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An Integrative Assessment of the Commercial Air Transportation System Via Adaptive Agents

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AN INTEGRATIVE ASSESSMENT OF THE COMMERCIAL AIR TRANSPORTATION SYSTEM VIA ADAPTIVE AGENTS A Dissertation Presented to The Academic Faculty by Choon Giap Lim In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy School of Aerospace Engineering Georgia Institute of Technology December 2008 Copyright c 2008 by Choon Giap Lim AN INTEGRATIVE ASSESSMENT OF THE COMMERCIAL AIR TRANSPORTATION SYSTEM VIA ADAPTIVE AGENTS Approved by: Dr. Dimitri N. Mavris, Advisor Dr. Daniel Schrage School of Aerospace Engineering School of Aerospace Engineering Georgia Institute of Technology Georgia Institute of Technology Dr. Jung-Ho Lewe Mr. Kurt Neitzke School of Aerospace Engineering Langley Research Center Georgia Institute of Technology National Aeronautics and Space Ad- ministration (NASA) Dr. Hojong Baik Department of Civil, Architectural and Environmental Engineering Missouri University of Science and Technology Date Approved: August 22, 2008 To my family, for their love, patience, and unwavering support iii ACKNOWLEDGEMENTS I would like to extend thanks to my adviser, Dr. Dimitri Mavris, who has provided invaluable advice, encouragement, and support throughout the years. To Dr. Jung- Ho Lewe, for his guidance in the research work for this dissertation. To Mr. Kurt Neitzke, Dr. Hojong Baik, and Dr. Daniel Schrage, for sharing their wealth of knowledge. To Dr. Daniel DeLaurentis and Dr. Elena Garcia for their mentorship during my early years at Georgia Tech. I would like to also thank my friends, Eunsuk, Timothy, Xin Yuan, and Joseph, who have helped carry me along in this journey, shared with me their knowledge and most importantly their friendship. Most importantly, I owe what I have achieved today to the unwavering support from my parents, Victor and Anne, who have given me the inspiration and confidence from the very beginning and continued to support me till the end. To my siblings, Harry, Joyce, and Melody, who have paved the early paths for me to get here. Last but certainly not least, to my wife, Katherine, who has been there with me through the highs and the lows. Thank you all. iv TABLE OF CONTENTS DEDICATION ................................... iii ACKNOWLEDGEMENTS ............................ iv LIST OF TABLES . viii LIST OF FIGURES ................................ x LIST OF SYMBOLS OR ABBREVIATIONS . xiv SUMMARY . xviii I INTRODUCTION .............................. 1 1.1 The Evolving Commercial Air Transportation System . 1 1.2 Research Statement . 4 1.3 Thesis Organization . 7 II LITERATURE REVIEW .......................... 9 2.1 Air Transportation Demand-Side Components . 10 2.1.1 Aviation Demand Forecasting Methodology . 10 2.1.2 General Transportation Demand Theory . 13 2.2 Air Transportation Supply-Side Components . 23 2.2.1 The National Airspace System . 23 2.2.2 Air Service Providers . 24 2.3 Literature Review Summary . 34 2.4 Research Questions and Hypotheses . 39 III SOLUTION APPROACHES ........................ 43 3.1 Modeling Complex Systems . 44 v 3.1.1 Complex Adaptive Systems . 44 3.1.2 Sentience . 46 3.2 Modeling Transportation Environment . 47 3.2.1 Spatially-Explicit Environment . 48 3.2.2 Time-Variant Environment . 49 3.3 Modeling Demand-Supply Interactions . 52 3.3.1 Transportation Demand . 53 3.3.2 Transportation Supply . 53 3.3.3 Integrative Demand-Supply Model . 61 3.4 Model Architecture . 63 3.4.1 Model Verification and Validation . 63 3.4.2 Blueprint . 65 IV IMPLEMENTATION ............................ 67 4.1 Modeling & Simulation Framework . 68 4.1.1 Object-Oriented Modeling Approach . 68 4.1.2 Database-Enabled Modeling Environment . 69 4.1.3 Transient Analysis Framework . 72 4.2 Transportation Environment Model . 73 4.2.1 Spatially Explicit Representation of the CONUS . 74 4.2.2 The Airport Network Model . 81 4.2.3 Doorstep-to-Destination Transportation Model . 85 4.3 Integrative Demand-Supply Model . 89 4.3.1 Transportation Demand via Consumer Agents . 89 4.3.2 Transportation Supply via Service Provider Agents . 109 4.3.3 Transportation Activities Simulation . 144 V MODEL VERIFICATION & VALIDATION . 147 5.1 Overview . 147 vi 5.2 Base Model Calibration . 148 5.2.1 Demand Model . 149 5.2.2 Supply Model . 158 VI SIMULATION STUDY ........................... 169 6.1 Business As Usual Scenario . 169 6.2 Rising Fuel Price Scenario . 177 6.3 Simulation Summary . 184 VII CONCLUSIONS & RECOMMENDATIONS . 186 7.1 Revisiting Research Questions & Hypotheses . 186 7.2 Research Contributions . 192 7.3 Recommendations . 194 APPENDIX A AVIATION MODELS & DATABASES . 196 APPENDIX B AGENT-BASED MODELING & SIMULATION . 212 APPENDIX C NETWORK MODELING ................... 220 APPENDIX D REVENUE MANAGEMENT SYSTEM . 