Agent based modelling and simulation of airplane boarding processes

AGENT-BASED MODELLING AND SIMULATION OF AIRPLANE BOARDING PROCESSES Serter IYIGUNLU Submitted in fulfilment of the requirements for the degree of Master of Engineering (Research) Science and Engineering Faculty Queensland University of Technology April 2015 Agent-based Modelling and Simulation of Airplane Boarding Processes i Agent-based Modelling and Simulation of Airplane Boarding Processes ii Keywords Agent-based model Aircraft boarding Airport operation Pedestrian model Simulation Agent-based Modelling and Simulation of Airplane Boarding Processes iii Abstract Passenger movements in an airport are representative of the drivers behind a city’s function including economic development, business, tourism and trade A major factor, which can influence these passenger movements, is the passenger experience, which is now an essential aspect of an airport’s success Passenger flow simulations are becoming an increasingly important tool for designing and managing airports and lead to a better understanding of the factors that impact upon passengers and, ultimately their movements A review of the literature reveals aircraft-boarding time is a major factor that influences an airline’s efficiency However, most research has failed to consider actual boarding strategies in larger aircraft like Boeing 777 or Airbus 380, which now transport hundreds of millions of passenger globally In order to reflect more realistic boarding strategies, larger aircraft must be included in the analysis of these strategies, to allow opportunities to develop new and more efficient strategies An Airplane’s Turn Time is described as the time needed to empty an airplane after its arrival at the gate and to make all preparations for its next departure Factors contributing to Turn Time are usually divided into seven groups, which are disembarkation, baggage unloading, refuelling the aircraft, cargo unloading, aircraft maintenance, cargo and baggage loading and passenger boarding (Soolaki, Mahdavi, Mahdavi-Amiri, Hassanzadeh, & Aghajani, 2012) Passenger boarding is a major factor that impacts upon the overall Turn Time, and improvements to passenger boarding can create significant improvements in airline efficiency An agent-based simulation model (ABS) is a practical and productive approach to design passenger flows in airports Using ABS, this thesis proposes a new set of boarding strategies to reduce the overall boarding time and thus improve airline efficiency ABS allows the actual interaction between passengers and their luggage to be explicitly modelled Agent-based Modelling and Simulation of Airplane Boarding Processes iv For airline operators, the model also provides a convenient way to investigate the effectiveness of the boarding method, which may contribute to improved passenger airport experiences This thesis analyses existing boarding methods utilised by airlines and proposes new boarding methods for both the Airbus 380 and the Boeing 777 aircraft The most optimal strategies have been discovered and new strategies that are more efficient are proposed The conducted experiments explicitly model group behaviour and stowing luggage in the boarding process under an agent-based simulation and modelling framework All existing and new proposed boarding methods have been developed using AnyLogic simulation software Agent-based Modelling and Simulation of Airplane Boarding Processes v Table of Contents KEYWORDS III ABSTRACT IV TABLE OF CONTENTS VI LIST OF FIGURES VIII LIST OF TABLES XI STATEMENT OF ORIGINAL AUTHORSHIP XIII ACKNOWLEDGEMENTS XIV INTRODUCTION 1.1 1.2 1.3 1.4 1.5 BACKGROUND KNOWLEDGE GAP RESEARCH AIMS AND SCOPE METHODOLOGY THESIS OUTLINE LITERATURE REVIEW 