Airport apron capacity: estimation, representation, and flexibility

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1 JOURNAL OF ADVANCED TRANSPORTATION J. Adv. Transp. 2014; 48: Published online 24 August 2013 in Wiley Online Library (wileyonlinelibrary.com) Airport apron capacity: estimation, representation, and flexibility Bojana Mirkovic* and Vojin Tosic Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, Belgrade11000, Serbia SUMMARY This paper addresses some important issues related to airport apron capacity planning and management. An overview of existing apron models for supporting planning studies and for optimizing available resources utilization is given, with an emphasis on analytical models for apron capacity estimation. Constraints on apron usage, physical and operational with respect to different users, are discussed in detail, together with their impact on apron capacity. Simple extension of existing apron capacity estimation models is suggested accounting for constraints both on aircraft types and dominant users. Further on, instead of expressing apron capacity through a single number, an apron capacity envelope is used to illustrate capacity changes, that is, an apron s ability to accept various mixes of dominant users in demand. The apron capacity envelope provides information on capacity for one apron configuration (with respect to stand size and policy of usage) and a given fleet mix, for different shares of dominant users in demand. Finally, apron capacity flexibility is discussed with respect to its role in apron capacity planning and management. It is suggested how to express and interpret apron capacity flexibility. Copyright 2013 John Wiley & Sons, Ltd. KEY WORDS: airport; apron; analytical modeling; capacity estimation; apron capacity envelope; apron capacity flexibility 1. INTRODUCTION Airport capacity planning and management is a very challenging task that requires matching capacity (which is neither easy nor cheap to expand) to fast growing demand, which from time to time suffers changes in its characteristics. We are witnessing the transformation from point-to-point networks to hub and spoke networks and back, of a new user profile appearance (low-cost), the introduction of new large aircraft (NLA) into service (A380), and so on. The runway system is considered to be the main airport capacity planning parameter. This is reasonable, considering that building a new runway is a huge infrastructural project for an airport, both in terms of investment and capacity gain (in aircraft operations per hour). Another huge infrastructural project is the development of the terminal complex, when the issue of passenger terminal capacity comes to the fore. However, in order to provide efficient functioning of the whole system between major infrastructural changes, it is important that the development of other elements (taxiway system, aprons, curbside, etc.) follows expected demand volume and structure changes. Development of other airport elements can be planned and realized in smaller steps, which is associated with smaller investments, as well as a lower risk of significant capacity/demand mismatch occurrence. However, that is not a justification for these issues to be put aside or to be very poorly considered. This paper *Correspondence to: Bojana Mirkovic, University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, Belgrade 11000, Serbia. b.mirkovic@sf.bg.ac.rs Copyright 2013 John Wiley & Sons, Ltd.

2 98 B. MIRKOVIC AND V. TOSIC deals mainly with airport apron(s) capacity planning and management, observing the apron area from the airside perspective. In the process of airport capacity planning and management, significant support comes from a wide range of models and methods for capacity estimation and optimization. In the long history of airport airside modeling, many models (of various levels of detail, methodology and scope) have been developed. A great majority of them focus on the runway system, being identified as the main airport capacity constraint. Regarding taxiway and apron modeling, not much has been carried out in the field of macroscopic modeling. Although apron capacity is affected by almost the same factors as runway system capacity (design, demand characteristics, operational constraints, and local conditions), the operational constraints and relations to other airfield elements are very locally specific and very difficult to represent in a general way. Therefore, aprons (together with the taxiway system) are usually observed, modeled, and resolved on a case-to-case basis, and they exist as part of integrated high level of detail simulation models. The first section gives an overview of apron modeling (to estimate capacity) with special emphasis on analytical models. In addition to that, also provided is a brief overview of the models for optimizing available resources utilization, primarily on apron area. In the process of apron capacity planning and management, it is important to take into account all the constraints on apron usage, which make this airside element much more sensitive to demand structure changes than the runway system is. Runway system capacity is affected by traffic structure with respect to aircraft types (fleet mix), while, in addition to fleet mix, apron capacity may also be affected by traffic structure with respect to airport users (type of flight, airline, origin/destination combination, etc.). In Section 3, all physical and operational constraints affecting apron capacity are discussed, together with their impact on the entire system. In Section 4, a simple extension of existing analytical models is proposed and important issues that have to be taken into account for its further improvement are discussed. Section 5 discusses apron capacity representation, using the apron capacity envelope to illustrate how capacity of a certain apron configuration reacts to changes in demand structure with respect to dominant users. The same section also discussed the apron capacity flexibility concept. It is suggested how to express and interpret apron capacity flexibility. The motivation comes from the fact that, before making huge infrastructural investments to expand existing capacity, an airport can do something to increase the efficiency of existing capacity utilization. On the one hand, apron capacity flexibility is observed as an indicator of ability of the apron to respond on changes in demand structure. At the same time, it is an indicator of latent/reserve capacity that may be activated by reallocation of available resources, that is, relaxation of the constraints on stand use. Concluding remarks are given in Section APRON MODELING Different approaches in apron modeling are discussed in this section. The first part of this section gives an overview of the models that support planning studies. It covers integrated airside models, in which the apron is observed together with other airside elements, as well as models of the apron area as a single airside element. Emphasis is given to analytical modeling. The second part addresses the issue of capacity management, keeping the focus on the apron area, only. It gives a brief overview of the models for optimizing available resources utilization Models for supporting planning studies The apron area is defined by the total number of stands, number of stands per aircraft type, gate usage policy, its position with respect to the runway system, and their mutual functional relations through the taxiway system, as well as by the apron taxiway system, ground handling characteristics, and other relevant factors. This implies that apron capacity problems are specific to each airport and usually observed, modeled, and resolved at the local level. It is very difficult to isolate these relations from the entire airfield system, which is why apron models usually exist as one of the modules of integrated simulation models.

