Modelling and Managing Airport Performance

Konstantinos G. Zografos, Athens University of Economics and Business, Greece, Giovanni Andreatta, University of Padova, Italy, Amedeo Odoni, MIT (Massachusetts Institute of Technology), USA.

Konstantinos G. Zografos is Professor and Chairman, Department of Management Science and Technology and Director, Transportation Systems and Logistics Laboratory (TRANSLOG) at the Athens University of Economics and Business. His areas of teaching and research interest are supply chain management, project management, intermodal terminal operations and airport planning and operations. He consults with industry, has won many awards for his activities within operations research and is a member of the editoral board for several peer review journals.

Giovanni Andreatta is Professor of Operations Research in the Department of Pure and Applied Mathematics at the University of Padova. His teaching and research interests lie within operations research, mathematical planning and optimization.

Amedeo R. Odoni is Professor of Aeronautics and Astronautics and of Civil and Environmental Engineering.  He has also served as Co-Director of MIT’s Operations Research Center, as Co-Director of the FAA’s National Center of Excellence in Aviation Education, and as Editor of the scholarly journal Transportation Science.  He is the author, co-author or editor of 8 books and about 100 technical papers. Among other distinctions, he is the recipient of the FAA’s National Award for Excellence in Aviation Education, the INFORMS Robert F. Herman Award for Lifetime Contributions to Transportation Science and several awards for excellence in teaching. Professor Odoni’s recent textbook, Airport Systems: Planning, Design and Management is a standard reference on airport planning and operations.

Series Editor’s Preface xix

Acknowledgements xxi

List of Abbreviations xxiii

Introduction xxvii

1 Modeling Airport Landside Performance 1

Anderson Ribeiro Correia and S. C. Wirasinghe

1.1 Motivation for Level of Service Modeling 1

1.2 Relationship between Measures of Capacity

and Level of Service 2

1.3 Airport Landside Components 3

1.3.1 Emplaning Curbside 3

1.3.1.1 Level of Service Standards 3

1.3.1.2 General Recommendations 4

1.3.2 Check-in Counter 5

1.3.2.1 Level of Service Standards 5

1.3.2.2 General Recommendations 7

1.3.3 Security Screening 7

1.3.4 Departure Lounge 8

1.3.4.1 Level of Service Standards 8

1.3.4.2 General Recommendations 10

1.3.5 Baggage Claim 10

1.4 Methodology for Deriving Quantitative Standards for Individual Components 13

1.4.1 Introduction 13

1.4.2 The Method of Successive Categories 13

1.5 Degree of Importance of Landside Components and Attributes 21

1.5.1 Introduction 21

1.5.2 Selection of Components and Attributes 21

1.5.3 The AHP – Analytical Hierarchy Process 22

1.5.4 Descriptive Analysis of Passenger Responses 22

1.5.5 Degrees of Importance of Components and Their Attributes 23

1.6 Conclusions 25

References 25

2 Decision Support Systems for Integrated Airport Performance Assessment and Capacity Management 27

Konstantinos G. Zografos, Giovanni Andreatta, Michel J.A. van Eenige

and Michael A. Madas

2.1 Introduction and Objectives 27

2.2 SPADE DSS Description 29

2.2.1 Basic Modelling Concepts 29

2.2.2 High-Level Structure 30

2.2.3 Suite of Use Cases 33

2.2.3.1 UC1: Airport Capacity Management 34

2.2.3.2 UC2: Match Capacity and Demand 34

2.2.3.3 UC3: Airport Airside Analysis 35

2.2.3.4 UC4: Fleet Characteristics Impact on Airport Operations 35

2.2.3.5 UC5: Airport Capacity Utilization 35

2.2.3.6 UC6: Airport Capacity Determination 35

2.2.3.7 UC7: Airport Capacity versus Environmental Capacity 36

2.2.3.8 UC8: Taxiing Methodology 36

2.2.3.9 UC9: Impact of New Procedures and/or Equipment 36

2.3 SPADE DSS Applications 37

2.3.1 SPADE DSS Application for Strategic Decision Making 37

2.3.1.1 Description of Use Case 1 (Airport Capacity Management) 37

2.3.1.2 Scenario Description 40

2.3.1.3 Discussion of Results 41

2.3.1.4 Conclusions 49

2.3.2 SPADE DSS Application for Operational/Tactical Decision Making 50

2.3.2.1 Description of Use Case 7 (Airport Capacity versus Environmental Capacity) and Use Case 9 (Impact of New Procedures and/or Equipment) 51