2.1 OVERVIEW 2.2 THE NEED FOR MODELLING AIRCRAFT BOARDING 2.3 AIRCRAFT BOARDING INVESTIGATION TECHNIQUES 10 2.3.1 Simulation Models 10 2.4 AIRCRAFT BOARDING METHODS AND AIRCRAFT BOARDING SIMULATION SOFTWARE 20 2.5 GAPS AND OPPORTUNITIES –AIRCRAFT BOARDING STRATEGIES 31 2.6 CHAPTER SUMMARY 32 DEVELOPING AGENT-BASED SIMULATION OF BOARDING METHODS FOR AIRBUS 380 AND BOEING 777-200 AIRCRAFT TYPES 34 3.1 INTRODUCTION 34 3.2 PEDESTRIAN CHARACTERISTICS 34 3.3 SIMULATION DEVELOPMENT 36 3.3.1 Flow Rate 41 3.3.2 Hand Luggage Distribution 41 3.4 AIRCRAFT BOARDING METHODS 42 3.4.1 Boeing 777-200 Boarding Methods 43 3.4.2 Comparison of Boeing 777 Boarding Methods 67 3.4.3 Airbus A380 Boarding Methods 68 3.4.4 Comparison of Airbus 380 Boarding Methods 92 3.4.5 Comparison of Results for Boeing 777-200 versus Airbus 380 Boarding Methods 93 3.5 CHAPTER SUMMARY 95 PROPOSED NEW BOARDING METHODS 97 4.1 INTRODUCTION 97 4.2 NEW BOARDING METHODS FOR BOEING 777-200 AND AIRBUS 380 98 4.2.1 Aisle Boarding First Method 98 4.2.2 Row Arrangement Method 101 4.2.3 Row Blocks Method 104 4.2.4 Row Jump Method 108 4.2.5 Row Middle Method 111 4.2.6 Window First Method 114 4.2.7 Aisle Seats First Method 118 4.2.8 Middle Seats First Method 121 4.2.9 Jump Seats Method 124 4.3 AIRLINE TURN AROUND TIME CALCULATION AND COMPARISON FOR THE BOARDING METHODS 127 Agent-based Modelling and Simulation of Airplane Boarding Processes vi 4.4 CHAPTER SUMMARY 130 CONCLUSIONS 131 5.1 5.2 5.3 5.4 5.5 INTRODUCTION 131 THESIS SUMMARY 131 RESEARCH AND CONTRIBUTION 133 RESEARCH LIMITATIONS 135 RECOMMENDATIONS 135 REFERENCES 137 Agent-based Modelling and Simulation of Airplane Boarding Processes vii List of Figures FIGURE 1.1 ILLUSTRATION OF INTERNATIONAL TOTAL PASSENGER CARRIED BY MONTH (AUSTRALIAN GOVERNMENT DEPARTMENT OF INFRASTRUCTURE AND REGIONAL DEVELOPMENT, 2014) FIGURE 2.1 AIRPLANE TURN TIME EXPLANATION (LANDEGHEM & BEUSELINCK, 2002) FIGURE 2.2 PEDESTRIAN MOVING ON A GRID (KÖSTER, ET AL., 2011) 13 FIGURE 2.3 AGENT-BASED MODELLING SOFTWARE [MACAL AND NORTH AS CITED IN (MA, 2013)] 19 FIGURE 2.4 WILMA BOARDING METHOD ILLUSTRATION 26 FIGURE 2.5 REVERSE PYRAMID BOARDING METHOD ILLUSTRATION 27 FIGURE 2.6 STEFFEN BOARDING METHOD ILLUSTRATION 27 FIGURE 2.7 BLOCKS BOARDING METHOD ILLUSTRATION 28 FIGURE 2.8 BY LETTER BOARDING METHOD ILLUSTRATION 29 FIGURE 2.9 SEAT (ABOVE) AND AISLE (BELOW) INTERFERENCES (EMILIO, ET AL., 2008) 30 FIGURE 3.1 BOEING 777-200(ABOVE) AND AIRBUS 380 (BELOW) LAYOUTS FIGURES SHOW SEAT CONFIGURATION OF THESE AIRCRAFTS A380 IS A DOUBLE-DECK AIRCRAFT 37 FIGURE 3.2 BOARDING PROCESS SCREENSHOTS SCREENSHOTS SHOW THE BOEING 777 BOARDING PROCESS 40 FIGURE 3.3 BOARDING PROCESS SCREENSHOTS SCREENSHOTS SHOW THE AIRBUS 380 BOARDING PROCESS 41 FIGURE 3.4 AIRCRAFT BOARDING SIMULATION PROCESS 43 FIGURE 3.5 WILMA METHOD BOARDING TIMES WITH STANDARD DEVIATION ON BOEING 777-200 45 FIGURE 3.6 WILMA METHOD PASSENGERS’ DELAY IN THE AISLES ON THE BOEING 777-200 45 FIGURE 3.7 WILMA METHOD - EACH PASSENGER’S BOARDING TIMES ON BOEING 777-200 46 FIGURE 3.8 WILMA METHOD - PASSENGERS’ WAITING TIMES ON BOEING 777-200 46 FIGURE 3.9 WILMA METHOD PASSENGERS’ DENSITY MAP ON BOEING 777-200 47 FIGURE 3.10 STEFFEN METHOD - BOARDING TIMES ON BOEING 777-200 49 FIGURE 3.11 STEFFEN METHOD AISLES DELAY TIME ON BOEING 777-200 49 FIGURE 3.12 STEFFEN METHOD PASSENGERS’ WAITING TIME IN THE QUEUES ON BOEING 777-200 50 FIGURE 3.13 STEFFEN METHOD PASSENGERS’ DENSITY MAP ON THE BOEING 777-200 51 FIGURE 3.14 RANDOM METHOD BOARDING TIMES ON BOEING 777-200 53 FIGURE 3.15 RANDOM METHOD- AISLE DELAY TIMES ON THE BOEING 777-200 53 FIGURE 3.16 RANDOM METHOD - EACH PASSENGER’S BOARDING TIME ON BOEING 777-200 54 FIGURE 3.17 RANDOM METHOD QUEUE WAITING TIMES ON BOEING 777-200 55 FIGURE 