PAPER FOR THE 15 TH ANNUAL WORLD CONFERENCE AIR TRANSPORT RESEARCH SOCIETY (ATRS)

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1 Costa, Falcao, Cunha, and Dias 1 PAPER FOR THE 15 TH ANNUAL WORLD CONFERENCE AIR TRANSPORT RESEARCH SOCIETY (ATRS) AIRPORT RESOURCES ALLOCATION USING A-CDM FOR THE BRAZILIAN ENVIRONMENT Rodrigo Pintus Goncalves da Costa, Jonatas Barros Falcao, Adilson Marques da Cunha, and Luiz Alberto Vieira Dias Brazilian Aeronautics Institute of Technology ITA Computer Science Division IEC Praca Marechal Eduardo Gomes, 50, CEP Sao Jose dos Campos SP Brazil Phone: +55 (12) {rodrigo.costa@easyflight.com.br, jonatas.falcao@easyflight.com.br, cunha@ita.br, vdias@ita.br} ABSTRACT Lately, the Brazilian civil aviation demand has grown mainly by social inclusion, economic expansion, and low fares. Annually, the capacity demand of airports has increased into two digit figures. Faced with the needs of hosting the most important world sport events for the next years in Brazil, airport infrastructure enterprises have a big challenge ahead. How to provide an appropriate airport resource allocation management system to improve the process of controlling operational information for optimizing resources? This article provides an application of an integrated and collaborative conceptual model involving airports, airline companies, and government. It represents the partial results of a proof of concept performed in the Guarulhos International Airport (GRU) by researchers from the Brazilian Aeronautics Institute of Technology. This approach is based upon the Airport Collaborative Decision Making (A-CDM) concept from the EUROCONTROL, aiming to improve operational efficiency, events predictability, and airport resource utilization, and also to reduce flight delays. Initially, a Problem Based Learning methodology was applied within an airport resource optimization and allocation system prototype named SOAR, involving the critical mission environment of the GRU Airport Operational Center. One of the main contributions of this research work is the positive impact that this proposed model adoption might produce in the airport infrastructure enterprises. KEYWORDS: Airport Collaborative Decision Making, A-CDM, Airport Resource Allocation Management, Situational Awareness, Collaborative Method, Airport Resource Allocation System, Requirements Elicitation.

2 Costa, Falcao, Cunha, and Dias 2 INTRODUCION This article provides an application of an integrated and collaborative conceptual model involving airports, airline companies, and government, based upon the Airport Collaborative Decision Making (A-CDM) concept from EUROCONTROL. It represents only the partial results of a proof of concept performed in the Guarulhos International Airport (GRU) by researchers from the Brazilian Aeronautics Institute of Technology (ITA). Its main objective is to describe a positive impact that the adoption of a proposed model might produce in the airport infrastructure enterprises. Initially, a Problem Based Learning (PBL) (Cunha, 2007) [1] methodology addressed in a graduate course at ITA was applied to the development of the Airport Resource Allocation and Optimization System, in Portuguese, named Sistema de Otimizacao e Alocacao de Recursos Aeroportuarios SOAR (Falcao, 2009) [2]. Afterword, it was improved and applied to the critical mission environment of the GRU Operations Center (Centro de Operacoes Aeroportuarias - COA). The first session of this paper presents the current status of the Brazilian civil aviation, including the main problems and needs of its conceptual model of flights authorizations. The second session introduces the A-CDM concept within the Airport Resource Allocation process, using a proposed method, some techniques, metrics, and a tool, aiming to solve some specific problems identified within a Brazilian COA. The third session presents a case study with the application of this concept within the context of the GRU COA. Finally, the last session provides an analysis of the main results from the case study. The scope of this work is the Airport Resource Allocation process using the A-CDM concept. In order to implement it, in a very specific environment, several different techniques were applied to the GRU airport. This was performed mainly: to cover requested flight plans from airlines, approved by the Brazilian regulator (Agencia Nacional de Aviacao Civil - ANAC); to operationally provide a better control allocation of slot positions 1 ; and to allow enhancements of provisions and verifications of airport resources. The main expected results of this work are the reduction of flight delays and the optimization of airport resources at GRU, as well as the improvement of: Speed on arrivals and departures; Safety and security in airport ground activities; Accuracy on resources utilization; Detection and prevention of potential problems within the airport capacity; and Collaboration on delivering airport resources for all involved entities. 1 Slot positions - locations reserved for aircraft parking.

