Modelling and Managing Airport Performance E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Aerospace Series (PEP)
• Sprache: Englisch

Seitenzahl: 569

Veröffentlichungsjahr: 2013

Beschreibung

Modelling and Managing Airport Performance provides an integrated view of state-of-the-art research on measuring and improving the performance of airport systems with consideration of both airside and landside operations. The considered facets of performance include capacity, delays, economic costs, noise, emissions and safety. Several of the contributions also examine policies for managing congestion and allocating sparse capacity, as well as for mitigating the externalities of noise, emissions, and safety/risk.

Key features:

• Provides a global perspective with contributing authors from Europe, North and South America with backgrounds in academia, research institutions, government, and industry
• Contributes to the definition, interpretation, and shared understanding of airport performance measures and related concepts
• Considers a broad range of measures that quantify operational and environmental performance, as well as safety and risk
• Discusses concepts and strategies for dealing with the management of airport performance
• Presents state-of-the-art modelling capabilities and identifies future modelling needs

Themed around 3 sections – Modelling Airport Performance, Assessing Airport Impacts, and Managing Airport Performance and Congestion Modelling and Managing Airport Performance is a valuable reference for researchers and practitioners in the global air transportation community.

Leseprobe

Contents

List of Contributors

Series Preface

Acknowledgements

List of Abbreviations

Introduction

1 Modeling Airport Landside Performance

1.1 Motivation for Level of Service Modeling

1.2 Relationship between Measures of Capacity and Level of Service

1.3 Airport Landside Components

1.4 Methodology for Deriving Quantitative Standards for Individual Components

1.5 Degree of Importance of Landside Components and Attributes

1.6 Conclusions

References

2 A Decision Support System for Integrated Airport Performance Assessment and Capacity Management

2.1 Introduction and Objectives

2.2 SPADE DSS Description

2.3 SPADE DSS Applications

2.4 Conclusions

Acknowledgements

Notes

References

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

3.1 Introduction

3.2 Operations at the Main 34 US and European Airports

3.3 Value of Delay as a Performance Measure

3.4 ATM-Related Operational Performance at US and EuropeanAirports

3.5 Summary and Conclusion

Notes

References

4 Forecasting Airport Delays

4.1 Introduction

4.2 Historical Example – JFK Summer 2007

4.3 Delay Forecasting Methodology

4.4 Conclusion

References

5 Airport Operational Performance and Its Impact on Airline Cost

5.1 Introduction

5.2 Quantifying Operational Performance

5.3 Estimating the Cost Impact of Imperfect Operational Performance

5.4 Further Issues

5.5 Conclusions

Notes

References

6 New Methodologies for Airport Environmental Impact Analysis

6.1 Introduction

6.2 Pollutant Overview

6.3 The Future of Airport Environmental Impact Analysis

6.4 Conclusion

Acknowledgements

References

7 Airport Safety Performance

7.1 Introduction

7.2 Accident Rates in Commercial Aviation

7.3 Analysis of Take-Off, Landing and Ground Operation Accidents

7.4 Analysis of Other CICTT Categories

7.5 Safety Driving Mechanisms

7.6 Safety Initiatives

7.7 Conclusion

Acknowledgements

Notes

References

8 Scheduled Delay as an Indicator for Airport Scheduling Performance

8.1 Introduction

8.2 Background

8.3 Definition of a Model to Predict Scheduled Delays

8.4 Validation of the Model Approach

8.5 Application of the Model Approach

8.6 Conclusion

References

9 Implementation of Airport Demand Management Strategies: A European Perspective

9.1 Introduction

9.2 Current Practice

9.3 Review of Existing Policy Proposals

9.4 Is a New Regime Really Necessary?

9.5 From Theory into Policy Practice

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

9.7 Conclusions

Acknowledgements

Notes

References

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

10.1 Introduction

10.2 Background

10.3 The Fundamental Question: Economic Justification for Slot Controls

10.4 Other Implications of Slot Controls

10.5 Design Issues for Slot Controls

10.6 Conclusions

References

Index

Aerospace Series List

Modelling and Managing Airport Performance

Zografos

July 2013

Advanced Aircraft Design: Conceptual Design, Analysis and Optimization of Subsonic Civil Airplanes

Torenbeek

June 2013

Design and Analysis of Composite Structures: With applications to aerospace Structures,Second Edition