3 AIRPORT APRON CAPACITY 99 The most common simulation tools being used nowadays for airside analysis are the following: TAAM, SIMMODPlus/Pro, and RAMSPlus. All three are complete gate-to-gate models, whereas some others, such as The Airport Machine and HERMES (developed for Heathrow and Gatwick Airports) are limited only to the airport airside area. A detailed description and evaluation of these models can be found in Odoni and Simpson [1]; Odoni [2], Gass [3]; Odoni et al. [4], and up-to-date coverage at Ashford et al. [5]. Updates of new features are available on the websites of companies currently in charge of the development and distribution of the tools (TAAM Jeppesen [6], SIMMOD ATAC [7], and for RAMSPlus ISASoftware [8]). AirTOpsoft [9] represents a new generation of gate-to-gate fast-time simulation tools. It does not introduce much innovation in modeling the airside itself but has the advantage of integrating future or customer-specific ATC concepts much faster. IATA s Total AirportSim includes terminal buildings within its scope in addition to airspace, runways, aprons, and gates [10]. Fast-time simulation airside models are of significant importance to airport planning. They enable definition of the system in high detail, by including physical and operational constraints that apply at the airport. Once the model is built, which requires a major effort, one can determine the effects caused by demand changes (demand increase, demand characteristics changes, temporary changes caused by the occurrence of certain events, etc.), by changes on the supply side (new runway, new parking stands, new runway exits, closure of a runway or an apron due to reconstruction, etc.) or by operational changes (procedural or technological improvements, new concepts introduction, etc.) in a relatively quick and reliable way, which makes it possible to analyze different scenarios and to choose the optimal solution based on that. Simulation models are designed to deliver highly detailed output data, which is very useful and required in some stages of planning but not necessary every time, especially in the case of strategic planning. Although capable of delivering a high level of output, it is important to remember that the quality of output depends on the quality (amount and level of detail) of input data provided. The more uncertain the input data are, the less we can trust the delivered output data. It is often the case that there is a lack of available input data for feeding into the simulation. In such cases, simulations are not the solution that decision makers should reach for and rely on. It is something that is often neglected by airport planners and the reason why these tools are sometimes misused. Because of that, when we have to calculate with rough input data, macroscopic models are much more suitable. Dealing with the uncertain future, planners, managers, and designers need to recognize the wide range of situations that may occur, examine the implications of these scenarios, and develop strategies that enable them to seize opportunities and protect them from risk [11]. An advantage of macroscopic models, in comparison with simulation models, is their capability to deliver good enough output very quickly, with less detailed input that is usually all that is available to the planner (e.g., arrival rates instead of the flight schedule). Quickly does not refer to calculation time, which is also quite small in simulations, but to the preparation period which is much more time-consuming for simulation modeling. That makes them more suitable for analysis of a great number of scenarios and allows their relative comparison. Such models are not necessarily used as a support to final decision-making. It is desirable to use them for the selection of candidate scenarios that will further be analyzed through high level of detail simulation tools. One of the rare (if not the only available) integrated airside macroscopic models is MACAD, Mantea Airfield Capacity and Delay (introduced by Andreatta et al. [12]; further elaborated in Stomatopulos et al. [13]; suggested as a component of the advanced decision support tool for total airport performance assessment and capacity management by EC [14]). MACAD integrates macroscopic airside models to provide approximate estimates of the capacity, utilization, and delays associated with every element of the airside. There are no specific details given on apron modeling, but it is stated that this module identifies the stands that are most limiting (depending on the aircraft types, the type of flights, and the handler/airline that they serve) as well as the ones that are underutilized for the examined configuration and demand scenarios. Not much has been performed in the field of macroscopic modeling regarding taxiway and apron modeling. This is either because they were not considered as a serious capacity constraint (as runways