3.18 RANDOM METHOD PASSENGERS’ DENSITY MAP ON BOEING 777-200 55 FIGURE 3.19 BLOCKS METHOD - BOARDING TIMES ON THE BOEING 777-200 57 FIGURE 3.20 BLOCKS METHOD - AISLE DELAY TIME ON THE BOEING 777-200 58 FIGURE 3.21 BLOCKS METHOD - EACH PASSENGER’S BOARDING TIME ON THE BOEING 777-200 58 FIGURE 3.22 BLOCKS METHOD - QUEUE WAITING TIME ON THE BOEING 777-200 59 FIGURE 3.23 BLOCKS METHOD - PASSENGERS’ DENSITY MAP ON BOEING 777-200 59 FIGURE 3.24 BACK – TO - FRONT METHOD BOARDING TIMES ON THE BOEING 777-200 61 FIGURE 3.25 BACK- TO- FRONT METHOD- AISLE DELAY TIME ON THE BOEING 777-200 61 FIGURE 3.26 BACK- TO- FRONT METHOD - EACH PASSENGER’S BOARDING TIME ON THE BOEING 777-200 62 FIGURE 3.27 BACK- TO -FRONT METHOD QUEUE WAITING TIME ON THE BOEING 777-200 62 FIGURE 3.28 BACK -TO -FRONT METHOD- PASSENGERS’ DENSITY MAP ON THE BOEING 777-200 63 FIGURE 3.29 BY -LETTER METHOD- BOARDING TIMES ON THE BOEING 777-200 64 FIGURE 3.30 BY LETTER METHOD AISLE DELAY TIME ON THE BOEING 777-200 65 FIGURE 3.31 BY-LETTER METHOD - EACH PASSENGER’S BOARDING TIME ON THE BOEING 777-200 65 FIGURE 3.32 BY - LETTER METHOD - QUEUE WAITING TIME ON THE BOEING 777-200 66 FIGURE 3.33 BY- LETTER METHOD- PASSENGERS’ DENSITY MAP ON THE BOEING 777-200 66 FIGURE 3.34 WILMA METHOD- BOARDING TIMES ON AIRBUS 380 69 FIGURE 3.35 WILMA METHOD- AISLE DELAY TIMES ON AIRBUS 380 69 FIGURE 3.36 WILMA METHOD- EACH PASSENGER’S BOARDING TIME ON AIRBUS 380 70 FIGURE 3.37 WILMA METHOD- QUEUE WAITING TIMES ON THE AIRBUS 380 71 FIGURE 3.38 WILMA METHOD PASSENGERS’ AISLE DENSITY ON AIRBUS 380 72 FIGURE 3.39 STEFFEN METHOD BOARDING TIMES ON AIRBUS 380 73 FIGURE 3.40 STEFFEN METHOD -AISLE DELAY TIMES ON AIRBUS 380 74 FIGURE 3.41 STEFFEN METHOD -EACH PASSENGER’S BOARDING TIME ON AIRBUS 380 74 Agent-based Modelling and Simulation of Airplane Boarding Processes viii FIGURE 3.42 STEFFEN METHOD- QUEUE WAITING TIMES ON AIRBUS 380 75 FIGURE 3.43 STEFFEN METHOD- PASSENGERS’ AISLE DENSITY ON AIRBUS 380 76 FIGURE 3.44 RANDOM METHOD -BOARDING TIMES ON THE AIRBUS 380 77 FIGURE 3.45 RANDOM METHOD- AISLE DELAY TIME ON AIRBUS 380 78 FIGURE 3.46 RANDOM METHOD - EACH PASSENGER’S BOARDING TIME ON AIRBUS 380 78 FIGURE 3.47 RANDOM METHOD -QUEUE WAITING TIMES ON AIRBUS 380 79 FIGURE 3.48 RANDOM METHOD -PASSENGERS’ AISLE DENSITY ON AIRBUS 380 80 FIGURE 3.49 BLOCKS METHOD- BOARDING TIMES ON THE AIRBUS 380 81 FIGURE 3.50 BLOCKS METHOD -AISLE DELAY TIMES ON AIRBUS 380 82 FIGURE 3.51 BLOCKS METHOD- EACH PASSENGER’S BOARDING TIME ON AIRBUS 380 82 FIGURE 3.52 BLOCKS METHOD -QUEUE WAITING TIMES ON THE AIRBUS 380 83 FIGURE 3.53 BLOCKS METHOD -PASSENGERS’ AISLE DENSITY ON AIRBUS 380 84 FIGURE 3.54 BACK- TO- FRONT METHOD- BOARDING TIMES ON AIRBUS 380 85 FIGURE 3.55 BACK - TO - FRONT METHOD - AISLE DELAY TIMES ON THE AIRBUS 380 86 FIGURE 3.56 BACK – TO - FRONT METHOD - EACH PASSENGER’S BOARDING TIME ON AIRBUS 380 86 FIGURE 3.57 BACK - TO - FRONT METHOD - QUEUE WAITING TIMES ON AIRBUS 380 87 FIGURE 3.58 BACK – TO - FRONT METHOD - PASSENGERS’ AISLE DENSITY ON AIRBUS 380 88 FIGURE 3.59 BY LETTER METHOD BOARDING TIMES ON THE AIRBUS 380 89 FIGURE 3.60 BY- LETTER METHOD - AISLE DELAY TIMES ON THE AIRBUS 380 90 FIGURE 3.61 BY- LETTER METHOD -EACH PASSENGER’S BOARDING TIME ON THE AIRBUS 380 90 FIGURE 3.62 BY -LETTER METHOD - QUEUE WAITING TIMES ON THE AIRBUS 380 91 FIGURE 3.63 BY -LETTER METHOD - PASSENGERS’ AISLE DENSITY ON AIRBUS 380 92 FIGURE 4.1 AISLE BOARDING FIRST ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND; SEAT TYPE ENTERS THE AIRCRAFT THIRD, AND SEAT TYPE ENTERS THE AIRCRAFT FORTH 98 FIGURE 4.2 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 99 FIGURE 4.3 AISLE BOARDING FIRST METHOD- QUEUE WAITING TIME FOR BOEING 777-200 100 FIGURE 4.4 AISLE BOARDING FIRST METHOD - QUEUE WAITING