226 APPENDIX E REINFORCEMENT LEARNING TECHNIQUE . 233 APPENDIX F AUXILIARY DATA ...................... 238 REFERENCES ................................... 243 VITA ........................................ 253 vii LIST OF TABLES 1 U.S. Air Carriers Percentage O-D Passenger Share, 1990-2002 . 3 2 U.S. Air Carriers Revenue Passenger Enplanements, 2000-2005 . 6 3 Capabilities and Limitations of Demand-Centric Models . 23 4 Capabilities and Limitations of Supply-centric Models . 34 5 2002 FAA NPIAS Airport Types Composition . 50 6 Mapping of Solution Approaches to Hypotheses . 65 7 Object Definitions in TransNet . 69 8 Geographic & Demographic Data Used in TransNet, Base Year = 1990 (1of3)................................... 78 9 Geographic & Demographic Data Used in TransNet, Base Year = 1990 (2of3)................................... 79 10 Geographic & Demographic Data Used in TransNet, Base Year = 1990 (3of3)................................... 80 11 Baseline Service Providers and Segment Operations . 83 12 Batch Size Distribution for Enterprise Agents . 96 13 1995 Mean Earners per Household by Household Income . 98 14 U.S. Transportation Seasonality Factor . 99 15 Probability of Airport Perceived Wait Times . 100 16 Long Distance Trips Composition by Mode and Distance . 107 17 1995 Market Shares and Average Load Factors . 112 18 1995 Market Shares and Average Load Factors by Carrier Size . 113 19 Direct and Indirect Operating Cost Components . 115 20 Direct Operating Cost per Utilization Minute (in steps of 40 seats) . 115 viii 21 Direct Operating Cost per Utilization Minute (in steps of 100 seats) . 115 22 Carriers’ Clustering Coefficient and Network Density Analysis . 126 23 Hub Airports Identified through Cumulative Hubbing Ratio . 127 24 Hub Airports Identified for Low Cost Carriers . 127 25 Deliberative Agents’ Properties . 216 26 Decile Income Distribution for MSA Locales, Base Year = 1999 (1 of 3) 239 27 Decile Income Distribution for MSA Locales, Base Year = 1999 (2 of 3) 240 28 Decile Income Distribution for MSA Locales, Base Year = 1999 (3 of 3) 241 29 Decile Income Distribution for Non-MSA Locales, Base Year = 1999 . 242 ix LIST OF FIGURES 1 Demand-Supply Decomposition of the Aviation System-of-Systems . 6 2 Thesis Organizational Structure . 8 3 U.S. Domestic NAS Capacity and Demand . 11 4 Mobility Budget Space Concept . 20 5 Level of Granularity . 50 6 Solution Approach for Modeling Transportation Environment . 51 7 Advantages of Hub Operations . 57 8 Aviation Demand and Supply Within a Hub-and-Spokes System . 62 9 Solution Approach for Modeling Demand-Supply Interactions . 62 10 Model Architecture of Integrative Demand-Supply Framework . 66 11 Origin-Destination Categories of the 1995 ATS . 76 12 Non-MSA Consumer Agents Probabilistic Displacement Method . 77 13 Spatially Explicit Representation of CONUS . 81 14 Airport Distribution in the NAS Network Model . 82 15 Doorstep-to-Destination Intermodal Relationship . 86 16 Alternative Airport Route Selection Approach . 88 17 MSA Consumer Agents Probabilistic Displacement Method . 93 18 Household Income Polynomial Fitting Equation . 94 19 Poisson Distributions for Sampling Advanced Purchase Period . 100 20 Model Fit for Hypothetical Total Produced Trips . 105 21 Nested Multinomial Tournament Logit Model . 110 22 Direct Operating Cost for Different Aircraft Classes . 117 x 23 Baseline Network Model Flow Diagram . 122 24 Baseline Network Model: Legacy Carriers . 123 25 Baseline Network Model: Low Cost Carriers . 123 26 Configurations for Hub-to-Hub Topology, R1 .............. 131 27 Configurations for Hub-to-Spoke Topology, R2 ............. 132 28 Configurations for Spoke-to-Hub Topology, R3 ............. 133 29 Configurations for Spoke-to-Spoke Topology, R4 ............ 134 30 Total Operating Cost vs. Expected Load Factor . 140 31 Perceived Demand Function for Advance Purchase Dynamic Pricing . 141 32 Integrative Demand-Supply Modeling Flow Process . 145 33 Simple Modeling and Simulation Paradigm . 148 34 Demand Calibration Phase I: Mode Selection Calibration . 151 35 Demand Calibration Phase I: Business Trips Modal Split Ratio . 152 36 Demand Calibration Phase I: Personal Trips Modal Split Ratio . 152 37 Demand Calibration Phase I: All Trips Modal Split Ratio . 153 38 Demand Calibration Phase I: Business Trips Normalized Total Trip Counts................................... 154 39 Demand Calibration Phase I: Personal Trips Normalized Total Trip Counts................................... 154 40 Demand Calibration Phase I: All Trips Normalized Total Trip Counts 155 41 Demand Calibration Phase II: Cumulative Distribution Function for Total Trips . 156 42 Demand Calibration Phase II: Total Produced and Attracted Trips . 157 43 Demand Calibration Phase III: Cumulative Distribution Function for Total Passengers . 159 44 Demand Calibration Phase III: Total
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