3 Costa, Falcao, Cunha, and Dias 3 1. CURRENT SITUATION The airport capacity demand of the Brazilian civil aviation is increasing annually, from 10 to 17% of flights (McKinsey, 2011) [3], making airports to look for: new solutions; high technologies; more compatible systems, with new guidelines for online control of operational information; constant trainings of human resources; and improvements of existing processes. Passengers and cargo services have been requiring special treatments, mainly because the growing of internal (airlines) and external (customers) demands for: better quality; speed; comfort; flow; security; and safety on airport operations. For an airline to operate in a specific route, it must request from the ANAC authority an inclusion of an Air Transport Schedule (Horario de Transporte Aereo - HOTRAN), assisted by the Coordination Commission of Regular Air Lines 2 (Comissao de Coordenacao de Linhas Aereas Regulares - COMCLAR) (Oliveira, 1999) [4]. HOTRAN documents are approved and delivered by the ANAC authority, who formalizes concessions for the exploitation of: domestic and international airline passengers; cargos; and postal services by airlines. These concessions must include: schedules, flight numbers, frequencies, aircraft types, and number of seats previously defined. Within a HOTRAN document, an airline must follow some procedures, in compliance with the provisions of the Civil Aviation Instruction (Instrucao de Aviacao Civil - IAC) (Oliveira, 2000) [5]. As shown in Figure 1, requests made by AIRLINES with the purpose of inclusion, modification, suspension or cancellation of a HOTRAN ought to be delivered to ANAC (COMCLAR), within 15 working days, before the expected date of starting operations, and after the first COMCLAR s meeting for examining the request. Therefore, the approved HOTRAN is sent to the COA and informed to AIRLINES. SCOPE OF THIS INVESTIGATION Figure 1 Current conceptual model of flight authorizations 2 COMCLAR A committee for advising the general direction of the Civil Aviation General Department (Departamento Geral de Aviacao Civil - DGAC).

4 Costa, Falcao, Cunha, and Dias 4 Within the scope of this investigation, as also shown in Figure 1, airport resource ALLOCATORS play the role of making general predictions of flights, by considering the size of aircrafts and the possible operational restrictions on the existing aircraft slot positions, for either domestic or international departures or arrivals terminals lounges. Concerning operational planning, airport resources ALLOCATORS must predict infrastructure resources and envision all existing airport facilities such as: fingers, availability of hydrants for aircrafts refueling, check-in counters, baggage carrousels, passengers transportations, among others. An airport flight schedule is based on predicted schedules of arrivals and departures of flights (HOTRANs) which are inserted into the airport Flight Informative System (Sistema Informativo de Voo - SIV). During their working shifts, flight information are received by airport resources ALLOCATORS through documents, periodically submitted by national and international AIRLINES, using several means of communication. AIRLINES must confirm aircrafts reuse for next flights and other data such as: total of passengers; type and aircraft registration number; and its arrival and departure time. This information is registered in the SIV, aiming at daily updating the system, beforehand. This procedure is also valid in case of extra flights, cancellations, schedule changes, aircraft maintenances, crew regulations, weather condition delays, returning flights, and emergencies. Having this information, airport resources ALLOCATORS, during the first working shift of 8 hours a day, makes the planning for the next 24-hour of operation, predicting: aircraft positions, gates, departure halls, baggage carrousels, and other facilities available in airport infrastructure, using the SIV to process information consulting: radio operators, the airport TV-IP ground, and the airport sound booth. Within the context of the Brazilian COA, there is a need for applying the collaborative decision-making concept. The application of this new concept within the Brazilian COA needs to automate and integrate the area of airport flight planning with the area of airport resource allocation to cover: predictability of operations; reduction of the planning time; and flights scheduling. This must be performed: to avoid unnecessary reworks; to mitigate risks caused by manual calculations of aircraft wing clearances 3 ; and to predict the already used capacity avoiding over-demands use of airport resources. 2. INTRODUCING A-CDM IN THE AIRPORT RESOURCE ALLOCATION This session introduces the A-CDM concept in the Airport Resource Allocation process, the information flow among its entities, and its main benefits. It describes the use of a proposed method, some techniques, metrics, and a tool, which characterizes an A-CDM way of solving some specific problems identified within a Brazilian COA. The A-CDM concept, created by (EUROCONTROL, 2011) [6], aims to integrate decisions, in a collaborative way, involving the entities shown in Figure 2 3 Wing Clearance - distance in meters between two aircraft wing tips parked side by side in slot positions.