Kassapoglou

April 2013

Aircraft Systems Integration of Air-Launched Weapons

Rigby

April 2013

Design and Development of Aircraft Systems, 2nd Edition

Moir and Seabridge

November 2012

Understanding Aerodynamics: Arguing from the Real Physics

McLean

November 2012

Aircraft Design: A Systems Engineering Approach

Sadraey

October 2012

Introduction to UAV Systems 4e

Fahlstrom and Gleason

August 2012

Theory of Lift: Introductory Computational Aerodynamics with MATLAB and Octave

McBain

August 2012

Sense and Avoid in UAS: Research and Applications

Angelov

April 2012

Morphing Aerospace Vehicles and Structures

Valasek

April 2012

Gas Turbine Propulsion Systems

MacIsaac and Langton

July 2011

Basic Helicopter Aerodynamics, 3rd Edition

Seddon and Newman

July 2011

Advanced Control of Aircraft, Spacecraft and RocketsCooperative Path Planning of Unmanned

Tewari

July 2011

Aerial Vehicles

Tsourdos et al.

November 2010

Principles of Flight for Pilots

Swatton

October 2010

Air Travel and Health: A Systems Perspective Unmanned Aircraft Systems: UAVS

Seabridge et al.

September 2010

Design, Development and Deployment

Austin

April 2010

Introduction to Antenna Placement & Installations

Macnamara

April 2010

Principles of Flight Simulation

Allerton

October 2009

Aircraft Fuel Systems

Langton et al.

May 2009

The Global Airline Industry

Belobaba

April 2009

Computational Modelling and Simulation of Aircraft and the Environment: Volume 1 – Platform Kinematics and Synthetic Environment

Diston

April 2009

Handbook of Space Technology

Ley, Wittmann Hallmann

April 2009

Aircraft Performance Theory and Practice for Pilots

Swatton

August 2008

Aircraft Systems, 3rd Edition

Moir & Seabridge

March 2008

Introduction to Aircraft Aeroelasticity And Loads

Wright & Cooper

December 2007

Stability and Control of Aircraft Systems

Langton

September 2006

Military Avionics Systems

Moir & Seabridge

February 2006

Design and Development of Aircraft Systems

Moir & Seabridge

June 2004

Aircraft Loading and Structural Layout

Howe

May 2004

Aircraft Display Systems

Jukes

December 2003

Civil Avionics Systems

Moir & Seabridge

December 2002

This edition first published in 2013© 2013 by John Wiley & Sons, Ltd

Registered OfficeJohn Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom

For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com.

The right of the author to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright, Designs and Patents Act 1988, without the prior permission of the publisher.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.

Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book.

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. It is sold on the understanding that the publisher is not engaged in rendering professional services and neither the publisher nor the author shall be liable for damages arising herefrom. If professional advice or other expert assistance is required, the services of a competent professional should be sought.

MATLAB® is a trademark of The MathWorks, Inc. and is used with permission. The MathWorks does not warrant the accuracy of the text or exercises in this book. This book’s use or discussion of MATLAB® software or related products does not constitute endorsement or sponsorship by The MathWorks of a particular pedagogical approach or particular use of the MATLAB® software.

Library of Congress Cataloguing-in-Publication Data

Modelling and managing airport performance / [edited by] Konstantinos G. Zografos, Giovanni Andreatta, Amedeo R. Odoni. 1 online resource. Includes bibliographical references and index.Description based on print version record and CIP data provided by publisher; resource not viewed.

ISBN 978-1-118-53547-9 (ePub) – ISBN 978-1-118-53585-1 (ePDF) – ISBN 978-1-118-53586-8 (MobiPocket) – ISBN 978-0-470-97418-6 (cloth) 1. Airports–Management. 2. Airports–Management–Evaluation. 3. Airports–Management–Simulation methods. I. Zografos, Kostas G. II. Andreatta, G. (Giovanni) III. Odoni, Amedeo R. TL725.3.M2 387.7′360684–dc23

2013015971

A catalogue record for this book is available from the British Library.

