i

Contents Preface

1 INTRODUCTION ....................................................................................... 1 1.1 Project Overview ......................................................................................................................... 1 1.2 Significance of The Proposed Method .................................................................................. 1 1.3 Project Boundaries ..................................................................................................................... 3 1.4 Book Organization ................................................................................................. 4

2 ISSUES RELATED TO CHECK-IN COUNTER SPACE ..................................... 7 2.1 Introduction to The Modeling Approach ............................................................................... 7 2.2 Previous Work .............................................................................................................................. 9 2.3 Evaluation of Existing Methods in Determination of Space Required ..................... 23 2.4 Summary ...................................................................................................................................... 24

3 DATA COLLECTION ................................................................................ 25 3.1 Introduction.................................................................................................................................. 25 3.2 General Information .................................................................................................................. 26 3.3 Input data for The Proposed Model ..................................................................................... 28 3.4 Summary ...................................................................................................................................... 31

4 ESTIMATION OF ARRIVAL DISTRIBUTION ................................................. 33 4.1 Introduction.................................................................................................................................. 33 4.2 The Concept ............................................................................................................................... 33 4.3 IATA Distribution of Arrival Earliness .................................................................................. 34 4.4 Passenger Distribution Program Development ................................................................ 36 4.5 Program Execution ................................................................................................................... 43 4.6 Summary ...................................................................................................................................... 46

5 MODEL DEVELOPMENT:TIME BLOCK SYSTEM ......................................... 47 5.1 Introduction.................................................................................................................................. 47 5.2 Background ................................................................................................................................. 49

ii

5.3 The Conceptual Model ............................................................................................................ 50 5.4 Methodology ............................................................................................................................... 52 5.5 Program Development ............................................................................................................. 57 5.6 Summary ...................................................................................................................................... 72

6 SIMULATION MODEL .............................................................................. 75 6.1 Introduction.................................................................................................................................. 75 6.2 Previous Related Work ............................................................................................................ 75 6.3 The Concept ............................................................................................................................... 76 6.4 Methodology ............................................................................................................................... 77 6.5 The Development of Simulation Program .......................................................................... 79 6.6 Verification Process .................................................................................................................. 89 6.7 Summary ...................................................................................................................................... 92

7 MODEL EVALUATION ............................................................................. 95 7.1 Introduction.................................................................................................................................. 95 7.2 Comparisons of Results .......................................................................................................... 95 7.3 Influence of Demand Fluctuation ........................................................................................ 102 7.4 Influence of A Different Earliness Distribution ................................................................ 103 7.5 The Influence of Queue Systems ....................................................................................... 105 7.6 The Influence of Service Time ............................................................................................ 107 7.7 Influence of Check-in Counter Sizes and Arrangements ............................................ 107 7.8 The Influence of Number of Servers on The Overall Cost ......................................... 108 7.9 Progressive Opening of Counters ...................................................................................... 109 7.10 Limitation of The Model ....................................................................................................... 109 7.11 Future Work ............................................................................................................................ 110 7.12 Summary ................................................................................................................................. 110

8 CONCLUSIONS .................................................................................... 113 REFERENCES ......................................................................................... 117 APPENDIX

iii

Preface This book is developed based on a thesis project carried out by the first author at School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia. We publish this book with some trepidation as we have made numerous simplifications due to resource and time limitations, although design of airport terminals involves many variables and complex relationships. Anyhow, the simplicity of the method we have devised motivated us to share the idea through this book.

This book is about a computational aid to assist in design of effective arrangements for airport check-in lobbies. The main idea we use is that it is possible to synthesize a key input variable required, the passenger arrival pattern, by manipulation of airline schedules. Then we link selected concepts from level of service, queuing theory and optimization methods to develop the methods proposed.

Two simulation models for design of check-in area arrangements are proposed in this book. The first is named the time block concept and assigns passengers in groups to specified time periods. The second method treats passengers as individual entities. Computational tools using these two methods have been developed using a spreadsheet platform. Interested readers can modify the software code included in the book to suit their particular requirements.

Finally, we would like to express our sincere thanks to all who made this project possible. First, we like to express our gratitude to financial support provided by the Australian Development Scholarship (ADS). Then there are numerous agencies and administrators that provided support in the form of data and advice. We thank International Air Transport Association (IATA) for allowing the use of their copyrighted material mentioned in this book. Airport Council International (ACI) provided useful data in the form of airport traffic reports. We also express our gratitude to the seven airport authorities mentioned earlier. Special thanks are also extended to Mr. Ariatedja for his suggestions and help during the development of the models. We hope that this book provides an insight to the reader for an alternative approach to determine appropriate check-in area arrangements.

E. Ahyudanari U. Vandebona June 2009

iv

1

1.1 PROJECT OVERVIEW

The check-in area is one of the busiest sections in airports at certain periods. The passengers are subjected to queues and delays during the check-in process. These delays and queues are due to constraints in the capacity of service facilities. The area required for service facilities for this process includes the amount of floor space that accommodates the check-in desks and passengers in queue, and the space for equipment assisting the check-in process. This project focuses on the investigation of space requirements in check-in areas.

The estimation of space requirements in airport check-in areas practices several different empirical methods. The methods are suggested by International Air Transport Association (IATA) 1989, 2003; Federal Aviation Administration (FAA) 1988; Ralph M. Parsons Company 1975; Ashford 1988; Horonjeff et al. 1993. The reported methods involve utilization of peak hour of passenger flow rates and service times as design variables. Elements such as check-in desk sizes and configuration, construction and operational cost, passenger arrival pattern, and queue system are known to influence the required space that will lead to effective design of check-in area arrangement. This project attempts to propose an alternative method to design airport check-in area arrangement by considering the elements mentioned.

1.2 SIGNIFICANCE OF THE PROPOSED METHOD This project attempts to propose a method that incorporates the elements mentioned above in designing check-in areas. The proposed method includes passenger-waiting time as a parameter that accounts for the quality of service during check-in process. The quality of service is the degree of passenger satisfaction when receiving some services from the system. The proposed method utilizes software, which is designed to estimate the optimum arrangement of check-in areas. The proposed method together with the computation programs developed forms an analysis model that represents the nature of airport check-in areas.

The software designed has two systems. The first system handles arriving passengers as groups based on time blocks. The time blocks follow the increment period of passenger arrival distribution available. This is called time block method.

INTRODUCTION

1 Introduction

2

Figure 1-1 shows the block arrangement applied in this method. Description of this method is provided later in section 5.3. The second one assigns passengers as individuals in the queue process. This is a simulation technique. Figure 1-2 shows the nature of microscopic analysis of this simulation. Passengers are treated as individual entities in this method.

In the time block concept, passengers are framed in counting periods. The length of this counting period depends on the increment period of the passenger arrival distribution available. During the service process, the passengers are grouped into smaller blocks. The length of smaller blocks is the same as the average service time applied, and the capacity of the smaller block depends on the number of servers provided. The estimation of the queue length and waiting time is based on the block system that treats arriving passengers in this block fashion. It seems that this system tends to overestimate the value of waiting time and queue length, and therefore provides upper bound solutions.

Figure 1-1 Time Block Concept

The results, regarding the queue length and waiting time, which is obtained from the simulation technique, are slightly different. The results are smaller in magnitude than the time block results. This is caused by the specified way of the program in handling the arriving passengers.

The advantage of having two different methods is that this allows cross checking the outputs for consistency of the results. Then, these results are utilized to obtain the optimum space required for the check-in process area. In reporting the optimum design, the proposed method focuses on the number of servers required to handle passengers. The optimization is conducted by minimizing the total cost. The costs considered in the optimization process covers construction cost, equipment and furniture cost, payments to check-in counter officers and user cost. The user cost is represented by a waiting time penalty.

The application of the model is demonstrated by analyzing data from five different airports. The collected data covers number of passengers, number of check-in desks available, applied queue system, and applied service time. The information regarding the check-in desk sizes and configurations, passengers arrival distribution pattern, and cost are adopted from industry references. This allows the proposed model results to be compared to the real situation. The results sensitivity of selected variables is investigated as well. The objective of this process is to demonstrate the capability of the proposed model.

Counting period

Time block

Passenger

3

Figure 1-2

Simulation elements

1.3 PROJECT BOUNDARIES This project is limited to the investigation of international check-in counters and examination of the check-in area arrangement. International passengers require longer processing times compared to domestic passengers (Chung and Sodeinde, 2000). For example, international check-in process requires activities related to, i.e.: flight connection (if required), and checking passport and visa. Besides, the processing time may be influenced by passenger luggage weight restrictions.