4 100 B. MIRKOVIC AND V. TOSIC are, especially at major airports that are core nodes in the air transport network) or they were too specific to be represented generally. There are a few generic apron models that can be found in the literature. They calculate dynamic apron capacity based on apron layout (number of stands), use strategy (by aircraft size or user), and weighted average stand occupancy time (SOT) of the aircraft mix demanding service. These models are based on the same approach applied for runway system capacity estimation, calculating the capacity of a service unit as the reciprocal of the average occupancy time of all users served by that service unit (set by Blumstein back in 1959 [15]). In the remainder of the text, the existing analytical apron capacity estimation models are described, as in Mirkovic [16]. They are based on the method of determining the average service rate of the resource from the weighted average service time of all users demanding service, which is broadly applied for runway capacity estimation. Two different models are observed in the literature. The basic one assumes that all aircraft can use all the stands available at an airport. The other assumes restriction on stand use by aircraft type aircraft of a certain size can use the stands designed for those or any larger aircraft. Maximum throughput capacity (saturation capacity) of the runway system indicates the average number of movements that can be performed on the runway system in 1 h in the presence of continuous demand, while adhering to all the separation requirements imposed by the ATM system [17]. Similarly, maximum throughput capacity of the apron (hereinafter referred to as apron capacity ) can be defined as the average number of aircraft that can be served at the apron area (fixed number of stands) in 1h, in the presence of continuous demand (defined by fleet mix and user mix), while adhering to all restrictions on stand use. When there are no restrictions on the stand use, meaning all aircraft can use all the stands, the capacity of the apron can be expressed as C ¼ N t (1) where N is the total number of available stands. t is the weighted average SOT of all aircraft demanding service. t ¼ p i T i (2) i where p i is the proportion of aircraft of class i in the population of aircraft demanding service. T i is the average SOT of the aircraft of class i. An apron capacity model with no restrictions on stand use (and numerical examples) can be found in relevant literature on airport planning as follows: Horonjeff [18], Horonjeff and McKelvey [19], Ashford and Wright [20], De Neufville and Odoni [17], Horonjeff et al. [21], Ashford et al. [5]. A second model assumes restrictions in stand use by stand size. It is defined by Horonjeff [18] and reformulated in later editions 19,21. For restricted stand use, it is necessary to define the group of stands that can accommodate each aircraft class (classification is based on aircraft size). It is assumed that a stand can accommodate the aircraft class they are designed for and all smaller-sized aircraft. The apron capacity limited by each group of stands is calculated from the number of stands in the group and weighted average SOT of aircraft using that group of stands. The minimum of the capacities set by each group of stands is the total apron capacity C ¼ minðc i Þ (3)

5 AIRPORT APRON CAPACITY 101 The capacity limited by the group of stands available for aircraft class i (C i ) is calculated as C i ¼ N i t (4) i where N i is the number of stands that may be used by aircraft of class i (stands designed for aircraft class i and for aircraft larger than i). N i ¼ N i þ N iþ1 þ þ N n (5) t i is the weighted average SOT demanded by all aircraft that can use stands from the i th group. t i ¼ p j T j (6) j i p j is the proportion of aircraft of class j in the population of aircraft demanding service. T j is the average SOT of the aircraft of class j. Ashford and Wright [20] explain the apron capacity model for restricted use (by aircraft size) but under a different assumption. They assume that each stand can be used only for the aircraft they are designed for (small for small, medium for medium, and large for large). It is not taken into account that each stand can also accommodate smaller aircraft. So, apron capacity, in their so-called exclusive use apron capacity model, is C ¼ minðc i Þ (7) where apron capacity limited by the group of stands designed for aircraft of class i is C i ¼ N i p i T i (8) where N i is the number of stands designed for aircraft of class i (only). p i is the proportion of aircraft of class i in the population of aircraft demanding service. T i is the average SOT of the aircraft of class i. This apron capacity model for exclusive use is not suitable for apron capacity estimation with restrictions on stand size, because the main assumption does not depict what is actually happening in reality. But such an approach can be applied for capacity estimation of aprons with exclusive use of stands by different airlines (typical for US airports) or by different users based on other criteria such as required security levels (domestic/international). Different apron stand usage criteria by users will be described in more detail in the next section. When we have aprons with separate areas exclusively used by one user each, one can (incorrectly) conclude that the total capacity of the apron is the sum of the capacities of these separate areas N i C ¼ (9) i T i However, that is not the case. To what extent each apron area is utilized depends on the share of users in demand (p i ). The most restricting apron area restricts total apron capacity C = min(c i ). At the same time, other areas are underutilized.

6 102 B. MIRKOVIC AND V. TOSIC For a quick estimation of apron capacity, there is also the FAA s graphical method [22]. The graphical approach proposed by the FAA, Figure 1, calculates hourly apron capacity expressed in movements/hour as G * S N. G* is the hourly gate capacity base, determined from the chart based on the share of non-widebody aircraft gate occupancy and their share in the fleet. S is the gate size factor and is determined from the gate mix and percentage of stands that accommodate widebody aircraft. N is the number of gates. However, it is disputable how the total apron capacity of three exclusive use areas is calculated (addressed in [16]). Figure 1. FAA s graphical method for calculating hourly gate capacity.