ISBN: 978-0-470-97418-6

About the Editors

Konstantinos G. Zografos is Chair Professor at the Department of Management Science of Lancaster University Management School (LUMS). He served as Professor and for four years as Chairman at the Department of Management Science and Technology of the Athens University of Economics and Business (AUEB), where he founded and directed the Transportation Systems and Logistics (TRANSLOG) Laboratory. His professional expertise, research and teaching interests include applications of Operations Research and Information Systems in Transportation and Logistics with particular emphasis on: the optimization of transportation and logistical decisions, supply chain performance assessment, airport planning and operations, and project management. He has published more than 60 papers in refereed academic journals and edited volumes. He has served as a member of the editorial board of 5 academic journals and has acted as a reviewer for numerous academic journals, including major journals in the fields of transportation, logistics and management science. He has served as member of several Transportation Research Board (TRB) committees in the areas of airfield and airspace capacity and delay, airport terminals and ground access, freight transportation planning and logistics, hazardous materials transportation, and transportation network modeling. In addition, he has been a member of European Commission Committees for the development and management of European R&D Framework Programmes in the area of Transport. Currently, he is a member of the Scientific Committee of the Single European Sky ATM Research (SESAR) Joint Undertaking. He has received teaching and research awards including the Edelman Laureate Honorary Medal in 2008 for Achievement in Operations Research and the Management Sciences, awarded by the Institute of Operations Research and the Management Sciences (INFORMS), and the 2005 President’s Medal Award by the British Operational Research Society. Professor Zografos has been involved as a principal investigator in more than 60 R&D projects funded by national and international organizations and companies in USA, Europe and Greece and he has acted as consultant to projects funded by governmental agencies, companies and international organizations including the European Commission, United Nations Economic Commission for Europe (UNECE) and EUROCONTROL.

Giovanni Andreatta is Full Professor of Operations Research at the School of Sciences of the University of Padova (Italy). He received a Laurea degree in mathematics from the same ­university and a Masters in Computer Science from the University of Bologna (Italy). He completed his academic formation at MIT (Cambridge, MA, USA) as Visiting Scholar for a couple of years (August 1979–July 1981). He has been teaching several courses, mostly within the domain of Operations Research, in Italy: University of Padova (School of Sciences, of Engineering, of Economy), University of Venice and Bicocca University in Milan. He has been teaching for a short period at MIT (Cambridge, USA) and in other foreign universities: University of Luanda (Angola), University of Mogadishu (Somaly), HIBA in Damascus (Syria). He has been actively engaged in research, both in Italy and abroad, in the field of ­operations research, with particular interest in the applications to air transportation problems and has been the Scientific Leader of the Padova team for several national and European research programs (TAPE, OPAL, THENA, SPADE, SPADE-2, AAS). He is an Associate Editor of the Journal of Aerospace Operations and a member of national (AIRO, UMI, etc.) and international scientific associations (ATCA, INFORMS, etc.). He has served as a member of the Scientific Program Committee of national (such as AIRO) and international conferences (e.g. Eurocontrol-FAA ATM Seminar, ICRAT and RIVF).

Amedeo R. Odoni is Professor of Aeronautics and Astronautics and Professor of Civil and Environmental Engineering at MIT. He specializes in the application of operations research methodologies to airport planning and operations, as well as to air traffic management. Among other positions, he has served as Co-Director of MIT’s Operations Research Center (1985–1991), of the FAA’s National Center of Excellence in Aviation Operations Research – NEXTOR (1996–2002), of the Global Airline Industry Center at MIT (1999–2009), and of the Future Urban Mobility research project of SMART, the Singapore-MIT Alliance for Research and Technology (2009–present). Dr Odoni is the author, co-author, or co-editor of nine books and more than 100 professional publications. He served as editor-in-chief of Transportation Science from 1985–1991, and is a current or past member of the editorial boards of many professional journals. He is an elected member of the US National Academy of Engineering, a Fellow of the Institute for Operations Research and Management Science (INFORMS) and the recipient of many awards for his teaching and research. He has supervised more than 50 PhD students, several of whom have won major prizes for their research and dissertations, and has been a member of the PhD thesis committees of more than 100 other students. He has served as consultant to national and international organizations, and to many of the busiest airports in the world on projects related to practically every aspect of airport planning, design and operations, as well as to air traffic management in terminal airspace.