The restrictions applied may vary; however, international passengers are generally restricted to have two pieces of luggage. For checked luggage, the restriction is no more than 30 kg per item. It is acknowledged that these limits vary with time and differences in jurisdictions. In situations where an individual piece of luggage exceeds the weight limit, the luggage must be unpacked and the contents are transferred to other luggage or discarded. As a result, the service time could be increased.

Passengers approach the departure terminal frontage at different points and times. Figure 1-3 presents the activities performed by departure passengers. After unloading the luggage from vehicles, passengers may be required to screen the luggage. This screening process may influence the arrival pattern at check-in areas. To simplify the proposed model, the area of interest is limited to check-in space. The activities before and after the check-in area are disregarded in this project.

Queue area

Servers

Passenger

1 Introduction

4

Figure 1-3 Departure Passengers Flow Diagram

1.4 BOOK ORGANIZATION In order to convey the information regarding the project, this book is organized into eight chapters.

A brief description regarding the project, the objective and the background of this project are given in Chapter 1. This chapter aims to help the readers to understand the scope of the project and main elements of the project development process.

The project development process is explained in detail in the methodology chapter (Chapter 2). The development stages and the thinking process followed during the project are presented in this chapter. The description of model stages provides background material and references to support the underlying concepts.

A data collection process is also performed during project work. This data collection is presented in Chapter 3. The relevance of some data will be clearer later when model development is presented in Chapter 5. Five different airports around the world were utilized as data sources.

Passengers approach the terminal from different points

Preliminary Baggage Screening

(If required)

Check-in area

Immigration

Departure Lounge

Aircraft

Research focus area

5

Data collected from airports require mathematical manipulations to estimate passenger arrival distributions. This process is described in Chapter 4. The flow rate of arriving passenger is adopted from IATA recommendations since individual airports were not able to provide the passenger arrival distributions. This chapter presents the process in converting the flight schedule into passenger arrival distribution. In other words, the passenger arrival pattern is synthesized from the flight schedules.

Chapter 5 explains model development. The model development entails a developing representative model based on an established method. The concept of the time block program is also explained in this chapter. The time block program is consistent with the IATA distributions for earliness of passenger arrivals given at intervals of ten-minute periods.

The time block is only able to handle a single line of queue and generalizes the estimation of the queue length and waiting time values. The simulation program assigns passengers in a different way compared to time block program (refer to Figure 1-1 and 1-2). The simulation program provides a facility to produce synthesized passengers if required data is unavailable. The process of developing the simulation program is explained in Chapter 6.

The programs are applied to analyze five airports. The estimates from the two programs are compared to the real situation. The programs are also evaluated to answer the research objective by attempting to determine check-in area arrangement. These evaluations are presented in Chapter 7. The limitations of the proposed model and recommendations for future work are also presented in this chapter

Chapter 8 provides conclusions of the project. The appendices consist of raw data related to the five airports, worksheets for

estimating passenger arrival distributions, worksheets for time block program, worksheets for simulation program, and the software code.

1 Introduction

6

7

This chapter presents how the project approached the issues of designing airport check-in area arrangement. The chapter starts with the process of how the model deals with the issues, inventory of the elements involved, and evaluation of the available methods.

2.1 INTRODUCTION TO THE MODELING APPROACH Several methods are available to estimate the required space at airport check-in areas. In practice, the passenger space is the common variable adopted. The passenger space design utilizes established standards provided by relevant organizations. Another method utilizes look-up charts in determining space for passengers. The charts are based on aircraft mix factors. Some researchers attempted to design the space based on the minimum required space for passengers and luggage carts. Other researchers estimated required space based on occupancy rate and cost optimization. The next section presents more details of previous work done in this particular area.

In the real situation, there is a number of elements that may influence the space design required of a check-in area. Those elements are passengers flow, number of servers, queue system, and service time during the check-in process. The proposed method attempts to involve these elements into the designed model. This model may be used as an alternative approach in designing the check-in area.

Figure 2-1 shows the procedure in brief to accomplish these project objectives. Pre-modeling is a data assessment stage before determination of the applicable method. This stage is aimed to review the involved elements in airport check-in area and to evaluate existing methods in establishment of check-in area arrangement. The explanation of elements involved and evaluation of the existing methods are presented in Section 2.2 and 2.3 respectively.

The next stage is modeling. In this stage, the proposed method and the design of the model are established. The term method in this project is a technique in solving the problems. The techniques here could be establishing a formula, developing software, or adopting available standards. The model is a replication of the method that represents the real situation. The model is assumed as the complete picture of check-in area together with all involved elements. More about this stage is presented

ISSUES RELATED TO CHECK-IN COUNTER

SPACE

2 Issues related to check-in counter space

8

in sub section 2.1.1. A complete discussion regarding this stage is available in Chapter 5.

Figure 2-1 Sequence of the model development process

The modeling stage includes data collection as well. This stage also covers the process of data editing and manipulation to obtain passengers arrival distributions.

The last stage is application of the model to some airports. Data from five different airports are utilized in this analysis. Sensitivity analysis is also performed to evaluate the sensitivity of each element in design process.

2.1.1 Method and Model Development The establishment of the proposed method is available in Chapter 5. This project develops a software model based on the proposed method and relevant elements. The proposed model is intended to represent the real situation of check-in areas by accommodating selected aspects of the check-in process. The software developed has two different systems to perform the computation process. The systems are called time block system and simulation. These two systems apply different approaches in assigning arriving passengers. More details about these two programs are described in Chapter 5 and 6.

2.1.2 Data Collection Data collection is performed during the model development. The process of data collection is time consuming due to unavailability of field data. The information in the literature provides a sample of arriving passenger distribution patterns. Based on this pattern, the data related to passenger flow could be obtained after manipulation of data of flight schedules. Therefore the required data is flight schedule, number of

Evaluation of Case Studies

Modeling

Pre-modeling

9

counters, service time and queue system applied. Five different airports agreed to provide the required data through some correspondences. The airport authorities contacted provided information in seasonal flight schedule forms. However, not all airports provided the desired data. Chapter 3 presents the information regarding the data collection, selected airports and other related information.

2.1.3 Data Manipulation A program is developed to assist the data manipulation process. The program is designed to distribute passengers in each flight based on the data of flight schedules. Passenger distribution in this program is developed based on the pattern as presented in IATA reference manual for passenger earliness arrivals (IATA, 1989). The results will provide passenger arrival pattern in check-in area. Chapter 4 presents details regarding this program and explains the distribution process.

2.1.4 Evaluation of Case Studies This stage is the last step in this project. The evaluations cover: (1) the association of the results of the two programs with the real situation, (2) analyzing queue length and waiting time of the two programs, and (3) sensitivity analysis of the programs related to service time, arrival distribution, counter arrangements, queue system, and cost. These evaluations aim to discover the influence of passengers, servers, service time, and queue system in designing airport check-in area arrangements. More about this stage is in Chapter 7.

2.2 PREVIOUS WORK This section aims to review the elements in airport check-in process that may influence check-in area arrangements. The elements involved can be examined by observing the real process in airport check-in area. The acknowledged influencing factors are number of passengers, number of counters available, service time applied, and queue system applied. A number of research works related to the factors mentioned has been conducted in order to improve the system in airport check-in area. These works are cited later to support the assumptions applied in this project.

2.2.1 Passenger Characteristics Passenger characteristics are important in estimating check-in area arrangement. Passenger characteristics in this context mean properties related to passengers, such as the number of passengers, the passenger flow rate, and the required space per passenger.

The number of passengers influences the number of counters and queue space that should be provided. It is important to know how to determine the demand and to understand the arrival distribution of passengers for design purpose. The required space per passenger and level of service perceived are other passenger related issues that are considered in developing the proposed model. The resume of acquaintance related to passenger characteristics and the literatures cited are presented in a separate section.

2 Issues related to check-in counter space

10

2.2.1.1 Determination of the Demand The initial step in developing the proposed model is identifying the demand at

airport check-in area. The methods available for planning the capacity of check-in area are based on peak-hour demand. There are three concepts of peak hour for planning purposes, i.e.: the Typical Peak Hour Passenger (TPHP), used by Federal Aviation Administration (FAA); the Standard Busy Rate (SBR), used by British Airports Authority; and the Planning Peak Hour Passenger (PPHP), used by Transport Canada.