5 Costa, Falcao, Cunha, and Dias 5 SCOPE OF THIS INVESTIGATION Figure 2 The information flow among the A-CDM entities (adapted from [6]). The main objective of the A-CDM is to ensure that the information flow among entities is performed with effectiveness and accuracy. It aims: to improve the operational efficiency at airports, by reducing delays; to enhance the predictability of events, during the progress of flights; and to optimize the utilization of resources (Martins et al., 2010) [7]. The application of the A-CDM concept provides several benefits (EUROCONTROL, 2011) [8] for its entities. For the Airport Operator (COA) entity, the main concern of this paper shown in Figure 2, the application of the A-CDM provides the benefit of increasing apron 4 capacity, gates usability, and traffic stability. In this case, it provides also taxi distances reduction, thereby minimizing congestions of: queues, runways, taxiways, and aprons. For the Air Traffic Control entity, it provides the benefits of improving: the capacity of planning; the quality of demand calculations for the airport Central Flow Management Unit (CFMU); complying with the demands of Air Traffic Flow Management (ATFM) slots. For the Ground Handler entity, it provides the benefit of more accurate arrivals schedule, allowing more quality of planning and efficient used resources. For the Aircraft Operator entity, it provides the benefit of more situational awareness about aircrafts localizations. By adding more collaborative information and better arrival time sequences, it enables more accurate fleets operations (Meinerz et al., 2010) [13]. 4 Apron airport area where aircrafts use to be parked, loaded, unloaded, fueled, refueled, or boarded.

6 Costa, Falcao, Cunha, and Dias 6 For the Central Flow Management Unit entity, it provides the benefit to avoid exceeding airport and air traffic control capacity. It also ensures available capacity for efficient use. The Airport Operator (COA) and the Airport Resource Allocation Process For each A-CDM entity, there are several processes. But, this paper tackles only the Airport Resource Allocation process assigned to the Airport Operator (COA) entity. Within the largest Brazilian airports, there are two main types of controls provided by: Control Tower (TWR) and Ground Control (GC). Usually, a TWR is responsible for air traffic controls, landings, and takeoffs. After landing, when an aircraft leaves the runway, the responsibility for its allocation on the airport belongs to a GC or a COA. In this case, the Airport Operator (COA) is responsible for the Airport Resource Allocation process comprised of activities such as: assigning aircrafts to slot positions; liberating terminal gates; controlling departure lounges; among others. A Proposed Collaborative Method for the Airport Resource Allocation Process For the airport resource allocation process, a collaborative method was investigated, conceptualized, and implemented, in order to improve airport operational efficiency, enhance events predictability, and optimize resources usability. The proposed collaborative method aims to avoid unnecessary risks and reworks caused by manual calculations of aircraft wing clearances, and to predict over-demands use of airport resources. It is described in the following four steps shown in Figure 3. Figure 3 A proposed collaborative method for the airport resource allocation process The Step 1 of the proposed collaborative method consists of Mapping Interactions among Entities (airlines, the regulator (government), and the airport infrastructure company). This step is necessary to analyze airlines interactions such as aircraft changes or maintenances, flight delays, and other event delays caused by crews, weather forecasting, and airlines, among others. Government authorization standards and documents must be reviewed to compare with airport procedures. In case of new standards or procedures changes, all this information must be documented and reported. Step 2 consists of the Definition of Communication Standards among entities. In this step, all communication procedures such as s, faxes, phone calls, or operational meetings are defined. Besides that, an analysis is performed to identify more effective and speedy communication means within the resource allocations process. Following, a