List of Contributors

Giovanni AndreattaDepartment of Mathematics, University of Padova, ItalyMichael O. BallRobert H. Smith School of Business and Institute for Systems Research, University of Maryland, USAHenk A.P. BlomAerospace Engineering Department, Delft University of Technology & Air Transport Safety Institute, National Aerospace Laboratory NLR, The NetherlandsDavid K. ChinFederal Aviation Administration, Office of Performance Analysis, USAAnderson Ribeiro CorreiaDepartment of Air Transportation, Aeronautics Institute of Technology, BrazilMichel J.A. van EenigeEnvironment and Policy Support Department, National Aerospace Laboratory (NLR), The NetherlandsPhilippe EnaudPerformance Review Unit, EUROCONTROL, BelgiumJohn GuldingFederal Aviation Administration, Office of Performance Analysis, USAMark HansenNational Center of Excellence for Aviation Operations Research, Department of Civil and Environmental Engineering, University of California, Berkeley, USAHolger P. HegendoerferPerformance Review Unit, EUROCONTROL, BelgiumDennis KlingebielPhysics Institute IIIA, RWTH Aachen University, GermanyDavid A. KnorrOffice of International Affairs, Federal Aviation Administration, USADaniel KöstersFrankfurt Airport, FRA Vorfeldkontrolle GmbH, Fraport AG, GermanyMichael A. MadasTransportation Systems and Logistics Laboratory (TRANSLOG), Department of Management Science and Technology, Athens University of Economics and Business, GreeceRichard F. MarchiSenior Advisor, Policy and Regulatory Affairs, Airports Council International, North America, USAAlius J. MeilusFederal Aviation Administration, Office of Performance Analysis, USADaniel MurphyFederal Aviation Administration, Office of Performance Analysis, USAJohannes ReichmuthRWTH Aachen Institute of Transport Science VIA, and DLR Institute of Air Transport and Airport Research, German Aerospace Center (DLR), RWTH Aachen University, GermanyAlfred RoelenAir Transport Safety Institute, National Aerospace Laboratory (NLR), The NetherlandsMarc RoseMCR LLC, USAMegan S. RyersonDepartment of Civil and Environmental Engineering, University of Tennessee, USAPrem SwaroopRobert H. Smith School of Business and Institute for Systems Research, University of Maryland, USAPrabhakar ThyagarajanFederal Aviation Administration, Office of Performance Analysis, USAS.C. WirasingheDepartment of Civil Engineering, Schulich School of Engineering, University of Calgary, CanadaKonstantinos G. ZografosDepartment of Management Science, Lancaster University Management School, Lancaster University, UKBo ZouCivil and Materials Engineering, University of Illinois at Chicago, USA

Series Preface

The Wiley Aerospace Series recognizes that the aerospace industry is multi-faceted and multi-disciplinary, involving a wide range of professionals and stakeholders that include not only aeronautical engineers but manufacturers, operators, and policy-makers, in addition to academics and students. The goal of this series is to provide practical and topical information to the diverse set of people in this innovative and dynamic industry.

A systems approach to aerospace engineering is essential to a full understanding of the industry, from the conception, design, testing, and production through to the operation of aerospace vehicles. In this systems perspective, relevant topics include air transportation, airline industry performance and infrastructure operations.

In Modelling and Managing Airport Performance, the editors have compiled an impressive set of articles devoted to an important part of the aviation system – air transportation infrastructure. Specifically, this book provides a comprehensive treatment of methodologies for analyzing, forecasting and improving the performance of airports and air traffic flows. Given the limited capability to expand existing airport infrastructure in most countries, the use of advanced airport performance modelling is critical to understanding and ameliorating the impacts of the growing demand for air travel on airport congestion and delays.

The contributors to this book are global experts on air traffic and airport management, from well-known academics to internationally recognized professionals in consultancy, government agencies and airport authorities. Models for analyzing airport capacities, measuring and forecasting air traffic delays are described, and the impacts of airport operations on airline costs and environmental impacts are explored. The implications for improving airport safety and a discussion of air traffic demand management strategies and their implementation round out this collection of articles, which is a welcome addition to the Aerospace Series.