TPHP is a figure that may be exceeded only for a short period. In other words, the figure of TPHP obtained may be exceeded by a small number of days in a year. Table 2-1 shows recommended factors from FAA to compute the TPHP from annual passenger volumes. For example, if the total annual passengers of an airport is 5 million, then the peak hour passengers that will be taken into account in design is: 5 million x 0.04 % = 2,000 passengers/hour.

Table 2-1

FAA recommended relationship for TPHP computations from annual figures

Total Annual Passenger TPHP as Percentage of Annual Flow More than 20 million 0.030 %

10 million 19.9 million 0.035 %

1 million- 9.9 million 0.040 %

0.5 million 0.99 million 0.050 %

100,000 499,999 0.065 %

Less than 100,000 0.120 % (Source: Ashford, 1992)

Other method for determination of demand is Standard Busy Rate (SBR). SBR is the thirtieth highest hour of the year. Some European designers still use this factor. The figure obtained based on SBR is exceeded by only 29 hours of annual operation. Another feature used by the British Airport Authority (BAA) is the Busy Hour Rate (BHR) that is slightly different from SBR.

For practical purposes, the method presented by FAA is easy to follow since data on annual passengers from airports around the world is easy to obtain from the airports authority websites. Unlike the FAA method, the SBR and BHR require annual daily peak hour data, which is difficult to obtain directly from airport authority.

The methods based on peak hour estimation (TPHP, SBR and BHR) yield different figures for planning (Fernandes and Pacheco, 2002). The different figures obtained lead to a puzzle in estimation of demand. IATA (1989) suggests estimation of demand by conducting a survey to obtain a passengers arrival distribution. In airport

11

reference manual, IATA gives an example of passenger arrival pattern. Figure 2-2 presents the example of IATA pattern or IATA passenger earliness distribution.

IATA earliness pattern shows the number of passengers that arrives at a particular time before the departure time of the respective flight. There are different curves for different times of the day. This project adopts IATA pattern since a field survey is avoided for this application, the project needs flight schedules from different airports. The details regarding data collection and estimation of passengers arrival distribution process are explained in Chapter 3 and Chapter 4 respectively.

Figure 2-2

IATA passengers earliness distribution pattern (Source: IATA, 1989)

Figure 2-2 shows four different curves. The curves are for the flights that depart

between 00:00 to 06:00, 06:01 to 10:00, 10:01 to 18:00, and 18:01 to 00:00. Horizontal axis indicates hour: minutes before departure time. For example, -2:10 means 2 hours and 10 minutes before departure time. The number in horizontal has 10 minutes increment. Vertical axis is percentage of total passengers in a particular flight.

2.2.1.2 Space per passenger The factor that needs to be considered in calculation of the total space for queuing

area is the minimum required space for each passenger. International passengers usually use luggage carts if available. The width of passengers with luggage carts is determined based on the average length of the largest luggage positioned crossways on the cart (Davis and Braaksma, 1988). Figure 2-3 shows the passenger dimensions with luggage carts. From this picture, the minimum required space is 1.1 square meters per passenger. This value is the result of the multiplication of the width of the luggage (0.64 meters) to total length of the space occupied by the passenger and the cart (1.72 meters).

FAA has overall standards for gross floor size. These standards are the guidelines for planners who adopt the TPHP figures for design. It means that in designing the required space, the planner estimates the demand based on TPHP as presented in Table 2-1. Overall passenger terminal area per annual enplanement is 0.007 0.011 square meters, and 14 square meters per design hour passenger. Ashford (1984) prescribes that these recommendations are not suitable for international terminals.

0%

5%

10%

15%

20%

25%

30%

-2:50 -2:40 -2:30 -2:20 -2:10 -2:00 -1:50 -1:40 -1:30 -1:20 -1:10 -1:00

Arrival time (hour:minutes) before departure flight

Perc

enta

ge

0:006:0010:0018:00

2 Issues related to check-in counter space

12

Some planners and engineers use Ralph M. Parson Charts (Ashford, 1984). This procedure presents space required for different facilities in airports based on variables such as aircraft mix, share of originating passengers, annual enplanement, and type of baggage devices. This recommendation applies assumptions that may be not suitable for every airport. For example, Ashford (1984) presents a diagram adopted from M. Parson Charts that is valid only for domestic terminals. The value for aircraft mix factor presented in this chart is unable to accommodate a large number of aircraft mix or designing large airports.

The FAA standards and M. Parson Charts, are simple to understand and relatively effortless to use. However, the vagueness of passenger traffic flow leads to difficulties in efforts to meet existing conditions.

BAA and IATA also present the space standard for passengers in check-in area. Table 2-2 gives these values. The recommended space by BAA and IATA is less than the space recommended by Davis and Braaksma. The figures in Table 2-2 could be the space for passengers and baggage without cart. However, it is common in international airport to provide the passengers with carts.

Table 2-2

BAA and IATA design standards for check-in areas

BAA IATA

Space standard

0.8 square meter per passenger with checked baggage

0.8 square meter per passenger with checked baggage

0.6 square meter per passenger with cabin baggage

0.6 square meter for visitor

In this project, a method of determination the required space for check-in areas is

developed to compliment the above methods. The proposed model adopts the minimum space for passengers with carts, and proceeds through microscopic analysis. The results of the model are compared to the available standards. Additionally, the results will be controlled by evaluation on passengers convenience that is discussed in the next section (Level of Service).

2.2.1.3 Level of Service In designing facilities for passengers, it is important to consider comfort level of

passengers. Passengers require enough space to stand and move in the queue area. IATA proposed a method in determining service level of airport passenger terminal based on six different levels of space provision as shown in Table 2-3. Based on level of service stated in IATA document (1989), the space applied in this project (1.1 square meters) is considered as level of service D. This condition is acceptable for short periods.

13

On the other hand, according to Martel and Seneviratne (1990), in quality of service analysis, the waiting time is the most important factor for passengers. The survey has shown that 60 percent of the respondents feel that waiting time is the most important variable

Figure 2-3 Passenger dimensions

(Source: Davis and Braaksma, 1988)

Table 2-3 Check-in area space standard (in square meter per occupant)

Level of Service

Space per person (square meter)

Description

A 1.8 Excellent level of comfort

B 1.6 High level of comfort

C 1.4 Related subsystems in balance

D 1.2 Conditions acceptable for short periods of time

E 1.0 Limiting capacity of the system

F

2 Issues related to check-in counter space

14

time is 3.1 minute (coefficient of variation 0.65) and 10.6 minute (coefficient of variation 1.17) respectively. These results indicate that the level of service measures tend to be different depending on the measuring instrument utilized.

This project tries to incorporate the required space per passenger and waiting time simultaneously. It means that the design aims to provide acceptable space with optimum average waiting time.

2.2.2 Check-in Counters Check-in counter is a stand up desk. There is a low shelf placed to the left and/or right of the check-in counter to provide inlet for outbound baggage. Here the bags are deposited, checked-in, tagged, and weighed. Afterwards, the baggage is transported using conveyor belt near the counter to a location sorting outbound baggage.

Check-in counters have two characteristics that may influence the design. These characteristics are size and configuration. IATA reference manual (1989) provides the size and configuration applied in this project. Some airports may have their own furniture designs.

In addition, the number of check-in counters needs to be considered as well. The small number of check-in counters for busy airports generates long queues and waiting time. As a result, the airport must provide a wide area to accommodate the long queue. It means the cost for queue area will increase.

The size and configuration, and the process in determination of the number of check-in counters are described separately in this section.

2.2.2.1 Size and Configuration The space for each counter must include the space for baggage handling as well.

The arrangement in handling the baggage depends on the counter configurations. The baggage handling arrangement influences the location of weighing machine and conveyor belt. Therefore, the space required for each counter depends on the type of the counters.

There are two main types of check-in counter facilities: frontal, and island. These two types of arrangement are shown in Figure 2-4. Frontal type counters are usually placed along the wall. The arrangements of these counters could be uninterrupted or separated. The uninterrupted arrangement is called linear type. Uninterrupted means that the counters are arranged side by side. The separated arrangement is also called pass through type. The space between the counters allows passengers to walk through after check in.

The island type consists of number of counters in one location. This type of counters usually consists of 10 15 individual counters. This number could be doubled if the baggage conveyor belts installed are also doubled.

15

Figure 2-4 Examples of check-in layouts (redraw not to be scaled)

(Source: IATA, 1989)

b.

FRONTAL PASS-THROUGH

Check-in desk

Conveyor belt and scale

Underground outbound conveyor belt

Void

a.