7 Costa, Falcao, Cunha, and Dias 7 communication standard is chosen and established to be used whenever possible among the involved entities. Step 3 consists of identifying, investigating, and Mapping Operational Problems among airlines, airports, and government for possible solutions. In case of recurrence of similar problems, previous solutions usually are consulted. Step 4 consists of Applying an Automated Tool. In this step, a system prototype for optimizing airport resource allocation processes is used. Here, an automated tool should be chosen to provide problems identification within airport aprons for allocation and detection of necessary airport resources in real-time. All obtained processes from Step 1 to Step 3 should be adjusted and inserted within Step 4, during the application of an automated tool. Applying Techniques in the Collaborative Method Step 3 In each step of the collaborative method for the airport resource allocation process a specific group of techniques can be applied. This paper describes only the Requirements Elicitation group of techniques used in Step 3. The Requirements Elicitation group of techniques aims to identify, among stakeholders 5, all system and product goals. The main techniques used for requirements elicitation in Step 3 - Mapping operational problems are: Interviewing, Brainstorming, and Prototyping. The Interviewing technique is the most commonly used for collecting information. It allows communications between stakeholders and business analysts or requirements engineers (Kotonya and Sommerville, 1998) [9]. The Brainstorming technique is performed on an informal environment. It involves a moderator that encourages new ideas from participants to solve problems. In this technique, all ideas must be taken into consideration and it is forbidden to criticize given suggestions. The Prototyping technique consists in building a prototype from the initial requirements up to the testing by users. The main benefit of this technique is to present several different alternatives without spending undue effort. After the prototype is accepted by users, developers need to create a requirements specification document together with an interface prototype (McConell, 1998) [10]. Applying Metrics in the Collaborative Method Step 4 Metrics are usually designed to measure results obtained from activities within a case study. Within the scope of this paper, the airport resource allocation is a process performed by an Airport Operator (COA). For each COA activity inside the airport resource allocation process, it should be analyzed and measured the execution time of an allocation process. In the context of this investigation, a comparison has to be defined between the COA current activities 5 Stakeholder - a person, group, or organization with an interest in a project.

8 Costa, Falcao, Cunha, and Dias 8 with and without the use of an automated tool. The template shown in Table 1, intends to summarize the COA activities with and without the use of an automated tool. Table 1 A Template for Metrics of COA Activities Activities/Metrics Execution time of COA activities without the SOAR tool (min:sec) Execution time of COA activities with the SOAR tool (min:sec) Time difference between them (min:sec) The best adapted tool for COA activities <Activity description being measured> MM:SS MM:SS MM:SS <The best tool description being measured> <Activity description being measured > MM:SS MM:SS MM:SS <The best tool description being measured > Applying an Automated Tool in the Collaborative Method At this point within this investigation, it was found out that an automated tool should be used in the collaborative method for the airport resource allocation process. This automated tool should be able to provide at least the following functionalities: Importing the existing standard messages such as IATA 6 and/or ICAO 7 flight messages, approved by government regulators; Planning rail flights 8 for arrivals and departures; Planning the ground movement; Scheduling aircraft allocations for slot positions, concerning wing clearance calculations and other rules; and Monitoring, on real-time, flight information through screen views. 6 IATA - International Air Transport Association. 7 ICAO - International Civil Aviation Organization. 8 Rail flight - the concatenation of a flight arrival and departure in the same information.

9 Costa, Falcao, Cunha, and Dias 9 3. CASE STUDY This session introduces a case study applying the A-CDM concept to the context of the Airport Resource Allocation process. It describes the application of the proposed collaborative method using some techniques, metrics, and also an automated tool, named Airport Resource Allocation and Optimization System (Sistema de Otimizacao e Alocacao de Recursos Aeroportuarios - SOAR) (Falcao, 2009) [2], to solve some specific problems identified within the GRU COA. The SOAR tool was the result of more than four years of research and development, involving the ITA (ITA, 2011) [11], the EasyFlight enterprise (EasyFlight, 2011) [12], and the GRU COA. From the current conceptual model of flights authorizations shown in the Figure 1, and also from the information flow among the A-CDM entities shown in Figure 2, this case study focused only on the Airport Operator (COA) entity. Therefore, four steps of the proposed collaborative method for the Airport Resource Allocation process were applied into the Airport Operator (COA) entity. In the Step 3, of the proposed method, three techniques for mapping operational problems were used for requirements elicitation: Interviewing, Brainstorming, and Prototyping. In the Step 4, the SOAR automated tool was applied to analyze and measure the execution time of the Airport Resource Allocation process of the GRU COA. Within this step, for each activity of the resource allocation process, a measurement and an execution time from the allocation process was taken. Following, a comparison was also performed with and without the use of the SOAR automated tool, in accordance with the template previously shown in Table 1. Applying the SOAR Automated Tool in the Collaborative Method A system prototype for optimizing the GRU COA airport resource allocation process named PROT-SOAR-GRU was developed. This was done, in order to provide, on realtime, problems identifications within the GRU apron to easy the detection and allocation of necessary resources. At this point, all the obtained processes from Step 1 to Step 3 were adjusted and inserted into the Step 4 of the collaborative method. During this case study, the PROT-SOAR-GRU automated software was developed to provide the main functionalities of importing the existing IATA and ICAO standard flight messages, approved by ANAC authority. This software prototype was able to provide the planning for the GRU rails flights (arrivals and departures) and the planning for the GRU ground movements. In this prototype, aircraft allocations scheduling were also addressed for the GRU slot positions, concerning wing clearance calculations and other rules. Besides all that, this prototype also has provided real-time monitoring of the GRU flight information through Gantts and aprons screen views. The PROT-SOAR-GRU prototype has supported also the application of the A-CDM concept. On the context of the GRU COA, the PROT-SOAR-GRU prototype has supported the application of the A-CDM concept. The main objective of this concept is