Peter Belobaba, Jonathan Cooper and Allan Seabridge

Acknowledgements

We wish to acknowledge Mr Tom Carter, Project Editor at John Wiley & Sons, Ltd, who provided critical assistance in managing the complex process of coordinating and stream­lining the contributions of a diverse set of authors. The preparation of this book has been ­supported by the SPADE-2 Integrated R&D Project (Supporting Platform for Airport Decision-making and Efficiency analysis: Phase 2, 2006–2009) partly financed by the European Commission: Directorate General for Energy and Transport (DG TREN) within the Sixth Framework Programme. We would like to thank the SPADE-2 Project Officers, Mr Cesare Bernabei, Mrs Elizabeth Martin and Mr Hoang Vu Duc, for providing useful feedback throughout the project’s duration. The preparation of the book has also been supported by the General Secretariat of Research and Technology of Greece under contract NC-1375-01 and by the Research Center of the Athens University of Economics and Business (AUEB-RC) through project EP-1809-01.

List of Abbreviations

AAR

Airport Acceptance Rate

AAS

Amsterdam Airport Schiphol

A-CDM

Airport Collaborative Decision-Making

ACI

Airports Council International

ACI Europe

Airport Council International Europe

ACM

Airport Capacity Management

AEDT

Aviation Environmental Design Tool

AFP

Airspace Flow Program

AHP

Analytical Hierarchy Process

AIA

Athens International Airport

AIR-21

Wendall H. Ford Aviation Investment and Reform Act

AIXM

Aeronautical Information Exchange Model

AMAN

Arrival Manager

AMS

Amsterdam-Schiphol Airport

ANS

Air Navigation Service

ANSP

Air Navigation Service Providers

APT

Airport Passenger Terminal

ARC

Airport Research Center

ARMT

Aviation Environmental Portfolio Management

ASA

Atlantic Southeast Airways

ASDE

Airport Surface Detection Equipment

ASDE-X

Airport Surface Detection Equipment, Model X

ASMA

Arrival Sequencing and Metering Area

A-SMGCS

Advanced Surface Movement Guidance and Control System

ASPM

Aviation System Performance Metrics (published by FAA)

ATA

Air Transport Assocation

ATC

Air Traffic Control

ATCSCC

Air Traffic Control System Command Centre

ATFM

Air Traffic Flow Management

ATH

Athens Airport

ATM

Air Traffic Management

ATO

Air Traffic Organization

BAA

British Airport Authority

BRU

Brussels Airport

CAA

Civil Aviation Authority

CAEP

Committee on Aviation Evironmental Protection

CANSO

Civil Air Navigation Service Organization

CDA

Continuous Descent Arrivals

CDG

Charles DeGaulle Airport (Paris)

CDM

Collaborative Decision Making

CENEL

California’s Day-Night Sound Level measurement

CFMU

Central Flow Management Unit

CH4

Methane

CO

Carbon Monoxide

CO2

Carbon Dioxide

CO2e

Carbon Dioxide Equivalents

CODA

Central Office for Delay Analysis

CPH

Copenhagen Airport

CTA

Controlled Time of Arrival

DbA

Decibal, A-weighted

DC

District of Columbia

DFS

Deutsche Flugsicherung GmbH (German ANSP)

DLTA

Difference from Long-Term Average

DNL

Day-Night Sound Level

DSS

Decision Support System

DUS

Düsseldorf Airport

ECU

Effective Curb Utilization

EDCT

Estimated Departure Clearance Times

EDMS

Emissions and Dispersion Modeling System

ERA

Environmental Protection Agency

ESRA

Eurocontrol Statistical Reference Area

EU

European Union

EU-27

27 member European Union

EU-ETS

European Union Emissions Trading Scheme

EUR

Europe

EUROCONTROL 

European Organisation for the Safety of Air Navigation

EWR

Newark Airport (New York)

FAA

(U.S.) Federal Aviation Administration

FAA AEE

Federal Aviation Administration Office of Environment and Energy

FAQ

Frequently Asked Question

FMS

Flight Management Systems

FRA

Frankfurt Airport

GAO

Government Accountability Office

GDP

Ground Delay Program

GHG

Greenhouse Gas

GS

Ground Stop

GSE

Ground Service Equipment

GSRT

Hellenic General Secretariat of Research and Technology

GUI

Graphical User Interface

HAP

Hazardous Air Pollutants

HC

Hydrocarbons

HCAA

Hellenic Civil Aviation Authority

HDR

High Density Rule

IATA

International Air Transport Association

ICAO

International Civil Aviation Organization

IFR

Instrument Flight Rules

IMC

Instrument Meteorological Conditions (poor weather)