FRONTAL LINEAR

Check-in desk

Conveyor belt and scale

Outbound conveyor belt

c. Check-in desk Conveyor belt and scale

Outbound + underground conveyor belt

ISLAND

Partition

2 Issues related to check-in counter space

16

a. Linear type with multiple single-server queues

b. Linear type with multiple servers queue

Figure 2-5 Linear type

The selection of the configuration of check-in counters depends on the design of the terminal building and management of passenger flow. Figure 2-5 gives more detail of linear type. The circulation area must be considered carefully since there

Conveyor

Officer Check-in

Passenger in service

Passenger finished

Passenger in queue

Arriving passenger

Circulation area

Outbound conveyor belt

Passenger in service

Passenger in queue

Queue line

Officer

Check-in desk

Passenger completing service

Passenger entering system

17

could be a conflict between flow of passengers waiting for service and passengers completing service. The conflict for linear type with multiple single-server queues is that passengers who complete the service may interfere with other passengers that move forward to obtain the service. For linear type with multiple servers queue, placing the outlet of the queue at the beginning of the counter desks and the outlet for passengers completing service at the end of the chain of check in counters can reduce the conflict. Therefore, the moving passengers for service will have the same direction as passengers completing service. The problem arises if the vacant counter is at the end of the counters group. This situation could increase the waiting time for service since the passengers have to walk for a longer distance, i.e.: from the queue area to the last counter. In this case, the number of multiple servers needs to be carefully defined.

If the check-in counters arrangement selected is pass-through type, the conflict in circulation area will not occur. In a pass-through type, after completing service, passengers continue their departure process by passing through the check-in counters. Figure 2-6 gives details of the pass-through arrangement. Based on this situation, it is possible to reduce the circulation area for pass-through type. However, this type requires more lateral space.

Figure 2-6 Pass-through type

The island type has the same problem as linear type in the circulation area. It is

important to have enough width and good circulation arrangement to avoid congestion in this area, especially during peak periods.

Passengers route after completing service

Passenger leave the system

Void

Conveyor belt

Officer

Check-in desk

Passengers in service

Passengers in queue

2 Issues related to check-in counter space

18

For reference, Table 2-4 presents sizes of check-in counters obtained are from Airport Terminal Reference Manual (1989) of IATA. This project adopted the check-in counter sizes as written in Table 2-4. However, the latest issue of IATA document entitled Airport Development Reference Manual (2003) provides the sizes of check-in counter more detail as shown in Table 2-5.

Table 2-4 List of check-in counter types and sizes

Type Size

Width (m) Length (m)

Pass-through 2.20 7.60

2.60 7.60

Linear

1.80 4.70

1.80 5.40

2.20 5.40

2.00 5.40

Island

2.50 5.12

3.00 5.12

3.00 5.28

3.00 5.40

(Source: IATA, 1989)

Table 2-5 List of check-in counter sizes (IATA, 2003 Used with permission)

19

Letters A, B,,V, denote as element of check-in counter general design requirements. Those letters are shown in Figure 2-7.

Figure 2-7a Detail requirements for check-in counter design top view,

section B-B and section C-C (Source: IATA, 2003 - Used with permission)

2 Issues related to check-in counter space

20

Figure 2-7b Detail requirements for check-in counter design section A-A

(Source: IATA, 2003 - Used with permission)

The length of the check-in counter includes the main conveyor and passenger circulation space in front of the counter. The variation on the size for each type is caused by different system characteristics applied to each check-in counter. Some important characteristics are baggage handling mode (manual or automatic transferring baggage to main conveyor), standing or sitting check-in agent, and easy or difficult access to working position. Those system characteristics are not considered in this project.

The optimum design of check-in area depends mainly on the number of required counters. Details of this issue will be discussed in Chapter 7. The IATA method to determine the number of check-in counters is presented in the next section.

2.2.2.2 Number of Check-in Counters The number of check-in counters usually depends on the number of departure

passengers and the average processing time per passenger. The convenience of the passengers in the check-in process should also be taken into account. Psychological factor of the passengers is important. This factor is covered in the level of service section (subsection 2.2.1.3). To calculate the number of check-in desks, IATA in Airport Development Reference Manual (1989) gives the following formula:

21

%)10(60

)( ++= deskstbaN (2-1) where: N = number of desk required a = peak hour number of originating passengers b = number of transfer passengers not processed airside t = average processing time per passenger (minutes) This equation does not guarantee that the number of check-in desks provided will

meet the service standard. Service standard here is associated with the level of service.

The number of check-in counters is considered to accommodate the maximum queue. However, the airport management must consider the operational cost. To provide the maximum service rate with minimal cost, in his article, Hon (1999) presented an intelligent resource simulation system. This system allocates the number of check-in counters efficiently to meet business demand. The system considers a number of factors, such as different service rates for different destinations, airlines, and handling agents; different passenger arrival rates for different departure times; and different requirements service levels. These are the benefit of this system,

Intelligent resource simulation system provides a progressive opening of service counters instead of opening all the counters for the entire check-in period. It means that the check-in officers are assigned to provide services based on certain period. This scheduling depends on the arrival pattern of passengers at the counter. For example, a counter profile of 8-10-12 means that eight counters are opened in the first hour of operation, ten counters for the next hour, and twelve counters for the last hour. During the implementation in Kai Tak airport, Hong Kong, this system claimed to be able to save up to 40% of resources.

However, the intelligent resource simulation system requires the availability of statistical data of the demand. Besides, there is no information regarding the achieved level of service in this system. The author did not discuss whether the system could be implemented during planning period of a new airport since the available data at this stage is only forecast of total demands. It is important for the planners to have a tool to calculate the number of check-in counters required to meet a particular demand. This project includes the information regarding the number of required counters to open at certain time. This information assists the airport authority in using the progressive opening check-in counters.

Based on the review on some results from previous work, it is important to have data related to the existing number of check-in counters in selected airports. This project utilizes the data to validate the model results.

2.2.3 Service Time The value of service time influences the number of check-in counters and required space. The longer service time requires more space to accommodate queuing passengers or requires more check-in counters to reduce the waiting time.

Some references provide the estimated values of service time and waiting time. The literature suggests service time based on standards from aviation organizations,

2 Issues related to check-in counter space

22

economic point of view, interviews with passengers, and the measured actual service time using objective instruments.

BAA and IATA provide design and service standard for departure passengers as shown in Table 2-6.

The specified standards by BAA and IATA need to be investigated further. The defined time standard may require a high cost. Omer and Khan (1988) investigated the correlation between quality of service and cost. They illustrated the application of utility and cost effectiveness theory. The authors adopted this theory to measure user perceived level of service and establishes economical design criteria. They suggested that the level of service that corresponds to the optimal alternative is the best one for facility design. The optimal alternative is the option with the minimum expected social cost.

Table 2-6 BAA and IATA service standard for check-in area

Indicator BAA IATA Time standard 95% of passengers are

less than 3 minutes. 95% of passengers less than 3 minutes 80% passengers less than 5 minutes at peak time

Allowable waiting time 10 min. Not applicable (Source: Ashford, 1988)

Park (1999) attempted to classify passenger perception of service level. The classification is based on time spent at airport terminal processing facility. In determination of this perception, he is using three linguistic identifiers. Those identifiers are good, tolerable and bad applied to perception-response (P-R) model. This methodology was applied at Kimpo International Airport, Seoul, Korea. The results for check-in processing time for long haul journey are good for time spent when the service is less than 13.5 minutes, tolerable for 13.5-22.5 minutes and bad for service that more than 22.5 minutes.

The above references have considered in the effect of service times to the waiting time. This project will also consider the social and construction cost related to the service time as one component.

2.2.4 Queuing System The queuing system is the last aspect considered in designing the check-in area arrangement. The most common queuing systems in airport are multiple single-server queues and multiple server queues. Sketches of these two queue systems are available in Figure 2-5. Figure 2-5a represents multiple single-server queues. This picture shows that the number of queue lines is the same as the number of counters. Figure 2-5b is a sketch of multiple server queues. This type applies one queue line to feed a number of counters.

23

As shown in Figure 2-5, the space required for these queue systems is different. For multiple single-server queues, the width of the queue line will always be the same as the width of the counter desk. This occurs since one queue line feeds one server. The width for multiple server queues is the minimum possible queue line width. This minimum queue width depends on the maximum width of passenger with baggage. This difference may influence space required in check-in area. Discussion regarding this is in Chapter 7.