7 AIRPORT APRON CAPACITY 103 In 2009, the project Evaluating Airfield Capacity was initiated under the Airport Cooperative Research Program of the Transportation Research Board. The aim is to produce a new manual for capacity estimation meant for airport planners. The report [23] was released in December It provides another software solution (spreadsheet) for runway capacity estimation but does not suggest any further improvements in relation to apron capacity. In the area of analytical apron modeling, there are several important papers addressing the issue of aircraft gate requirements estimation, which is an issue analog to capacity estimation of the apron area. Bandara and Wirasinghe [24] suggested a stochastic model to estimate the number of gates required to provide a given reliability, based on aircraft arrival rates at gates, the gate occupancy times, and the aircraft separation (buffer) times, considering them as random quantities. Reliability is defined as the probability that there are sufficient gates to ensure zero delay of aircraft on the apron, in a given time period. The method is applicable both under common and preferential gate-use policies, as well as for estimating the required number of remote stands for overflow situations. Steuart [25] investigated the effect of bank operations on gate requirements. He assumed that all flights in the bank have the same behavior. Using a stochastic model based on empirical data, he showed that banking tends to increase the number of gates needed. An extension of his work was published by Hassounah and Steuart [26]. They assumed that each flight has a unique behavior relative to its scheduled arrival and departure times and established a relationship between occupancy of aircraft gates and flights behaviors. On the basis of that, they developed a stochastic model to estimate the demand for gates as a function of time of day, under different scheduling practices and assignment strategies. In addition, they also analyzed the influence of the time interval between banks on gate requirements. In these papers, it is assumed that the flight schedule is known. But as that is usually not the case early enough in advance, when planning a terminal complex for the long term, aircraft arrival rates provide a more reliable estimate than flight schedules. Wirasinghe and Bandara [27] suggest a method for determining the optimum number of gate positions to minimize the sum of cost of gates and cost of delays to aircraft. Gate cost is calculated from the number of gates and the marginal capital, maintenance, and operating costs of the gate per day that is assumed to be constant. Delay cost is calculated from the average cost of delay per aircraft per hour and the total deterministic delay to aircraft per day caused by the lack of gates. The total deterministic delay is calculated from the maximum arrival rate, the mean arrival rate, and the time during which the mean rate is exceeded. A distinction is made between triangular and parabolic-shaped peaks when calculating delay. Cases with one and several non-overlapping peaks during the day were discussed, as well as the modification that uses a known shape of the expected arrival rate curve instead of mean values. This approach was further expanded by de Barros and Wirasinghe [28] to take into account the use of common areas that could be shared by different aircraft types and the effect of interest and demand increase over the lifespan of the terminal to support development in stages ( how much to build and when ). These issues were addressed in light of the introduction of NLA. Two variations of the space-sharing model were discussed. In the first one, gates for NLA and wide body (WB) aircraft are allowed to be used by conventional jets (CJ). The second one assumes that CJ are allowed to use NLA/WB gates, and one CJ is allowed between every two WB and/or NLA gates. It was shown that significant savings are achievable with stage construction and carefully planned shared space between different aircraft types Models for optimizing available resources utilization On the basis of the existing tools, which are widely accepted and implemented in practice, it is clear that the optimization of airport airside resources utilization is mainly focused on the runway system (not only arrival managers and departure managers but also managers for surface movements and turnaround processes, as they all aim to be integrated into total airport managers, having a common objective function, which is runway performance improvement).