ISA

Innovation for Sustainable Aviation

JFK

John F. Kennedy Airport (New York)

KPA

Key Performance Area

LAeq

United Kingdom’s Day-Night Sound Level measurement

Lday

Level of sound integrated over a day

Lden

European Union’s Day-Night Sound Level measurement

Leq

Level of sound integrated over an hour

LGA

La Guardia Airport (New York)

LHR

London Heathrow Airport

Lmax

Peak Sound Level

LMI

Logistics Management Institute

LOS

Level of Service

LTO

Landing-takeoff

MDI

Minimum Departure Interval

MIT

Miles in Trail

MOVES

Motor Vehicle Emission Simulator

MTOW

Maximum Take-Off Weight

MUC

Munich Airport

MVC

Model-View-Controller

N20

Nitrous Oxide

NAAQS

National Air Quality Standards

NAS

(U.S.) National Airspace System

NEXTGEN

Next Generation Air Traffic Control System (FAA)

NEXTOR

Center for Excellence in Operations Research

NLA

New Large Aircraft

NLR

National Aerospace Laboratory

NM

Nautical mile (1.852 km)

NOX

Nitrogen Oxides

OAG

Official Airline Guide

OEP35

35 U.S. airports forming the “Operational Evolution Partnership”

OPAL

Optimisation Platform for Airports including Landside

PANYNJ

The Port Authority of New York and New Jersey

PAS

Proportionate Allocation Scheme

PASSUR

Passive Surviellance system

PM

Particular Matter

PRC

EUROCONTROL Performance Review Commission

PRU

EUROCONTROL Performance Review Unit

R&D

Research and Development

RAS

Reward-based Allocation Scheme

RMS

Root Mean Square

RNAV

Area Navigation capabilities

SAGE

System for assessing Aviations Global Emissions

SEL

Sound level of an event integrated over its duration

SES

Single European Sky (EU)

SESAR

Single European Sky ATM Research (Eurocontrol)

SID

Standard Instrument Departure

SIPs

State Implementation Plans

SOX

Sulfur Oxides

SPADE

Supporting Platform for Airport Decision-making and Efficiency Analysis

STAR

Standard Terminal Arrival Route

SWMM

Storm Water Management Model

TAPE

Total Airport Performance and Evaluation

TBM

Time Based Metering

TM

TradeMark

TMA

Terminal manoeuvring area

TRB

Transportation Research Board

UC

Use Case

US

United States of America

VCE

Venice Airport

VMC

Visual Meteorological Conditions (good weather)

VOC

Volatile Organize Gasses

ZRH

Zurich Airport

Introduction

The increasing demand for air transport in conjunction with technical, physical and political constraints on providing capacity has resulted in a serious mismatch between demand and capacity. According to Eurocontrol, the planned capacity at the 138 Eurocontrol Statistical Reference Area (ESRA) airports is expected to increase by 41% in total by 2030, while the corresponding demand is foreseen to exceed airport capacity by as many as 2.3 million flights (or 11% of demand) in the most-likely growth forecast scenario for 2030 (Eurocontrol, 2008). Similarly, the FAA expects a quick resumption of US traffic growth, with traffic reaching 2007 levels by 2013, and growing by an additional 32% by 2025 (FAA, 2011).

The anticipated traffic volumes have to be accommodated by a system of airports with limited capacity, which in many cases has already been exceeded. Airports, as the terminal nodes of the air transport network, are the locations where delays generated and propagated throughout the network become most evident. At the same time, airports are also the most important ‘triggers’ of delay events, as a result of their often-reduced capacity due to poor weather or other problems. Direct consequences of airport congestion and delays include large external costs, poor level of service to the travelling public, inefficiency in airport operations, and negative impacts on the quality of the surrounding environment and the safety of the entire air transport system. Even during the current economic crisis, unconstrained demand (i.e. demand in the absence of slot controls) at several of the busiest European airports would have exceeded capacity for most of the day or, in a few cases, throughout the day. The percentage of departures delayed reached 37% (36% for arrivals), with an average delay per delayed flight for departures reaching 28 min (29 min for arrivals) in 2011 (Eurocontrol, 2012). The economic costs of these delays, operational inefficiencies and bottlenecks have been ­staggering. Ball et al. (2010) have estimated that the total economic impact of air ­transportation delays on the US economy amounted to $28.9 billion in 2007. Unavoidably, there has been increasing political pressure for improvements in airport performance through better and ­sustainable management of existing airport resources. But in order to improve performance, one should first be able to assess it. This has stimulated vigorous research efforts aimed at modelling all aspects of airport operations and evaluating quantitatively their impacts on delays and congestion, safety, the environment and the economy at large.