The other thing that needs to be investigated is the queue discipline. The common queue discipline applied in airport is first-in first-out (FIFO) or first-come first-served (FCFS). This queue discipline is possible to apply if the queue system is multiple server queues. For multiple single-server queues, passenger who come at t and join the queue line number 1 will not always obtains service before passenger who come at t+1 and join queue line number 2. This situation occurs since the passengers in queue 1 may require longer service than passengers in queue 2 do. The queue discipline will be discussed more in Chapter 5.

This project includes the queue system as one factor influencing the design of check-in area arrangements. The queue system is the last factor in the list of involved elements in this project.

2.3 EVALUATION OF EXISTING METHODS IN DETERMINATION OF SPACE REQUIRED

The purpose of evaluation of the available methods is to understand the characteristics of the available methods. The proposed method attempts to provide alternative solution in determination of check-in space. The alternative is expected to have an improvement compare to the existing method.

2.3.1.1 IATA method IATA in its Airport Terminal Reference Manual (1989) gives a formula to calculate

the space for queuing area in square meters. The formula is:

(2-2)

Where a = peak hour number of originating passengers

b = number of transfer passenger not processed airside s = required space per passenger It is assumed that s = 1.5 square metres. This fits to the assumption that separation

between check in counters (also the queue width) is average 1.9 metres and lateral space requirement per passenger is 0.8 metres (Note: 1.9 x 0.8 = 1.5 square metres).

It is assumed that 50% of peak hour passengers arrive within the first 20 minutes. However, the number of passengers could be more than this estimate. Therefore additional 10% of space is allowed as a general rule when calculating the space. This correction factor may vary depend on local conditions.

The space required per passenger in equation 2-2 is different from suggested values in Table 2-2. There is no further information regarding this difference. The

.)(25.0)(

2 ) ( 3

60 20 + =

+ + = babab a x xs A

2 Issues related to check-in counter space

24

space in Table 2-2 may have adopted different queue width or used different level of service.

2.3.1.2 Other Methods

As mentioned earlier, some organizations suggested personal space based on the six levels of service. On the other hand, FAA and Horonjeff proposed a method based on the queue length, number of servers, service rate and spacing between queuing passengers. Parson (in Ashford, 1984) recommended required space based on aircraft mix by making use of the charts. The required space for passengers depends on the occupancy rate (Seneviratne and Martel (1995)). Subprasom et al (2002) introduce the most recent method. Their method considers cost of constructing facility, cost of operation and maintenance, and user costs.

The total space in check-in counter consists of space for passengers and for the counters. The method only estimates the space for passengers in queue. IATA (1989) also provides the formula for estimating the number of servers required (equation 2-1) and sizes of the counters (Table 2-4). The separation in estimating the facility may present the required space, since elements in check-in area influence each other.

The previous methods available also do not consider the influence of queue system. From the explanation at section 2.2.4 regarding the queue system, it is clear that different queue systems could be lead to different space requirements.

At this stage, aspects in check-in area and the limitation of the available methods also have been identified. To avoid an overestimate in designing the check-in area arrangement, this project tries to develop the proposed method.

2.4 SUMMARY The project proposes a method to determine space requirement at airport check-in areas. This project is approached in three steps, i.e.: pre-modeling, modeling and evaluation of case studies. The pre-modeling step comprises two stages, i.e.: making a list of involved elements and evaluation of the existing methods. The elements considered are passengers, check-in counters, service time, and queue systems.

It is important to observe passenger characteristics in order to avoid over estimation of the checking area. The check-in counter arrangements may influence the queue system applied and the passenger circulation process. Passengers require different service times regarding the check-in process. This project will investigate the sensitivity of service time value to the design (section 7.6).

Some references are cited to show that all elements have been considered properly. Modeling and evaluation steps have been briefly discussed. These steps are presented in detail in separate chapters in Chapters 5, 6 and 7.

25

3.1 INTRODUCTION As stated in previous chapters, this project requires data about demand; number and type of available servers, applied service time, and implemented queue system. This chapter presents the process of data collection, airports selected to be investigated, and data presentation as data entry for the propose model.

Data required for this project were received from five different airports. Field surveys were not performed due to limitations on time and funds. This type of surveys requires large number of surveyors to record the time of arriving passengers and follow their progress until the passengers finish check-in process. Field surveys are not possible to conduct since in each state, usually, has only one international airport. To be able to model the check-in process, data from different airports are preferred.

Data collection process involves three activities. Those are correspondences with organizations related to air transport, browse through airport websites and contact airport authorities. Organizations related to this project are International Air Transport Association (IATA), Federal Aviation Administration (FAA), International Civil Aviation Organization (ICAO), and Airport Council International (ACI).

IATA was the organization that provided information regarding the earliness arrival distribution, check-in counters arrangement, and formulae for estimating check-in space and number of required servers in its Airport Terminal Reference Manual. This manual has been renewed with new edition entitled Airport Development Reference Manual (2003). It was speculated that IATA also has other required elements for this project. However, IATA was unable to provide relevant documents. However, IATA made an annual report available for this project. Unfortunately, information contained in the annual report was insufficient.

Some research reports about similar issues have quoted several documents from FAA regarding check-in area arrangements. FAA was contacted to obtain

DATA

COLLECTION

3 Data Collection

26

the documents entitled Terminal Design Advisory Circular. Unfortunately, the documents were still under revision during the period of this project.

ICAO was also contacted to obtain documents related to the project. ICAO also did not have the required information. However, ICAO suggested contacting ACI, which has documents on quality of service at airports. The document entitled Quality of Service at Airports: Standards and Measurements; contains measurements of airport quality of service. The document also includes passenger preference regarding waiting time.

In order to obtain the necessary data, some airport websites were explored and contacted the airport authorities. Not all airports responded. The responded airports are Birmingham (UK), Brisbane (Australia), Brussels (Belgium), Calgary (Canada), Hong Kong (China), Melbourne (Australia), and Orlando (USA). Those airports, except Brussels, provided flight schedule information instead of demand profile. However, flight schedules from Calgary airport were in Gantt chart form and unclear to read. Therefore, Calgary airport was excluded from the analysis presented later. Brussels airport provided its annual report for year 1999.

The other data provided are number of servers, type of check-in desks, type of queue system, average service time, and number of advised to passengers hours to do their check-in. These data are presented in Section 3.3. This additional information is retrieved from correspondences with the airport planners in each airport. General information of selected airports is given in the next section.

3.2 GENERAL INFORMATION This section presents brief information about airports selected. The

description covers location of those airports, the size, and some passenger demand information. Not all airport websites deliver complete information. Table 3-1 presents comparison of information regarding all airports selected in one table.

3.2.1 Birmingham International Airport (UK) Birmingham International Airport (BIA) is the 5th busiest airport in UK. The airport is situated 13 km (8 miles) southeast of Birmingham city center. Transport modes available to the airport are train, bus, coach, car, and taxi. Birmingham airport was opened in year 1939 and it became an international airport in 1984. In year 2001, BIA handled 7.8 millions passengers. BIA serves 110 destinations offered by 40 airlines. Most of the destinations are in Europe and North America. The IATA code for this airport is BHM.

Check-in desks for Birmingham airport is not merely for International passengers. International, Domestic and Common Travel passengers use the desks. Common travel passengers are frequent travelers that use charter flights. A CUTE (common user terminal equipment - ARINC) system operates

27

at this airport, which makes it possible for all desks to be used by all categories of passengers. The total area of departure concourse is 2088 sqm.

More information on BIA is available in its website: www.bhx.co.uk

3.2.2 Brisbane International Airport (Australia) Brisbane airport is located 20 minutes drive (13 km) from the CBD. Coach, taxi, and train are ground transportation alternatives to the airport. The airport size is 2,700 ha, which is three times larger than the Sydney airport (Australia). There are 27 international airlines serving Brisbane airport. In 1998, there were 2.5 million international passengers and 10.5 million domestic passengers. The forecast for year 2018, the total passengers, including international, domestic, regional, are 33 million. The airport operates 24 hours a day.

The IATA code for this airport is BNE. Information on Brisbane International Airport was available from the last

update of its website in 1999. The website is www.brisbaneairport.com.au.

3.2.3 Hong Kong International Airport (China) Passengers from China and Asia have voted Hong Kong International Airport as the best airport in year 2002. The airport is located in an island, 25 km west of Hong Kong city; 23 minutes drive from downtown. Transportation links to the airport are ferry, public busses, coach, taxi, hotel limousine, and private car. The airport is able to handle maximum 49 movements (aircraft take off and landing) per hour. The airport was designed to handle 87 millions passengers per year and 13,680 pieces of baggage per hour at its peak usage in future. The current capacity of the airport has been increased from 35 millions to 45 millions passengers. In 2000, the airport handled 34 millions passengers.