2.3.2.2 Scenario Description 54

2.3.2.3 Discussion of Results 56

2.3.2.4 Conclusions 62

2.4 Conclusions 62

Acknowledgements 64

Notes 64

References 64

3 Measuring Air Traffic Management (ATM) Delays Related to Airports: A Comparison between the US and Europe 67

John Gulding, David A. Knorr, Marc Rose, Philippe Enaud and P. Holger Hegendoerfer

3.1 Introduction 67

3.2 Operations at the Main 34 US and European Airports 68

3.3 Value of Delay as a Performance Measure 70

3.3.1 On-Time/Punctuality Measures 72

3.3.2 Evolution of Scheduled Block Times 74

3.3.3 Delays by Phase of Flight 74

3.4 ATM-Related Operational Performance at US and European Airports 76

3.4.1 Managing En-Route and Arrival Constraints at the Departure Gate 80

3.4.2 Managing Arrival Constraints within the Last 100 NM 80

3.4.2.1 Case Study 1: Improving Arrival Management with Controlled Times for Arrivals (CTAs) 82

3.4.3 Managing Departure Runway Constraints – A Look at Taxi-Out Delay 85

3.4.3.1 Managing Departure Constraints on the Taxiways 85

3.4.3.2 Managing Departure Runway Constraints at the Gate 87

3.4.3.3 Case Study 2: Managing Taxi-Out Delay with Airport CDM 87

3.5 Summary and Conclusion 91

Notes 91

References 92

4 Forecasting Airport Delays 95

David K. Chin, Alius J. Meilus, Daniel Murphy, and Prabhakar Thyagarajan

4.1 Introduction 95

4.2 Historical Example – JFK Summer 2007 95

4.3 Delay Forecasting Methodology 97

4.3.1 Projected Demand 97

4.3.1.1 Airline Schedule Evolution 97

4.3.1.2 Unscheduled Traffic 99

4.3.2 Annual Service Volume Delay Model 99

4.3.3 NAS-Wide Delay Model 101

4.3.3.1 Flight Plan Data 101

4.3.3.2 Unscheduled Traffic 104

4.3.3.3 Model Description 104

4.3.4 Results 110

4.3.4.1 Validation 114

4.4 Conclusion 116

References 116

5 Airport Operational Performance and Its Impact on Airline Cost 119

Mark Hansen and Bo Zou

5.1 Introduction 119

5.2 Quantifying Operational Performance 121

5.2.1 Arrival Delay Against Schedule and Schedule Buffer 121

5.2.2 Alternative Metrics 122

5.3 Estimating the Cost Impact of Imperfect Operational Performance 123

5.3.1 Cost Factor Approach 123

5.3.1.1 Categorizing Delay 124

5.3.1.2 Determining Cost Factors 127

5.3.1.3 Shortcomings of the Cost Factor Approach 131

5.3.2 Aggregate Cost Approach 136

5.3.2.1 Total Time Approach 136

5.3.2.2 Econometric Approach 137

5.3.2.3 Summary 138

5.4 Further Issues 139

5.4.1 Cancellations 139

5.4.2 Optimal Level of Operational Performance and System Response 140

5.5 Conclusions 141

Notes 141

References 141

6 New Methodologies for Airport Environmental Impact Analysis 145

Mark Hansen, Megan S. Ryerson, and Richard F. Marchi

6.1 Introduction 145

6.2 Pollutant Overview 146

6.2.1 Noise 146

6.2.1.1 Pollutant Harm and Impact 147

6.2.1.2 Aircraft Noise Policy 148

6.2.1.3 Noise and Community Reaction 148

6.2.1.4 Models for Noise at Airports 149

6.2.2 Greenhouse Gas Emissions 150

6.2.2.1 Pollutant Characterization and Challenges 151

6.2.2.2 GHG Policies 151

6.2.2.3 Inventories and Models 152

6.2.3 Water Runoff 153

6.2.3.1 Pollutant Harm and Impact 154

6.2.3.2 Models for Water Runoff at Airports 155

6.2.4 Criteria Air Pollutants 155

6.2.4.1 Pollutant Harm and Impact 155

6.2.4.2 Policies 157

6.2.4.3 Models 159

6.3 The Future of Airport Environmental Impact Analysis 161

6.3.1 Environmental Impact Models 162

6.3.2 Environmental Impact Policy Models 164

6.4 Conclusion 166

Acknowledgements 167

References 167

7 Airport Safety Performance 171

Alfred Roelen and Henk A.P. Blom

7.1 Introduction 171

7.2 Accident Rates in Commercial Aviation 172

7.2.1 From Accident Statistics to Accident Rates 172

7.2.2 CICTT categories 175

7.2.3 Take-off, Landing and Ground Operation versus Other Categories 175