8 104 B. MIRKOVIC AND V. TOSIC A very common, and widely addressed, optimization problem in the area of apron utilization optimization is the gate assignment problem (optimization of gate/stand utilization). Many papers deal with this issue (one of the earliest, Babic et al. [29], Mangoubi and Mathaisel [30], Hamzawi [31]; and one of latest, Genc et al. [32]). The majority of them are based on the minimization of passenger walking distances from check-in to gate and from gate to baggage claim area, as well as from gate to gate for transfer passengers. Cheng [33], Haghani and Chen [34], and Dorndorf et al. [35] give a thorough literature overview on research results in this area, classified by methods, goal functions, and so on. However, these models result in aircraft stand assignment schemes and do not consider the apron area as part of the airside. The major parameter for stand assignment is the passenger walking distance to improve and maintain a certain level of service in the terminal building. Ding et al. [36] expand the gate assignment problem by considering over-constrained cases, where the number of aircraft exceeds the number of available gates. They address both the objectives of minimizing the number of ungated aircraft and minimizing total walking distances. The remainder of this paper addresses the issue of apron capacity planning and management, observing aprons as a part of the airside (but still not separating them from the operational constraints imposed by the terminal), which is an issue not often referred to in the literature. 3. PHYSICAL AND OPERATIONAL CONSTRAINTS ON APRON USAGE The main users of the runway system are arrivals and departures (regarding type of operation) and different aircraft types (which directly affect runway capacity through imposed separations). On the other hand, the situation is much more complex when the apron area is being considered. When observed in the broadest sense, the users of the airport are various types of flights (passenger, general aviation, cargo, military, etc.). Regardless of the flight type, all of them use the same runway and (usually) taxiway system, but if the volume of traffic justifies it, the passenger apron is usually separated from the cargo and general aviation apron. In the case of joint civil military airports, there are separate civil and military terminal complexes and taxiway systems. (The number of these airports is increasing, as they are found to be a solution for the lack of runway capacity in the air transportation network [37]). Within the passenger apron, a certain segmentation of the apron area can exist. Low-cost traffic may have their own terminal complex separated from traditional airlines (e.g., Marseilles, Geneva, Kuala Lumpur, Singapore, and Brussels not the whole complex but the new pier with six stands). Because of a significant increase in low-cost traffic, at some airports, existing terminal complexes are adapted for low-cost traffic, for example, Berlin Schonefeld (the previous charter terminal building is adapted for the low-cost airline Easyjet), Budapest (Terminal 1 was reconstructed into a pure low-cost terminal, serving around 10 low-cost airlines), Warsaw (the old terminal building was reopened for low-cost traffic), Paris Charles de Gaulle (charter Terminal 9 is now also used for low-cost flights), and Amsterdam Schiphol (one pier was transformed for low-cost traffic, having a minimum of equipment and facilities), compiled from Radovanovic [38]. When the share of low-cost traffic is not very significant, they usually have a preference of using open stands over terminal (contact) ones (in order to avoid paying for air-bridges usage, which is in accordance with their business model). Regardless of the apron segment in question, there are physical constraints on aircraft stand usage due to aircraft type/stand size compatibility. Each stand may be occupied by an aircraft for which it is designed or by any other smaller-than-design aircraft. Aprons can have a fixed number of parking stands of a certain size or a flexible structure that enables various arrangements of aircraft in the same area, one large aircraft, or two smaller aircraft, for instance (e.g., IATA [39] proposes, so called MARS Multi Aircraft Ramp System concept). Aprons with a fixed configuration are more sensitive to fleet mix changes. The flexible configuration appeared as a consequence of frequent changes in fleet mix, and from difficulties in coping with it, having a fixed structure by stand size. The fleet mix is not the only that affects the apron throughput. There is also traffic structure with respect to users, as there are certain operational constraints that apply to the apron area, depending on the airport. One of the operational constraints refers mainly to terminal stands. It is caused by the necessity to separate domestic and international passengers, as the same processes do not apply to both categories

9 AIRPORT APRON CAPACITY 105 of passengers, either in arrival or departure flow. International passengers have to pass through additional processes (passport control, customs, and perhaps additional security checks) that do not apply to domestic passengers. That is why terminals are divided into those handling only domestic passengers, only international passengers, and mixed terminals if vertical separation of passenger flows is enabled inside the terminal building. That has direct consequences on the aircraft using terminal stands. Domestic terminal stands can be used only by aircraft coming from and flying to domestic destinations. Similarly, international terminal stands are available only for aircraft coming from and flying to international destinations. Aircraft having mixed domestic/international rotations can be accepted only at mixed terminals; otherwise, aircraft have to be moved from one terminal to another when changing destination type. Terminal stands at mixed terminals can accept any combination of origin/destination of flights. At the San Francisco Airport (source: SFO [40]) gates A and G are international, whereas gates B, C, D, E, and F (Terminals 1, 2, and 3) are domestic. There are no mixed domestic/international terminals. European airports experience a somewhat more specific situation, because part of Europe belongs to the Schengen area inside of which there is a free flow of passengers and goods. Domestic passengers are those traveling not only to/from a particular country but to/from the entire Schengen area. The other group is non-schengen passengers having their origin and/or destination outside the Schengen area. Among this group, it is often the case to separate the sub-group of international (intercontinental or special countries) passengers traveling to/from the countries that require some additional passenger checks (usually referring security). The Schengen area in the terminal building has to enable the free flow of passengers, and the non- Schengen area requires entry/exit separation from the Schengen area. Depending on the terminal building, the apron can be available only for Schengen flights, only for non-schengen/ international flights or for mixed flights with respect to origin/destination. If separation between non-schengen and Schengen flows is achieved vertically (by levels) in the same building, terminal stands can be for mixed usage. Unlike USA airports, there are many more mixed terminals at European airports, in order to shorten connecting times between the flights on mixed routes that account for a great share of the total number of connections. For example, at the Zurich Airport (source: ZRH [41]), there is Pier A for Schengen flights and Piers B and E for mixed Schengen and non-schengen flights. Terminal E has separate areas for international flights with special security requirements. If there are more dominant classes of passengers accounting for a significant share, there can be a different organization, for example, Palma de Mallorca Airport has an additional module for inter-island flights. Operational constraints at the passenger apron come from the policy of stand assignment that applies at the airport. In Europe, it is typical that assignment of aircraft to stands is entirely the airport operator s decision. This is so-called a common-use strategy. On the other hand, the typical USA approach for stand usage/operating is dictated by the airline. There is a difference between exclusive, preferential, and joint usage of stands. Exclusive use mode signifies that a single airline has complete use and control of gates. Lease agreements may give the airport operator the right to negotiate for underutilized gates. There are also preferential and joint-use strategies. Under preferential use, a gate is leased to a particular airline, but the airport operator retains the right to assign them to other airlines when they are not in use by the leasing airline. Under joint-use gate strategy, gates are leased to more than one airline. For example, at JFK (source, JFK [42]), airport Terminal 5 is used by JetBlue alone, Terminals 2 and 3 by Delta, whereas other terminals (1, 4, 7, and 8) are jointly used by several airlines. At the San Francisco Airport, all terminals are used jointly by severalairlines.terminal1isusedbyairtranairways, Alaska, Delta, Frontier, Southwest, and US Airways; Terminal 2 by American and Virgin America; Terminal 3 by continental, United and United Express; and the international area is used by all international flights, plus Hawaiian, JetBlue, and Sun Country. As there are more constraints in the usage of certain infrastructure elements, they are less flexible to accept the changes in demand structure. Inflexibility of one element affects the inflexibility of the whole system. In an inflexible system, changes in demand structure can lead to a significant decrease in the efficiency of overall capacity utilization. This issue was referred to in Mirkovic [43].