TIME FOR AIRBUS 380 100 FIGURE 4.5 THE AISLE FIRST BOARDING METHODS ‘AISLE DENSITY MAP FOR THE BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 101 FIGURE 4.6 ROW ARRANGEMENT METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND, AND SEAT TYPE ENTERS THE AIRCRAFT THIRD 101 FIGURE 4.7 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 102 FIGURE 4.8 ROW ARRANGEMENT METHOD- QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380(BELOW) 103 FIGURE 4.9 THE ROW ARRANGEMENT BOARDING METHOD’S -‘AISLE DENSITY MAP FOR THE BOEING 777-200(ABOVE) AND AIRBUS 380(BELOW) 104 FIGURE 4.10 ROW BLOCKS METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND; SEAT TYPE ENTERS THE AIRCRAFT THIRD; SEAT TYPE ENTERS THE AIRCRAFT FOURTH, SEAT TYPE ENTERS THE AIRCRAFT FIFTH AND SEAT TYPE ENTERS THE AIRCRAFT SIXTH 105 FIGURE 4.11 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 106 FIGURE 4.12 ROW BLOCKS METHOD -QUEUE WAITING TIME FOR BOEING 777-200 AND AIRBUS 380 107 FIGURE 4.13 THE ROW BLOCKS BOARDING METHOD’S- ‘AISLE DENSITY MAP FOR THE BOEING 777-200(ABOVE) AND AIRBUS 380(BELOW) 108 FIGURE 4.14 ROW JUMP METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND 108 FIGURE 4.15 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 109 FIGURE 4.16 ROW JUMP METHOD - QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 110 FIGURE 4.17 THE ROW JUMP BOARDING METHOD’S- ‘AISLE DENSITY MAP FOR THE BOEING 777-200(ABOVE) AND AIRBUS 380(BELOW) 111 FIGURE 4.18 ROW MIDDLE METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND, AND SEAT TYPE ENTERS THE AIRCRAFT THIRD 112 FIGURE 4.19 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 112 FIGURE 4.20 ROW MIDDLE METHOD - QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 113 FIGURE 4.21 THE ROW MIDDLE BOARDING METHOD’S - ‘AISLE DENSITY MAP FOR THE BOEING 777-200(ABOVE) AND AIRBUS 380(BELOW) 114 FIGURE 4.22 WINDOW FIRST METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND, AND SEAT TYPE ENTERS THE AIRCRAFT THIRD 115 FIGURE 4.23 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 116 Agent-based Modelling and Simulation of Airplane Boarding Processes ix FIGURE 4.24 WINDOW FIRST METHOD - QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 117 FIGURE 4.25 THE WINDOW FIRST BOARDING METHODS ‘AISLE DENSITY MAP FOR THE BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 117 FIGURE 4.26 AISLE SEATS FIRST METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND, AND SEAT TYPE ENTERS THE AIRCRAFT THIRD 118 FIGURE 4.27 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 119 FIGURE 4.28 AISLE SEATS FIRST METHOD - QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 120 FIGURE 4.29 THE AISLE SEATS FIRST BOARDING METHOD’S - ‘AISLE DENSITY MAP FOR THE BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 120 FIGURE 4.30 MIDDLE SEATS FIRST METHOD ILLUSTRATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND, AND SEAT TYPE ENTERS THE AIRCRAFT THIRD 121 FIGURE 4.31 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 122 FIGURE 4.32 MIDDLE SEATS FIRST METHOD QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 123 FIGURE 4.33 THE MIDDLE SEATS FIRST BOARDING METHOD’S - ‘AISLE DENSITY MAP FOR THE BOEING 777-200 (ABOVE) AND AIRBUS 380(BELOW) 124 FIGURE 4.34 JUMP SEATS METHOD EXPLANATIONS SEAT TYPE ENTERS THE AIRCRAFT FIRST; SEAT TYPE ENTERS THE AIRCRAFT SECOND; SEAT TYPE ENTERS THE AIRCRAFT THIRD; SEAT TYPE ENTERS THE AIRCRAFT FOURTH, SEAT TYPE ENTERS THE AIRCRAFT FIFTH AND SEAT TYPE ENTERS THE AIRCRAFT SIXTH 124 FIGURE 4.35 COMPARISON OF AISLE DELAY TIMES FOR TWO DIFFERENT AIRCRAFT TYPES (BOEING 777-200 AND AIRBUS 380) 125 FIGURE 4.36 JUMP SEATS METHOD - QUEUE WAITING TIME FOR BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 126 FIGURE 