7.3 Analysis of Take-off, Landing and Ground Operation Accidents 177

7.3.1 Runway Excursions 177

7.3.2 Take-off and Landing Categories other than Runway Excursion 179

7.3.3 Ground Operation Categories 181

7.3.4 Summary of Take-off, Landing and Ground Operation Analysis 184

7.4 Analysis of Other CICTT Categories 186

7.4.1 Occurrence Rate per Category Grouping 186

7.4.2 Airborne Grouping Categories 188

7.4.3 Categories in the Weather Group 191

7.4.4 Categories in the Aircraft Group 191

7.4.5 Categories in the Miscellaneous Group 194

7.4.6 Categories in the Non-Aircraft Group 194

7.4.7 Summary of the Findings for the Other CICTT Categories 194

7.5 Safety Driving Mechanisms 197

7.5.1 Technological Developments 197

7.5.2 Regulation 199

7.5.3 Competition, Reputation and Balancing Objectives 200

7.5.4 Professionalism and Safety Culture 201

7.6 Safety Initiatives 202

7.6.1 Initiatives of the Flight Safety Foundation 202

7.6.1.1 CFIT Task Force 202

7.6.1.2 ALAR Task Force 202

7.6.1.3 FSF Runway Safety Initiative (RSI) 203

7.6.2 Commercial Aviation Safety Team (CAST) 203

7.6.3 European Action Plan for the Prevention of Runway Incursions 204

7.6.4 FAA/Eurocontrol Action Plan 15 on Safety Research and Development 204

7.6.5 Impact of Safety Initiatives on Safety Improvements 205

7.7 Conclusion 206

Acknowledgements 207

Notes 208

References 208

8 Scheduled Delay as an Indicator for Airport Scheduling Performance 211

Dennis Klingebiel, Daniel Kösters and Johannes Reichmuth

8.1 Introduction 211

8.2 Background 212

8.2.1 Airport Coordination 212

8.2.1.1 Coordination Parameters – Declared Capacity 213

8.2.1.2 Initial Slot Request, Coordination, and Slot Allocation 213

8.2.1.3 Post Initial Allocation Activities 214

8.2.2 Performance Indicator: Scheduled Delays 214

8.2.3 Slot Utilization and Scheduled Delays 215

8.3 Definition of a Model to Predict Scheduled Delays 219

8.4 Validation of the Model Approach 221

8.5 Application of the Model Approach 225

8.5.1 Analyzing the Impact of Different Demand Profiles on the Scheduling Performance 225

8.5.1.1 Typical Demand Profiles 226

8.5.1.2 Prediction of Scheduled Delays 227

8.5.2 Analyzing the Impact of Declared Capacity Values on the Scheduling Performance 228

8.6 Conclusion 231

References 231

9 Implementation of Airport Demand Management Strategies: A European Perspective 233

Michael A. Madas and Konstantinos G. Zografos

9.1 Introduction 233

9.2 Current Practice 235

9.3 Review of Existing Policy Proposals 237

9.4 Is a New Regime Really Necessary? 239

9.4.1 Mismatch but also Misuse 240

9.4.2 Poor Allocation Efficiency 240

9.4.3 Declared Capacity Considerations 241

9.4.4 Barriers to New Entrants 241

9.4.5 Potential Impacts 242

9.4.6 Pricing Effectiveness of Existing System 243

9.5 From Theory into Policy Practice 244

9.6 Improvement Complements to Existing Policy Practice: Directions for Future Research 252

9.7 Conclusions 255

Notes 256

References 256

10 Design and Justification for Market-Based Approaches to Airport Congestion Management: The US Experience 259

Michael O. Ball, Mark Hansen, Prem Swaroop and Bo Zou

10.1 Introduction 259

10.2 Background 260

10.2.1 Airport Operations and Slot Controls 260

10.2.2 Recent Public Policy Initiatives in the US 263

10.3 The Fundamental Question: Economic Justification for Slot Controls 264

10.4 Other Implications of Slot Controls 270

10.5 Design Issues for Slot Controls 273

10.5.1 Getting the Slot Level Right 273

10.5.2 Small Community Access 273

10.5.3 Where Does the Money Go? 274

10.5.4 Federal versus Local Control 274

10.5.5 Who Can Own Slots? 275

10.5.6 International Bilateral Agreements 275

10.5.7 Infrastructure Investment Incentives 275

10.6 Conclusions 275

References 276

Index

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