The Hong Kong airport provides nine check-in islands with 288 desks. The target of the airport operator was passenger check-in in less than 30 minutes. The airport operator claimed that arriving passengers can clear immigration within 10 minutes.

The IATA code for Hong Kong airport is HKG. For more information, visit the website of Hong Kong airport authority:

www.hkairport.com

3.2.4 Melbourne International Airport (Australia) Melbourne airport is located 22 km northwest of the CBD. The airport can be reached by car, taxi, and bus. The airport serves 22 international airlines and 3 domestic airlines. In 2001, this airport served 3.36 million international passengers. To provide a good service, the airport authority has 88 check-in desks and a 2800 square meters of check-in area.

The IATA code for this airport is MEL.

3 Data Collection

28

The website for more information is: www.melboune-airport.com.au

3.2.5 Orlando International Airport (USA) Orlando International Airport is the third largest airport in the USA. It is located in State of Florida. The passengers can reach the airport using rental cars, bus, taxi, and shuttle bus. The airport is able to serve 72,000 passengers per day, or more than 31 millions passengers per year. At the present, the airport handles about 26 millions passengers per year. The area of the terminal building is about 0.4 million square meters (4.5 million sqft).

The airport website: www.orlandoairports.net:/goaa/main.htm offers additional information.

Orlando airport applies a system that is commonly used. International flights are assigned a certain number of positions based on aircraft size. For example, a narrow body and a wide body are assigned 2 and 4 positions (check-in desks) respectively. Area for check-in desks and queuing available varies depending on the airline. The majority of airlines operate a "snake-line" to queue passengers. The snake line system is a line curved around several times with stanchions to reduce the space occupied by the queuing passengers. The snake line is the same system as multiple server queue system (Figure 2-5). The length of the queue is built around the number of check-in counters, which gives more space for larger aircraft. The queues are generally 1.06 m (42 inches) wide. Each ticket counter desk is approximately 1.36 m (4 ft) wide. The length is generally 5.44 m (16 ft) from the desk to the beginning of the queue.

3.3 INPUT DATA FOR THE PROPOSED MODEL As mentioned earlier, flight schedules are adopted as data input in the proposed model. The flight schedules provide information regarding departure times and aircraft type. The aircraft type is useful since it describes the passenger capacity. Table 3-2 presents an example of flight schedules. In this table, the aircraft types are indicated by the capacity of respective aircraft.

Departure times shown in this flight schedules is utilized to derive passenger arrival distribution. To do this process, this project adopts the earliness arrival of IATA, as mentioned in Section 2.2.1.1 and Figure 2.2. Next chapter explains more detail regarding the computation process of arrival distribution.

Data shown in Table 3-2 is from Birmingham airport for international departures for summer 2001. Data presented in this table is organized the same way as the input interface that will be explained later in conjunction with the model. The first column (column A) shows the sequence number of the schedule. Column B is the destination. In this column, one destination could have more than one schedule since different airlines have different departure times. The aim of the numbering of destinations is to distinguish each dispatch.

29

Table 3-1 General information of the selected airports

DetailBirmingham Brisbane Hong Kong (Chek Lap Kok) Melbourne Orlando

Year built - 1925 1989 - -Location 13 km South East the city 13 km from CBD in an island, 25 km West of Hong

Kong city, 23 minutes from downtown

25 km from city centre, 30minutes by car

-

Access modes train, bus, coach, car, taxi, hire car

coach, taxi, train ferry, public buses, taxi, coach, hotel limousine, private car

car, taxi, bus rental car, bus, taxi, shutle bus

Terminal area 2088 sqm (departure concourse) - - -

0.4 million sqm

Airport area - 2700 ha 1255 ha 2369 ha 6075 haService commenced 1939 1964 1998 1970 1970International open 1984 1995 1998 - 1976Volume (passengers/year) 7.8 million (2001), 8 million

(2002)2.5 million (international),

10.5 million (domestic) -

in year 1998

34 million in 2002 (expected 45million, ultimate 87 million)

3.36 million

(international), 13.56

million (domestic) in 2002

26.750 million

Number of airlines served 40 27 60 31 49Traffic volume 250 Air Traffic Movement/day, - 49 Air Traffic Movements per

hour187Air Traffic Movement per day

790 Air Traffic Movement per day

19,000 passengers/dayAwards -Best UK Bussiness Airport in

2000 (4 times in 6 years)

-

-Best Airport, voted by TTG Asiaand TTG China, October 2002

-Top 10 World Airport by Bussiness Traveller Magazine, 2000,1999,1998,1997,1996

-Number One inPassengers Satisfactionvoted by FrequentTravellers, November2000

-Most Improved Airport -Runner up at The globalAirport Service ExelenceAward, November 2001

- Eagle Award from IATA, June2002

-Victorian Tourism AwardHall of Fame, 2000

-Best Bussiness Terminus- 5times in 9 years (in UK), 2002

- Merit Award for Exellence fromAVSECO at Edith CowanUniversity in Perth, June 2002

-Australian TourismAward, 2000, 1998

-World's Best Airport 2002, votedby passengers around the world.

-Cargo Airport of The Year-January 2002, by London basedAir Cargo News

Website www.bhx.co.uk www.brisbaneairport.com.www.hkairport.com www.melbourne-airport.com.auwww.orlandoairports.net/goaa/main.htm

Airport

3 Data Collection

30

Table 3-2 Data example.

23456789

1011121314151617181920212223242526

A B C D E F G H I J KNO. DESTINATION

100% 80% 1 2 3 4 5 6 71 Aberdeen1 70 56 8:45 8:45 8:45 8:45 8:452 Aberdeen2 70 56 10:103 Aberdeen3 70 56 13:154 Aberdeen4 70 56 15:10 15:10 15:10 15:10 15:105 Aberdeen5 70 56 18:30 18:30 18:30 18:30 18:30 18:056 Alicante 130 104 16:007 Amsterdam1 95 76 6:10 6:10 6:10 6:10 6:10 6:10 6:108 Amsterdam2 130 104 6:45 6:45 6:45 6:45 6:459 Amsterdam3 95 76 8:15 8:15 8:15 8:15 8:15 8:15 8:15

10 Amsterdam4 78 62 10:1511 Amsterdam5 130 104 10:45 10:45 10:45 10:45 10:4512 Amsterdam6 95 76 10:55 10:55 10:55 10:55 10:55 10:55 10:5513 Amsterdam7 78 62 12:0514 Amsterdam8 78 62 12:30 12:30 12:30 12:30 12:3015 Amsterdam9 95 76 12:35 12:35 12:3516 Amsterdam10 95 76 15:00 15:00 15:00 15:00 15:00 15:00 15:0017 Amsterdam11 130 104 16:3018 Amsterdam12 95 76 17:50 17:50 17:50 17:50 17:50 17:5019 Amsterdam13 78 62 18:1020 Amsterdam14 95 76 19:10 19:10 19:10 19:10 19:10 19:1021 Arrecife 185 148 9:2522 Ashkhabad 185 148 18:20 9:30 12:00 17:4523 Barcelona 124 99 10:35 10:35 10:35 10:35 10:35 10:35 10:35

PASSENGERS DAY DEPARTURE & TIME

215216217218219220221222223224225226

A B C D E F G H I J K212 Tenerife2 185 148 19:40213 Toronto1 185 148 8:10214 Toronto2 250 200 12:55215 Toulouse1 78 62 9:55 9:55 9:55 9:55 9:55216 Toulouse2 71 57 14:30217 Vienna1 78 62 8:40 8:40 8:40 8:40 8:40 8:40218 Vienna2 78 62 12:15219 Vienna3 78 62 14:40 14:40 14:40 14:40 14:40220 Zurich1 44 35 7:00 7:00 7:00 7:00 7:00 7:00221 Zurich2 50 40 10:15 10:15 10:15 10:15 10:15222 Zurich3 50 40 15:50 15:50 15:50 15:50 15:50 15:50223 Zurich4 50 40 15:50

31

Column C indicates the capacity of the aircraft. In reality, seldom the aircraft flies with a full capacity or 100% of seats occupied. For this reason, the number of passenger per aircraft is factored by 80% as seen in column D. This is a constant selected for passenger load factor. In real situation, the passenger load factor is likely to be variable. The process of changing the number of passengers based on load factor is automatically done in the computer model. The user is only required to fill the 100% capacity. However, if the user has a different assumption, the load factor can be changed.