The assessment of airport performance is a complex task that requires a thorough ­understanding of the numerous aspects of airport operations and processes. By definition, a large variety of performance measures (e.g. capacity, delays, level of service, safety, security, emissions, noise, economic costs and benefits) should be considered along with their ­interdependencies and trade-offs. The airport decision making process is further complicated by the diversity of entities processed (passengers, baggage, cargo and aircraft) and the range of strategic, tactical, and operational considerations that need to be addressed throughout the airport, from ground access to the terminal airspace. Most importantly, these decisions should account for the often-conflicting needs and interests of the multiple stakeholders involved (civil aviation authorities, airlines, airport operators, passengers and shippers, airport ­neighbours, other government agencies). In such a multifaceted and complex environment, airport decision makers and planners must be supported by advanced airport modelling ­capabilities complemented by policies and strategies aimed at minimizing congestion and the externalities of airport operations.

The objective of this book is to provide an integrated view of state-of-the-art research on the performance of airport systems. Multiple facets of performance, such as capacity, delays, noise, emissions and safety, are considered. Furthermore, some of the chapters aim to go beyond modelling of operations, by shedding light on ways in which airport performance can be improved through policies for managing capacity allocation and congestion, as well as ­mitigating the externalities of noise, emissions, and safety/risks. Taken together, the chapters that are included herein have been selected with a view to (1) covering both landside and ­airside elements of the airport, (2) considering a broad spectrum of airport performance ­measures and (3) coupling reviews of modelling capabilities with the development of concepts and strategies for managing and improving airport performance.

The book consists of 10 chapters that are conceptually organized into three thematic ­sections. Section I (Chapters 1 and 2) focuses on the modelling and assessment of airport performance both on landside and airside. Section II (Chapters 3–7) deals with the ­quantification, measurement and forecast of the costs of airport delays, while further elaborating on the assessment of additional impacts (externalities) of airport operations. Finally, Section III (Chapters 8–10) covers topics related to the management of airport congestion and the efficiency of the scheduling and capacity allocation process on both sides of the North Atlantic.

In the first chapter of the book, Correia and Wirasinghe develop a methodology for ­evaluating the operational performance and quality of service offered by airport passenger terminals. They provide an overview of existing level of service (LOS) standards for airport passenger terminals along with their use for planning and operational management purposes. Furthermore, they recognize that LOS standards vary substantially with local passenger ­characteristics, and therefore employ a methodology for deriving quantitative standards by use of passenger surveys and observations. They initially use the psychometric scaling ­technique in order to develop quantitative LOS standards for individual components of the terminal. Then, they use the Analytical Hierarchy Process (AHP) in order to derive the importance weights that passengers assign to individual components and attributes of an ­airport passenger terminal. The application of the proposed methodology is demonstrated for São Paulo/Guarulhos International Airport, the busiest airport in Latin America. It is ­concluded that the proposed AHP methodology is appropriate for LOS modelling and can be further used to obtain a global LOS measure of an airport passenger terminal as a function of the LOS of its constituent components.

Chapter 2 by Zografos, Andreatta, van Eenige and Madas presents the development of an integrated Decision Support System (DSS) for total airport performance assessment. The presented DSS seamlessly integrates a variety of analytical models (e.g. MACAD, SLAM, INM, TRIPAC) and simulation tools (e.g. TAAM, RAMS Plus, SIMMOD, CAST) to capture the ­interdependencies among various performance measures (e.g. capacity, delay, noise, safety) and enable trade-off analyses at various levels of detail (e.g. strategic, tactical/operational) for the entire airport complex (both airside and landside) simultaneously. The chapter presents the architecture and operational concept of the DSS and demonstrates its capabilities through two pilot studies at Athens International Airport and Amsterdam Airport Schiphol. Based on the system’s ­demonstration and validation process, the authors conclude that it fulfils the requirements of potential end users and produces useful results for airport decision making with an adequate approximation of reality. The proposed DSS offers some important benefits to the user/airport decision maker since it adopts a problem-oriented rather than tool-driven approach which shields the user from the technical complexity of the tools, thus enabling him/her to focus on the real decision making issues to be addressed.