4.37 THE JUMP SEATS BOARDING METHOD’S- ‘AISLE DENSITY MAP FOR THE BOEING 777-200 (ABOVE) AND AIRBUS 380 (BELOW) 127 Agent-based Modelling and Simulation of Airplane Boarding Processes x The literature has introduced different boarding strategies in order to reduce boarding time These methods are Wilma method, Reverse Pyramid, Steffen method, random method, blocks method, by letter method Chapter has detailed the existing boarding methods’ simulation modelling and their results At the beginning of the chapter, aircraft types’ layouts that were used in the simulation were demonstrated Passengers’ attributes such as gold-class passenger and, passengers with children, have been included in the simulation program Economy class passengers were divided into groups according to their seat numbers, for each type of boarding strategy The Reverse Pyramid method is the best boarding method for the Boeing 777 aircraft and the Steffen boarding method is the best boarding method for the Airbus 380 aircraft The Steffen boarding method minimises aisle interferences by ordering people by their seat letters not seat numbers The Reverse Pyramid boarding method is subjected to aisle and seat interferences but this boarding method begins from the rear of the aircraft, because of this, the congestion occurs in the rear of the aircraft so the incoming passengers are not overly affected by it For the Boeing 777 with 313 passengers, the lowest time is taken by the Reverse Pyramids strategy, which is 29.641 minutes Similarly, the lowest time for the Airbus 380 with 498 passengers is 39.643 minutes by using the Steffen boarding method The Airbus 380 takes a longer absolute boarding time than Boeing 777 However, the average time of boarding per passenger for Boeing 777 and Airbus 380 are 29.641/313=0.095 minutes and 39.643/498=0.079 minutes respectively This shows, if passenger numbers are equal then Airbus 380 will take on an average 24.916 minutes, which is lower than the Boeing 777 Chapter introduces nine new boarding methods in order to investigate further, find the best boarding time, and reduce Turn Time It compares boarding results for Chapter 5: Conclusions 132 two different aircraft types In the end, boarding simulation results shows the important part of a boarding method in order to reduce Turn Time and annual cost This chapter also compares the difference between the existing boarding strategies and the new boarding strategies The best boarding method for the Boeing 777 is aisle boarding first method and for the Airbus 380 is the row arrangement method 5.3 Research and Contribution The goal of this research is to build a boarding process model for the airport terminal environment in order to reduce turn-around time, thus providing a novel tool for airport managers and airlines to use to achieve better management at the airport This closely realises the research vision: “To provide a better boarding strategy for the continuous improvement of airline passengers and airlines." During this research, the answers to the following question were sought: 1.) What is the best boarding strategy? 2.) What aircraft types are currently modelled in existing strategies? 3.) How can more efficient boarding strategies be developed using agent-based modelling? 