10 Costa, Falcao, Cunha, and Dias 10 to implement a collaborative information flow among ANAC, AIRLANES, INFRAERO (GRU COA), and SOCIETY, as illustrated in Figure 4. SCOPE OF THIS INVESTIGATION Figure 4 The Context of the GRU COA within the A-CDM Concept The Airport Resource Allocation process of the GRU COA has the main responsibilities of: receiving the approved flights by ANAC; planning capacity needs; planning flight allocations and ground motions for each season; scheduling daily flights; managing resources allocations; and monitoring operations. Applying the Collaborative Method to GRU COA Using the PROT-SOAR-GRU prototype, the proposed collaborative method was applied to GRU COA by performing its four steps. Step 1 Mapping Interactions Among Entities - was applied on systems integration, by using ordinary flight communication and information transfer among entities, as the best way to help all involved entities to support decision-making. Step 2 Definition of Communication Standards - was applied only to some airlines, by sending flight information through different medias (fax, , or even personally). But this, still put at risk the airport operations progress, because currently at GRU, each airline are still reporting flights to the GRU COA through different medias, sometimes with delays. In this case, it was possible to formulate a new standard procedure for more effective flight scheduling delivery, using digital messages ( s) to be sent daily until 11:59 pm. Step 3 Mapping Operational Problems - was applied in the mapping of operational problems that must be improved, as soon as possible, within the GRU COA. One of them was the current lack of the information sharing between the GRU COA and airlines to avoid aircraft changes for given flights. For example, although the GRU COA knows an aircraft type is to operate in a specific flight, when an equipment change occurs, it can directly reflect on the aircraft size and wing scale. If this information is not delivered on time, the Resource Allocator (GRU COA) has no means to properly allocate on time the aircraft on a slot position.

11 Costa, Falcao, Cunha, and Dias 11 Step 4 Applying an Automated Tool on this step, the PROT-SOAR-GRU prototype was used. This software prototype used several functions to provide resources allocation. It allows automatically calculations of resource allocations on real-time. Applying Techniques on the Collaborative Method Step 3 to GRU COA Some of the Requirements Elicitation Techniques were applied in the GRU COA, in order to map problems. This investigation reports only the interviewing technique, since it was the most frequently used, due to time and space constraints. The interviewing technique was applied in all GRU COA areas. It started with the resource allocators with the main purpose of collecting operational information daily. Next, this technique was applied to radio operators. At this time, it was possible to collect detailed information between the GRU COA resource allocators and other operational entities (TWR Controllers). After that, the planning coordinators and the flight passenger terminal coordinators were also interviewed. At this time, it was possible to collect information about the GRU capacity, check-in queues, and peak times. Finally, the interviewing technique has involved supervisors and managers. From these stakeholders, it was possible to collect some strategic and important information to verify relationships among airports, airlines, and the society (passengers, users, and others), by converging with other operational and tactical stakeholders interviews, as shown in Table 2. Table 2 Frequency Application of the Interviewing Technique Stakeholder Airport Resource Allocator Radio Operators Tower Controllers Planning Coordinators Supervisors Managers Periodicity daily daily weekly daily monthly bimonthly