10 106 B. MIRKOVIC AND V. TOSIC When an apron appears to be a bottleneck in the airside system, it is necessary to detect whether there is an objective lack of capacity, in other words would the capacity issue appear if the apron was constraint-free, or does the capacity issue appear as a result of a misbalance between the supply side (apron configuration plus constraints) and the demand side (demand structure)? In the first case, the only solution to the problem is infrastructure expansion. In the second case, it is possible to avoid a bottleneck through adequate reallocation of the parking stands among the users, that is, through changes and/or relaxation of the constraints that apply on the apron area. If an airline is switched from using one runway to another to achieve higher throughput, that should not present a problem (except that taxiing may be significantly increased). But switching parking stands between users is not simple as that. When evaluating variants, it is important to take into consideration that aprons can be more or less resistant to changes. The reallocation may be such that it does not require restructuring of the terminal building, such as, the assignment of a certain number of terminal stands to low-cost airlines, applying only a different fee policy, or engagement of underutilized cargo or general aviation stands for temporary increase in passenger traffic volume. Reallocation can also be such that it requires some greater or smaller investments in the terminal building, for instance, transformation of the domestic terminal into a two-level mixed domestic/ international terminal. Although it requires some investment, this solution should be taken into consideration if the alternative option is building a new terminal complex. Also, through reallocation, some small infrastructural changes can be accepted, such as a different configuration by aircraft type, which may be achieved simply by removing old and painting new markings at remote stands (assuming there are no fixed installations). 4. ANALYTICAL MODEL EXTENSION On the basis of the previously discussed models, a simple extension is proposed, which combines size and user restrictions, in order to include both physical and operational constraints. The minimum of the capacities set by each ij group of stands is the apron capacity (i user, j aircraft size) N ij C ¼ min C ij ¼ min t ij (10) where N ij is the number of stands that may be used by user class i and aircraft of class j (stands allowed to be used by user i, designed for aircraft class j, and stands designed for aircraft larger than j). t ij is the weighted average SOT demanded by all aircraft, which can use stands from ij group. C ij is the apron capacity limited by the group of stands available for user class i, aircraft class j. The users can be different airlines (typical US stand usage strategy exclusive, preferential, and joint) and/or different flights with respect to their origin and destination/security level required inside the terminal building (general case domestic/international or European specific domestic, Schengen, non-schengen, international with special requirements). In Mirkovic, [16] the results from the FAA s graphical approach are compared with the results from the analytical model previously described. An example from AC 150/5060 is used not only for comparison but also to stress some areas that need improvement. The discussed analytical apron models are suitable for quick capacity estimation for small aprons having simple size and user restrictions. The apron becomes much more complicated to model with the inclusion of more complex user restrictions, size restrictions, different turnaround times, buffer times (BT), and so on. However, these models can serve as a good basis for further improvement in the analytical apron modeling field. In the remainder of this section, important issues to be improved are emphasized. First of all, all these examples assume in their calculation that all stands are fully utilized (100%). In order to obtain a better (more realistic) estimate of apron capacity, calculated values should be