4.) What is the best method to explicitly model important factors in passenger boarding including group behaviour and stowing passenger luggage? The best boarding method differs from the aircraft models The researchers have mainly used one aisle aircraft in their research, with seat capacity up to 180 passengers In the research, an Anylogic simulation program has been used to develop boarding strategies Simulation programs allow you to develop a view that is Chapter 5: Conclusions 133 more realistic In addition to the existing boarding method, nine different boarding methods have been developed and examined Previous studies have a set of rules that include passenger’s optimal speed, a safe distance, and maximum speed but in fact, each passenger has different attributes The main contributions of this thesis are embodied in the following three aspects: Extending the seating capacity of the aircrafts in the simulation The literature review in Chapter demonstrates researches that have considered the aircraft seat capacity up to 180, and they have investigated the aircraft with one aisle only In the thesis, the seat capacity is extended to 498 seats and two aisle aircraft types Improve the delay times for passengers hand luggage issue The passengers’ hand luggage issue is the main cause of delay when considering the boarding strategies Passengers tend to carry one or two-piece of hand luggage during the boarding process In the thesis, the waiting time in the aisle is determined by the triangular distribution The minimum waiting time is seconds, average waiting time is 30 seconds and the maximum waiting time is 60 second in the aisles when the passenger put his/her luggage in the bins Reducing boarding time In the thesis, existing boarding methods and the new proposed boarding method were examined and analysed for long-haul aircraft types, such as Boeing 777 and Airbus 380 In the research of this thesis, passengers with children, first and business-class passengers and groups of passengers (four or more people) were considered first for boarding The Reverse Pyramid and the Steffen boarding Chapter 5: Conclusions 134 methods were found to be the best boarding methods for the Boeing 777 and Airbus 380 respectively Their boarding times are 29.641 and 39.463 minutes respectively The new proposed boarding methods have been introduced in order to reduce boarding time as well as the Turn Time The best boarding methods are aisle boarding first method and row arrangement method for the Boeing 777 and the Airbus 380 respectively The boarding times are 26.050 and 42.773 minutes respectively 5.4 Research Limitations The limitation of this thesis is the lack of access to detailed airport data, which leads to difficulties in model development, validation and calibration For agentbased models, the preciseness of decision-making procedures decides the dependability of the model Boarding methods have been investigated, since the airline sector has played a significant role in the transportation sector Due to security reasons, collecting sufficient data is difficult All research outcomes are still important and valuable; however, explicit validation is more challenging 5.5 Recommendations It is recommended that future research be undertaken in the following areas: 1.) Investigate long haul flight aircrafts Nowadays, international flights are playing important roles in the airline industry Future research should concentrate on other long haul flight aircraft such as Boeing 787 Dreamliner They should include new aircraft types in order to investigate aircraft boarding methods more broadly and with depth Chapter 5: Conclusions 135 Boeing 777 and Airbus 380 have been used for the existing boarding methods as well as the new proposed boarding methods 2.) 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ABMS Agent- based Modelling and Simulation ABS Agent- based Simulation CA Cellular Automata CAFE Cellular automata with Force Essentials Agent- based Modelling and Simulation of Airplane Boarding Processes. .. METHOD’S BOARDING TIMES 129 Agent- based Modelling and Simulation of Airplane Boarding Processes xi List of Abbreviations AAA Australian Airport Association ABM Agent- based Model/modelling