12 Costa, Falcao, Cunha, and Dias 12 Applying Metrics on the Collaborative Method Step 4 to GRU COA On this case study, metrics were applied for more than 50 different GRU COA activities. From these activities, 38 of them have presented a reduction in their execution time. Table 3 shows only four of them. For each one of the four GRU COA activities (lines of Table 3), the execution time of an allocation process and its difference was measured (columns of Table 3). The following three metrics were applied: Execution time of COA activities without the SOAR tool (min:sec); Execution time of COA activities with the SOAR tool (min:sec); and Time difference between them (min:sec). Table 3 Apply Metrics of the GRU COA Activities Time Activities/Metrics Execution time of COA activities without the SOAR tool (min:sec) Execution time of COA activities with the SOAR tool (min:sec) Time difference between them (min:sec) The best adapted tool for COA activities A. Inserting flights from regulator requests (ANAC) 01:00 00:01 00:59 A-CDM/SOAR B. Inserting flight plans B.1. Scheduling daily flights 180:00 60:00 120:00 A-CDM/SOAR C. Real-time monitoring flight information through airport Gantt screen C.1. Real-time monitoring flight information through airport apron screen 01:00 00:01 00:59 A-CDM/SOAR D. Reporting and graphing preparation to support decisionmaking 240:00 00:10 239:50 A-CDM/SOAR Figures 5 to 10 show the main results from the application of the PROT-SOAR-GRU software prototype from the four GRU COA activities of Table 3.

13 Costa, Falcao, Cunha, and Dias 13 A. The activity of Inserting flights from regulator requests (ANAC) The PROT-SOAR-GRU software prototype has allowed inserting approved flights by the ANAC authority, using the IATA and the ICAO standard, for a given period, as shown in Figure 5. Figure 5 A. The activity of Inserting flights from regulator requests (ANAC) B. The activity of Inserting flight plans After inserting the ANAC authority approved flight messages into on the screen shown in Figure 5, the PROT-SOAR-GRU software prototype enables also the insertion of flight plans and ground motions, and the definition for the entire period, as shown in Figure 6. Figure 6 B. The activity of Inserting flight plans

14 Costa, Falcao, Cunha, and Dias 14 B.1. The sub-activity of Scheduling daily flights After inserting ground motions in Figure 6, the resource allocator must perform flights schedule, for one day or more. The system is capable of suggesting slot positions available, based upon algorithms developed with rules of the GRU COA, as shown in Figure 7. Figure 7 B.1. The sub-activity of Scheduling daily flights C. The activity of Real-time monitoring flight information through airport Gantt screen Based upon flights inserted (Figure 5), planned (Figure 6) and scheduled (Figure 7) within the PROT-SOAR-GRU software prototype, it is possible to visualize daily scheduled flights, on real-time, in Gantt format (table shape), as shown in Figure 8. Figure 8 C. The activity of Real-time monitoring flight information through airport Gantt screen

15 Costa, Falcao, Cunha, and Dias 15 C.1. The sub-activity of Real-time monitoring flight information through airport apron screen The PROT-SOAR-GRU software prototype allows the resource allocator to monitor the GRU apron through visual inspection on 1pix:1.8m scale, making possible to view status of the airport slot positions used, as well as, to search for any flight by looking at the left hand side menu, as shown in the Figure 9. A pop-up window is also available when a mouse overpasses the position of the objects (aircrafts) on the screen. Figure 9 C.1. The sub-activity of Real-time monitoring flight information through airport apron screen D. The activity of Reporting and graphing preparation to support decision-making As the last activity described in this paper, the monitoring tool provides some graphic representations and reports, in order to aid the resource allocator in his decision-making process, as shown in Figure 10.

16 Costa, Falcao, Cunha, and Dias 16 Figure 10 D. The activity of Reporting and graphing preparation to support decision-making 4. THE MAIN RESULTS ANALYSIS The collaborative method, its techniques and metrics, together with the PROT-SOAR- GRU software prototype used in the GRU COA Resource Allocation process, have shown that, out of 50 case study activities, 38 of them have improved. After successfully applying this new proposed implementation collaborative method, 2 to 3 hours of daily airport resources allocations savings resulted. Inserting, planning, and scheduling activities have presented the most significant improved results in the decision-making process. The PROT-SOAR-GRU software prototype automatic calculations of slot positions, has allowed more agility and optimization of the GRU resource allocation process. Consequently, its safety and security operation in ground activities were also improved. Compared with previous and traditional ways of managing and monitoring the GRU COA resource allocation process, the new proposed collaborative method has provided, among other results: CONCLUSION New visual and virtual inserting, planning, and scheduling of resources allocation activities; Faster allocation of slot positions, resulting in reduction of flight delays; Increasing the speed of handling arrivals and departures; Accuracy enhancement of resource utilizations, allowing better detections and preventions of potential problems within the GRU capacity; and Better collaboration on delivering GRU resources for all involved entities.

