the future Rotterdam Central Station and performance tests of the new Breskens-Vlissingen ferry terminals.
This report was prepared for the Joint Aviation Authorities. This study was initiated by the Joint Aviation Authorities (JAA) under UK Civil Aviation Authority funding. The study was undertaken against a background trend of generally increasing body dimensions within the European population. This trend, when combined with an increasing number of longer duration flights and high density seating, prompted the need for a wide-ranging review of published anthropometric data that would guide JAA when considering the need for any regulation in this area. It should be noted that this report concentrates on the safety issues associated with seating arrangements. The specific aim is to ensure that seating standards are such that passengers would be able to quickly evacuate an aircraft in the event of an emergency. Thus, the study considers seating accommodation against expected population body dimensions. Software modelling has been used to make an initial assessment of the relationship between seating dimensions and evacuation difficulties. The health implications of aircraft seating are also considered. However, the comfort aspects of aircraft seating did not form part of the research study.
A computer model is described to study strategies used by passengers evacuating a burning aircraft. Two baseline cases are presented to demonstrate the model. In the first case, in a simple scenario, strategies were found to change from even movement to the nearest exit to others farthest from the fire. In the second case, a test studying the effects of obstacles on passenger movement, nonlinear effects were found that may increase the time required to escape. The presence of obstacles created bottlenecks and, in some cases, isolated whole sections of the passenger cabin, making it impossible to escape. This occurred even though exits were still available for escape, but passengers could not reach them.