11 AIRPORT APRON CAPACITY 107 multiplied by the stand utilizations factor. Horonjeff and McKelvey [19] consider the utilization factor in their calculation. They assume that for each group of stands, stand time supplied has to be larger or equal to stand time demanded, formulating that for the i th group of stands μ in i t ic i (11) In the expression, μ i represents the percentage of time in an hour that the stands from the i th group can be used by all aircraft that can use stands from group i. Apron capacity is C = min(c i ) where restriction set by the group of stands i is C i ¼ N i t i μ i (12) On the basis of some previous experiences, the utilization factor typically ranges from 0.6 to 0.8 [5]. It becomes more complicated when it has to be expressed for different groups of stands (by user/size), where one stand may belong to more than one group. Average turnaround times have a direct impact on the calculated capacity value. For a certain user, as is the case for low-cost airlines. Their business model is such that it insists on short turnaround times (25-30 min), operating uniform fleet on short- and medium-haul routes, without being dependant, on any connecting flights. On the other hand, traditional airlines, operating variety of aircraft types and wide range of routes, may have turnaround times from 20 min to several hours ([11], [17]), it is easy to make a good approximation of average turnaround time. The analysis of turnaround times and important factors that affect them (e.g., manufacturers requirements, scheduling, hubbing operations, and increasing aircraft size) were addressed by Caves [44]. In addition to that, it is important to take into account that the time during which a stand is blocked by one aircraft and cannot be used by any other, consists not only of the turnaround time at the stand but also includes the buffer (separation) time between two consecutive aircraft using thesamestand. Bandara and Wirasinghe [24] define separation time as the time between a departure from a gate position and the next arrival. It consists of push-out or power-out time, the time required by departing aircraft to clear the apron area and the time required by arriving aircraft to move in from the apron entrance to the gate position. Separation time is influenced by the apron layout. De Neufville and Odoni [17] define the so-called stand blocking time as the sum of SOT, positioning time (PT), and BT. SOT stands for turnaround time, and authors argue that it depends on the size of the aircraft, flight distance, airline, and model (low-cost, traditional, general aviation, etc.). SOT ranges from 20 min (small regional aircraft) to 4 h (wide-body intercontinental flights). PT can range from 2 to 10 min depending on whether the aircraft is pushed back or it does power-in / power-out. In order to absorb possible disturbances in the flight schedule, it is desirable by the airport to plan the BT between two consecutive users of the same stand. Depending on the local circumstances, it can range from several minutes to an hour. When using the utilization factor and/or separation time to obtain a more realistic instead of an overestimated apron capacity, one should be cautious, in order not to include the same correction twice in the calculation which would result in underestimating the capacity of the apron (e.g., if a minimum required separation time between two occupancies of the same stand is already included in the calculation with utilization factor, then it should not be added again to the SOT). Analytical models express apron capacity in aircraft/hour, whereas runway capacity is expressed in operations/hour. In order to observe the airside system as a whole, it is desirable to find a relation to transform aircraft/hour into operations/hour (or vice versa). The roughest calculation is to multiply aircraft/hour by two, assuming that one aircraft is related to two operations arrival and departure.

12 108 B. MIRKOVIC AND V. TOSIC Such a calculation is used, for instance, in the FAA s graphical method. But, as rough as it is, this calculation certainly overestimates the number of operations that correspond to a certain number of aircraft being turned around at the airport. De Neufville and Odoni [17] suggest a more prudent approach. It takes into consideration largest fraction of arrivals in the traffic mix during a certain time interval. For example, if we have 65% of arrivals and 35% of departures and an apron capacity of 11 aircraft/hour, that will correspond to 16.9 movements/hour. Still, this calculation is not enough to capture the real connection between apron and runway system throughputs, because that relation is not as simple as that. This relation depends on many factors such as type of airport in respect to traffic scheme (not only primarily hub and origin destination but also seasonal traffic, etc.), dominant market segments (e.g., scheduled, charter, low-cost, general aviation), and airfield elements design. At hub airports, the traffic schemehas characteristic waves of arrivals followed by the wave of departures (approximately 2 h wide). There are several (alternating arrival/departure) peaks of demand each day. At non-hub airports, demand is not concentrated in waves, but spread out over the day, with the existence of more or less emphasized peak periods (usually morning and late evening and perhaps a midday peak). At seasonal airports with a hedgehog traffic scheme, different relations apply in season and out of season. All these issues are covered in relevant literature related to airport planning and operations but only to the level presented earlier. They are under consideration in ongoing research, but for this stage, only the basic model is used for the purpose of graphical analysis of apron capacity changes due to demand characteristic changes. 5. APRON CAPACITY REPRESENTATION AND FLEXIBILITY ANALYSIS The common way to illustrate maximum throughput capacity for a given configuration of the runway system and given demand structure is the runway capacity envelope, introduced by Gilbo [45]. An example is given in Figure 2, for a single runway. It consists of four typical points, representing different arrival/departure shares. Point 1 represents the capacity of arrivals only. Point 2 represents so-called departure-free capacity and considers additional departures that can be performed without any changes in arrivals separation. Point 3 represents capacity under a 50/50% arrivals/departures share, and Point 4 is the departures-only capacity. In the literature, nothing similar has been used to illustrate apron capacity. Possible shape(s) of the apron capacity envelope(s) are suggested and discussed in examples. The aim is to illustrate the ability of a certain apron configuration to accept different demand structures with respect to dominant users, instead of expressing apron capacity using a single number. A runway capacity envelope gives the maximum throughput capacity for one runway system configuration, for a given demand structure, but for different shares of arrivals and departures. Figure 2. Runway capacity envelope, single runway.