17 Costa, Falcao, Cunha, and Dias 17 The main objective of this paper was to describe a positive impact that the adoption of a proposed model and method of resource allocation might produce in the airport infrastructure enterprises. It synthesized an investigation of an integrated and collaborative conceptual model involving airports, airline companies, and government, based upon the Airport Collaborative Decision Making (A-CDM) concept from EUROCONTROL. It has presented partial results of a proof of concept successfully performed in the International Airport of Guarulhos (GRU) by researchers from the Brazilian Aeronautical Institute of Technology (ITA). The initial motivation of this investigation arose from a Problem Based Learning Methodology of a graduate course at ITA. Following, this investigation was applied to a critical mission of the GRU Operations Center (Centro de Operacoes Aeroportuarias - COA), using the airport optimization and resource allocation tool named SOAR.

18 Costa, Falcao, Cunha, and Dias 18 The collaborative method, its techniques, and metrics were implemented in an automated software prototype named PROT-SOAR-GRU, used in the GRU COA Resource Allocation process, showing that out of 50 case study activities, 38 of them have improved. The new proposed implementation collaborative method has provided savings from 2 to 3 daily hours of GRU COA airport resources allocation. One of the most significant results in the GRU COA airport resources allocation decision-making process was its improvement on the inserting, planning, and scheduling activities. With the adoption of the proposed model, the major positive expected impacts of this investigation are resources allocation optimizations and flight delays reductions, in the Brazilian airport infrastructure environments. The use of the proposed collaborative method is recommended to other Brazilian airports, and further works are suggested for improving airports capacity. REFERENCES [1] Cunha, A. M. (2007) Database System Project Course syllabus from the Brazilian Aeronautics Institute of Technology ITA, Sao Jose dos Campos, Sao Paulo, Brazil, 1 st semester, [2] Falcao, J. B. (2009). TECSOAR - Uma tecnica para desenvolvimento de sistemas especialistas na organizacao e alocacao de recursos aeroportuarios, Master Degree Thesis, ITA, Sao Jose dos Campos, Sao Paulo, Brazil. [3] McKinsey (2011), Estudo do Setor de Transporte Aereo, Latin American Airport Infrastructure Seminar, Sao Paulo, Brazil, page 9. [4] Oliveira, M. A. (1999), COMCLAR -PORTARIA Nº 692/DGAC, Departamento de Aviacao Civil, October, [5] Oliveira, M. A. (2000), IAC PORTARIA Nº 033/DGAC. NORMAS PARA CONFECCAO E APROVACAO DE HORARIO DE TRANSPORTE HOTRAN, Departamento de Aviacao Civil, January, [6] EUROCONTROL (2011), Airport Collaborative Decision Making, accessed online, on March, [7] Martins, O. A.; Loubach, D. S.; Meinerz, G. V.; and Cunha, A. M. (2010), Collaborative Decision Making and Information Sharing for Air Traffic Management Operations. In: Chapter 13 - Computational Models, Software Engineering, and Advanced Technologies in Air Transportation. Pages New York, NY: Hershey.

19 Costa, Falcao, Cunha, and Dias 19 [8] EUROCONTROL (2011), Airport CDM Cost Benefit Analysis, accessed online, on March, [9] Kontonya, G. and Sommerville I. (1998), Requirements Engineering: Processes and Techniques. New York, NY: John Wiley & Sons Inc., ISBN: [10] McConnel, S. (1998), Software Project Survival Guide: How to Be Sure Your First Important Project Isn't Your Last. Microsoft Press, Redmond, WA, ISBN: [11] ITA (2011), Brazilian Aeronautics Institute of Technology - ITA, accessed online, on March, [12] EasyFlight (2011), Airport Intelligence Solutions - SOAR. accessed online, on April, [13] Meinerz, G. V.; Gerhold, T.; Hüttig, G.; and Cunha, A. M. (2010), C-ATM/BR: A Cooperative ATM Concept Preliminary Definition for the Brazilian Environment, IX SITRAER - Simpósio de Transporte Aéreo, Manaus, AM, Brazil.