The columns E to K describe the departure time for each day. The columns are sub headed by numbers from 1 to 7. 1 means Monday, 2 means Tuesday, and so on. Thus, 7 means Sunday. These days represent departure day. This information is useful to shows that each day has a different distribution of time.

The flight schedule is stored in spreadsheet form. The computer program makes use of Excel functions to estimate passenger arrival distribution that match the aircraft schedule given as input. Details of passenger distribution estimation is presented in the next chapter.

The other data acquired from airports are average service time, number of check-in desks, queue system, and number of hours advised to allow for passengers. These are summarized in Table 3-3.

Table 3-3 Queue Data Summary

Airport Number of Check-in

Desks

Type of Check-in

Desks Queue System

Average Service

Time (min:sec)

Number of Hours

Allowed to Check-in

Birmingham 70 N/A N/A 2:10 2:15 Brisbane N/A N/A N/A N/A N/A

Hong Kong 288 N/A N/A 3:18 N/A

Melbourne 88 N/A N/A N/A N/A

Orlando N/A Pass through Snake line 4:30 2 to 3

3.4 SUMMARY A data collection process is followed to understand system properties that could be input to the proposed model. During this process, air transport organizations were contacted. These organizations were IATA, FAA, ICAO and ACI. The data collection process also contained exploring airport websites. In addition, e-mail correspondence were made with the airport authorities.

Data obtained from the airports are flight schedules, service time, number of check-in counters, type of the check-in desk, and queue system applied.

3 Data Collection

32

The flight schedules provide information about aircraft type and aircraft departure time. The aircraft type provided an indication of the capacity of the aircraft. Aircraft capacity and load factor concept was applied to determine the number of departing passengers. From departure time and number of departing passengers, the frequency distribution for passenger arrivals can be derived by adopting IATA earliness distribution. The proposed software program for this purpose is presented in the next chapter.

33

4.1 INTRODUCTION The proposed model requires data input related to passenger arrival. Data collection process presented in the previous chapter has shown that information regarding the passenger arrival is unlikely to be readily available. To have this information, the project decided to synthesize passenger distribution in realistic ways. This chapter discusses the process of estimating the passenger arrival distribution.

As explained in Section 2.2.1, IATA gives an example of arrival earliness distribution (refer to Figure 2.2). The figure shows the percentage of passengers that arrives at a particular time before scheduled departure time. The available data is about flight schedules as presented in Table 3-2, and the advised number of hours for check-in (Table 3-3). To determine the initial time passengers start to arrive for a particular departure flight, this project adopts the advised number of hours for check-in as a reference. This reference is significant since the IATA pattern of arrival distribution is for domestic passengers, which has a different initial time of passenger arrival. More detail concerning this initial time is available in section 4.3. Based on this concept, distribution of each schedule is developed by applying the IATA pattern. The following sections explain details of this transformation process.

To explain the transformation process, this chapter starts with the concept of the process. This chapter also reviews the IATA pattern and supporting references to have a better understanding regarding this earliness distribution. Following this review is a section describing program development to accommodate the process of spreading passengers of each scheduled flight to an arrival distribution. Explanation regarding program execution is available in a subsequent section. The last section presents synthesized passenger arrival distribution estimated in this project.

4.2 THE CONCEPT The basic concept in estimating passenger arrival distribution is transforming the available passenger count data into a description of demand profile. As mentioned before, important factors regarding the passenger arrival distribution are flight schedule and number of hours advised for check-in. The flight schedules provide information about departure time and aircraft type for each scheduled dispatch. The

Estimation of Arrival

Distribution

4 Estimation of Arrival Distribution

34

aircraft type gives an indication of the seat capacity. The flight schedules can be now written in a slightly different format as shown in top left corner of Figure 4.1.

The earliness distribution obtained from IATA is referred to here as the IATA pattern. An example of the IATA pattern is at the lower left hand side of Figure 4.1.

The number of passengers for each flight schedule then is drawn out according to the IATA pattern to obtain passenger arrival distribution. In distributing passengers, it is important to link the departure time to the appropriate pattern. As shown in Figure 4-2, there are three different patterns depending on the time of day. Arrival distributions for all scheduled flights during the day are distributed and summed up to obtain the daily passenger distribution. The program computes the average of passenger arrival distribution at a particular time for a particular airport after obtaining all daily distributions over the week,

Figure 4-1 Methodology of synthesizing passenger arrival distribution

4.3 IATA DISTRIBUTION OF ARRIVAL EARLINESS IATA, in Airport Terminal Reference Manual (1989), provides an example pattern of arrival earliness at check-in as shown in Table 4-1 and Figure 4-2. Figure 4-2 is a reproduction of Figure 2-2 for convenience of reading this chapter. Table 4-1 shows the passenger flow rate at check-in desks. The tabulation provides arriving passengers at intervals of ten minutes before departure time. The table also shows that the pattern will be different depending on the time of day. There are three

DESTINATION NUMBER OF PASSENGERS DEPARTURE

TIME

Aberdeen 56 15:10

Amsterdam 76 6:10

Barcelona 99 10:35

Flight Schedules

Passenger Arrival Distribution

Earliness Distribution

Arrival Earliness Distribution

0%5%

10%15%20%25%30%

-2:50 -2:40 -2:30 -2:20 -2:10 -2:00 -1:50 -1:40 -1:30 -1:20 -1:10 -1:00

Arrival time (minutes) before departure flight

Perc

enta

ge

Monday

050

100150

200250

300

0:00

1:40

3:20

5:00

6:40

8:20

10:0

0

11:4

0

13:2

0

15:0

0

16:4

0

18:2

0

20:0

0

21:4

0

23:2

0

Time arrival

Num

ber o

f Pas

seng

ers

35

different periods applied, i.e.: from 06.00 to 10.00, 10.00 to 18.00, and 18.00 to 24.00. For example, for a flight scheduled at 11.10, the pattern adopted is the one that is valid for period from 10.00 to 18.00. The table does not provide a pattern for flights scheduled in the 00.00 to 06.00 period. The pattern for this period is assumed to be same as the 06.00-10.00 pattern.

Table 4-1 IATA pattern of arrival earliness

(Source: IATA, 1989)

Time of day

Percentage arrival of passengers at the check-in counters by 10 minutes periods prior to flight departure

120-110

110-100

100-90

90-80

80-70

70-60

60-50

50-40

40-30

30-20

20-10

10-0

06.00-10.00 0 0 1 2 6 10 20 26 20 12 3 0

10.00-18.00

0 1 3 8 11 15 17 18 15 10 2 0

18.00-24.00

3 4 6 9 11 14 15 15 15 7 1 0

Figure 4-2

IATA arrival earliness distribution (Source: IATA, 1989)

The arrival pattern in Table 4-1 and Figure 4-2 is for a domestic flight. The figure

shows that the last passenger arrives 10 to 20 minutes before departure time. This situation is impractical for international flights since international flights require longer processing times. Thus, this project adjusts the available distribution.

Ashford (1984) presented the comparison of passenger arrival. There is a difference of passenger arrival earliness for international and domestic flights. According to Ashford, for international flights, the last passengers should arrive 60 minutes before departure time. For domestic flights, the passengers may arrive much later. Passengers for international flights are required to arrive early since there is further processing such as immigration checks. In some countries,

0%

5%

10%

15%

20%

25%

30%

-2:50 -2:40 -2:30 -2:20 -2:10 -2:00 -1:50 -1:40 -1:30 -1:20 -1:10 -1:00

Arrival time (hour:minutes) before departure flight

Perc

enta

ge

0:006:0010:0018:00

4 Estimation of Arrival Distribution

36

passengers may be also required to pay certain charges and duties. There could be also quarantine and customs checks in some regions.

In Table 4-1, the last passengers arrive at 10 20 minutes before departure time. That was for a domestic flight. To prepare the distribution for an international flight, the program shifts the passenger flow rates by an amount of 40 minutes earlier to these times. These shifts are applied to all periods as shown in Table 4-2 and Figure 4-3.

This project converts the flight schedule data presented in Table 3-2 to passenger arrival distribution with the patterns presented in Figure 4-3.