13 AIRPORT APRON CAPACITY 109 Runway capacity is expressed in operations per hour, but smaller time units are also used (usually 15 min). If we consider that arrivals and departures are the main users of the runway as a resource, conversely, the apron capacity envelope should represent the maximum throughput capacity of a certain apron configuration and given demand structure (fleet mix, share of different aircraft classes) for different shares of its users (airlines, origin/destination combination, type of operation, etc.). Apron capacity is expressed in aircraft/hour. Depending on the traffic pattern, different time units might be more suitable than 1 h, for example, the length of the arrival wave at hub airports. In Figure 3, the apron capacity envelope is given for Example 1. Example 1 An apron has 11 stands, of which five stands are available only for domestic rotations (both origin of flight and destination after turnaround are domestic) and six stands are available for all rotations (domestic, international, and mixed). (A rotation stands for a combination of the flight origin of the aircraft and its destination after it is turned around at the airport). Average SOT for domestic rotations is 45 min, and for other than domestic rotations (O/D: domestic international, international international), it is 55 min. If we assume a demand of 50% domestic flights and 50% other than domestic flights, apron capacity is 13.1 aircraft/hour. Apron capacity changes with user structure changes in demand, as shown in Figure 3. With apron configuration changes, the shape of the apron capacity envelope also changes. Figures 4 and 5 represent a set of apron capacity envelopes for different apron configurations (different number of stands available for domestic flights and stands for all flights). It can be seen (Figure 4) that, as the number of stands for all flights increases, the apron becomes less sensitive to user mix in total demand. In (extreme case) a configuration with one stand for domestic flights and 10 stands for all flights, the capacity ranges from 10.9 to 14.7 aircraft/hour. On the other hand, as the number of exclusive use stands (only for domestic flights) increases, the apron becomes more sensitive to the share of different users in total demand (see Figure 5). In the opposite extreme case, assuming a configuration with 10 stands for domestic flights and only one stand for all flights, the capacity of the apron ranges between (only) 1.1 aircraft/hour and 14.7 aircraft/hour. The indicator of the sensitivity of a certain apron configuration to demand structure changes with respect to users will be referred to, hereinafter, as apron capacity flexibility. With an increase in the number of exclusive use stands, apron capacity flexibility decreases. Higher flexibility goes with apron configurations with fewer constraints on stand usage. This is only a simple example to show an apron s ability to accept different demand structures and how it changes with apron configuration changes. In this example, demand structure is given as the Figure 3. Apron capacity envelope, Example 1.

14 110 B. MIRKOVIC AND V. TOSIC Figure 4. Set of apron capacity envelopes, increase in the number of mixed-use stands, Example 1. Figure 5. Set of apron capacity envelopes, increase in the number of exclusive use stands, Example 1. share of domestic/other flights. Depending on the policy of stand usage at the apron, it can be expressed with respect to other users, for example, airlines/alliances. Flexible use of the same area by different aircraft sizes was addressed by De Barros and Wirasinghe [28]. They propose an analytical methodology to determine the number of positions required to accommodate a mix of aircraft types, which takes into account the concept of space sharing between different aircraft types. They determine shared space based on the requirements for gates by each aircraft type in peak periods and idle gate positions during secondary peaks of a typical day. The space to be shared should be carefully planned so that the apron area remains able to respond successfully to variations in demand (volume and structure) during a typical day. With space sharing, the total area required to serve the demand is reduced, as it becomes more flexible with respect to type of aircraft. The paper also discusses operational issues, imposed by type of flights/passengers, which need to be resolved within the terminal, so as to enable full implementation of space sharing. If we have combined restrictions (different types of users, aircraft size), there are many possible combinations that could be analyzed. However, not all of them are within the scope of our interest. For the purpose of comparison between different scenarios, we can observe a set of selected segments of the apron capacity envelope, as in Example 2. Example 2 An airport has an apron of 11 stands, out of which five stands are exclusively used by the base airline, and six stands are for all other airlines flying from the airport. At the base airline apron, three stands are designed for aircraft of class 1 and two stands for aircraft of class 2. The apron for other

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