Table 4-2

Adjusted times of departing international passenger arrival pattern

0%

5%

10%

15%

20%

25%

30%

-2:50 -2:40 -2:30 -2:20 -2:10 -2:00 -1:50 -1:40 -1:30 -1:20 -1:10 -1:00Arrival time (hour:minutes) before departure flight

Perc

enta

ge 0:006:0010:0018:00

Figure 4-3

Adjusted patterns of arrival of international passengers

4.4 PASSENGER DISTRIBUTION PROGRAM DEVELOPMENT This computer program is aimed to compute the appropriate passenger arrival distribution. The program is developed by utilizing excel spreadsheet functions. The program consists of 5 worksheets: Arrival distribution, Input data, Daily distribution, Summarize, and Chart. The Arrival distribution worksheet contains the shifted IATA pattern as shown in Table 4-2. The Input data worksheet accommodates the flight schedule data as presented in Table 3-2. The Daily distribution worksheet is designed to facilitate the distribution process. The Summarize worksheet accommodates results after averaging process for the whole week. The last worksheet is the Chart worksheet that pictures the passenger distribution. Figure 4-5 describes the process.

The process starts with application of the appropriate earliness pattern for each flight schedule. After all scheduled flight departures in a particular day have been converted to passenger arrival patterns, the next step is summation of the number of passengers at a particular time. Sub section 4.4.3 explains this process in more

Period After

-2:50 -2:40 -2:30 -2:20 -2:10 -2:00 -1:50 -1:40 -1:30 -1:20 -1:10 -1:00 -0:50 -0:400:00 0% 0% 0% 1% 2% 6% 10% 20% 26% 20% 12% 3% 0% 0%6:00 0% 0% 0% 1% 2% 6% 10% 20% 26% 20% 12% 3% 0% 0%

10:00 0% 0% 1% 3% 8% 11% 15% 17% 18% 15% 10% 2% 0% 0%18:00 0% 3% 4% 6% 9% 11% 14% 15% 15% 15% 7% 1% 0% 0%

Time before departure

37

detail. The daily summary accommodates the totals of passengers arrival in each time in a day (sub section 4.4.4). The average of those results is determined by completing the daily processes for a week.

The program developed can be applicable to any airport as the flight schedules from any airport can be loaded into the Input data worksheet. In addition, the earliness distribution may follow the trend at a particular airport if such information is already available. These points are explained more detail in the discussions of each worksheet.

Figure 4-4 Flow chart in preparing passenger arrival distribution

4.4.1 Arrival Distribution Worksheet The Arrival distribution worksheet is designed to accommodate the arrival earliness patterns. Table 4-2 is an example of the arrival earliness distribution used in this worksheet. Table 4-3 presents a similar table as Table 4-2, but in worksheet format. Column A in Table 4-3 represents the start time of the departure period for each pattern. Column B is the pattern number. The pattern number represents a different pattern depending on the time of day. The aim of this numbering is to simplify the program when selecting the corresponding pattern. The fourth row of columns C to P indicates hours and minutes before departure time. The fifth row to the eighth row and columns C to P, show the percentage of passengers arrival. Zero percent means that no passengers arrive at this particular time.

Sum up the total passengers at a particular time increment

Daily process

Flight schedules

Find appropriate pattern

Place the results in daily summary

Repeat for a week

Determine the average count of passengers at a particular time Final process

4 Estimation of Arrival Distribution

38

The values in table 4-3, i.e.: the period, the time before departure, and percentage, can be modified depending on the planner knowledge. The important thing is that the total of each row for columns C to P add up to 100%.

Table 4-3

Arrival distribution worksheet

4.4.2 Input Data Worksheet This worksheet (Table 4-4 column A, B, and C) contains the same table as Table

3-2. This worksheet is assigned to accommodate the flight schedule. In this worksheet, the occupancy level per aircraft (column C) can be changed depending on the planner assumptions. The program adopts flight schedule in this worksheet to obtain daily passenger distribution. The passenger distribution is processed in the next worksheet.

4.4.3 Daily Worksheet The daily worksheet facilitates the passenger arrival distribution for one day. Table

4-4 shows the heading lines of this worksheet and a single row (row 183) related the Munich flight. This example is for day 6 (cell D3), Saturday.

For example, flight to Munich (row 183) departs on Saturday at 6:40. The number of passengers in this flight is 57 passengers. Arrival passenger distribution for this particular flight follows the second pattern of arrival earliness pattern (refer to Table 4-3). The passenger arrival distribution (cells AV183 to BD183) shows that passengers start to arrive at 4:20 and the last passenger arrives at 5:40, one hour before departure time. The number of passengers at a particular time follows the percentage given in the corresponding pattern (pattern number 2 in this example or cell E183).

Table 4-4 Example for passenger arrival distribution

Table 4-5 shows a larger portion of this worksheet. This has columns up to FI, and

goes up to row 226. The large table is expected to accommodate all flights and their passengers.

1

45678

A B C D E F G H I J K L M N O P Q

Period After #Tbl -2:50 -2:40 -2:30 -2:20 -2:10 -2:00 -1:50 -1:40 -1:30 -1:20 -1:10 -1:00 -0:50 -0:40

0:00 1 0% 0% 0% 1% 2% 6% 10% 20% 26% 20% 12% 3% 0% 0% 100%6:00 2 0% 0% 0% 1% 2% 6% 10% 20% 26% 20% 12% 3% 0% 0% 100%

10:00 3 0% 0% 1% 3% 8% 11% 15% 17% 18% 15% 10% 2% 0% 0% 100%18:00 4 0% 3% 4% 6% 9% 11% 14% 15% 15% 15% 7% 1% 0% 0% 100%

Time before departure

123

183

A B C D E F AR AS AT AU AV AW AX AY AZ BA BB BC BD BE BF5263 0 1 2 7 14 30 49 76 100 108 99 84 70 73 78

No. DESTINATION PASS. DAY Tbl 80% 6 5263 3:40 3:50 4:00 4:10 4:20 4:30 4:40 4:50 5:00 5:10 5:20 5:30 5:40 5:50 6:00

180 Munich1 57 6:40 2 57 0 0 0 1 1 3 6 11 15 11 7 2 0 0

39

Columns A C are the same as in Table 3-2 These columns are aimed to accommodate all available flight schedules in a particular airport. Thus, during the program execution, the user does not have to repeatedly input the schedules. Column D shows the departure time for each destination in a particular day. Cell D3 is the day number. Day number corresponds to day of the week as mentioned in section 4.3. This number can be changed from the Summarize worksheet to select a different day.

Table 4-5 Daily distribution

The time in column D is rounded down to the nearest ten minutes. This is applied

to this column to simplify the distribution process since the earliness distributions are in ten-minute intervals. The time shown in this column is only the schedules for the corresponding day. In other words, blank cells mean no scheduled flights for those destinations on that day.

Column E is for the earliness pattern number. The pattern number shown in the column means that the flight schedule is distributed according to the corresponding pattern in the Arrival Distribution worksheet. For example, if in column D the time shown is 6:10, the distribution pattern in column E is pattern number 2 (refer to Table 4-3). The computer executes the pattern number selection automatically. In other words, this worksheet has been programmed to select the pattern based on the departure time.

The total number of passengers for each destination is in column F. The figure in column F will be generally the same as the figure in column C. The value in these two columns could be different because of rounding down in the distribution process. Besides, the figure in column F will be zero if there is no flight in the day observed. The total number of passengers of the particular day is shown in two places in cells F1 and F3. Cell F1 is for the total number in the first row, cell F3 is for the total number in column F. These two cells are there for cross checking the total number of passengers. The matrix in cells from G4 to FI 226 is allocated to accommodate the passenger distribution.

2 2 12 2 22 2 32 2 42 2 52 2 6

A B C D E F G H F F FG F H F I2 1 8 V ienna 2 6 2 02 1 9 V ienna 3 6 2 02 2 0 Z u rich1 3 5 7 :0 0 2 3 5 0 0 0 02 2 1 Z u rich2 4 0 02 2 2 Z u rich3 4 0 02 2 3 Z u rich4 4 0 1 5 :5 0 3 3 9 0 0 0 0

123456789

1 01 1

A B C D E F G H F F F G F H F I5 2 6 3 0 0 0 0 0 0

N o . D E S T IN A T IO N P A S S . D A Y T b l T IM E8 0 % 6 5 2 6 3 -2 :3 0 -2 :2 0 2 3 :2 0 2 3 :3 0 2 3 :4 0 2 3 :5 0

1 A b e rd e en 1 5 6 02 A b e rd e en 2 5 6 03 A b e rd e en 3 5 6 1 3 :1 0 3 5 6 0 0 0 04 A b e rd e en 4 5 6 05 A b e rd e en 5 5 6 06 A lica n te 1 0 4 1 6 :0 0 3 1 0 4 0