In Chapter 3 (Section II), a joint FAA/Eurocontrol team of researchers (Gulding, Knorr, Rose, Enaud and Hegendoerfer) use an analysis of extensive data to compare and discuss airport-related flight delays and other measures of operational efficiency at the 34 busiest ­airports of the Unites States and of Europe. These airports handle more than two thirds of all passengers in each region every year. The authors initially define several different metrics and then use them to draw comparisons between US and European airports, placing their emphasis on air traffic delays that can be influenced by Air Traffic Management (ATM) actions. The chapter adopts two alternative reference points when it comes to measuring delays. One ­reference is the airline schedules: delays are measured relative to scheduled times, that is, they provide estimates of punctuality. This type of delay is of special interest to air travellers, but may not capture the full extent of delays because airlines tend to ‘pad’ their schedules in order to improve their on-time performance. For this reason, the second reference is the unimpeded travel times between each origin-destination pair: delays relative to unimpeded travel times provide a more complete picture of performance and are particularly useful in identifying operational bottlenecks and inefficiencies in the ATM system that may be hidden by the schedule padding practices of the airlines. For this second type of analysis, delays are ­attributed to specific flight segments (pre-take-off, airborne, post-landing) and compared with ­unimpeded times for each segment. The results may be very informative and valuable to Air Navigation Service Providers (ANSP), the operators of ATM systems. Furthermore, delay comparisons between US and European airports can be the basis for the identification of best practices and opportunities for focused improvements. As an example of the insights provided, the chapter concludes that reductions in taxiway delays in the US may be achievable through the use of European queue management practices, while Europe might benefit from US best practices for absorbing arrival delays through collaboration with the airlines in implementing air traffic flow management interventions.

Delays are also the main subject of Chapter 4 by Chin, Meilus, Murphy and Thyagarajan. This chapter presents a new initiative/programme led by the FAA’s Air Traffic Organization (ATO) that forecasts delays at major (Core 30) US airports 6–12 months in advance. The starting points for these forecasts are the airlines’ published schedules, as well as historical operational data. To increase the reliability of the exercise, airline schedules are supplemented by a short-term, economics-based forecast of demand for each one of the thirty airports, based on the FAA’s Terminal Area Forecast (TAF) methodology. Demand forecasts, in the form of planned daily schedules of flights, are then combined with estimates of airport capacities to project delays six months into the future. Two alternative approaches are used for this purpose. The first is highly ‘macroscopic’ and based on a simple model of airport capacity (Annual Service Volume) along with parameterized relationships between annual operations and average delays for individual airports. The second approach uses a far more detailed network model to compute system-wide delays for each day of operations. The authors describe in detail both approaches as well as the extensive work that has been done in order to validate each by using historical data. At this point, the FAA is in a position to predict with a high level of confidence airport-specific and nationwide delays in the near future. In turn, the accurate projection of delays sufficiently far in advance enables the FAA not only to implement short-term mitigation measures, but also to provide early signals to policy makers regarding expected airport congestion. Affected groups (e.g. passengers) may also use this information to adjust their travel plans accordingly.

A comprehensive assessment of airport operational performance necessitates the ­quantification of the cost of delays. This topic is discussed in detail in Chapter 5 by Hansen and Zou. The chapter attempts to estimate the cost of air traffic delays to airlines in the United States. The authors take into account both the cost of delays relative to schedule and the cost of the additional time that airlines build into their schedules in anticipation of delay (schedule padding). They review critically and compare two fundamentally different approaches for estimating the impact of imperfect operational performance on airline costs. The first – the ‘cost factor’ method – is a ‘bottom-up’ approach that applies unit costs to different categories of delay (e.g. according to flight phase, aircraft type, delay duration, primary vs reactionary delay, etc.). The second – the ‘total cost’ method – is a ‘top-down’ approach based on aggregate costs. It posits the existence of a relationship between the total costs of an airline and the amount of delay (relative to schedule, as well as due to schedule padding) incurred by the flights of the airline. To derive this latter relationship, the authors develop an econometric model that investigates the statistical relationship between the various aspects of the operational performance of an airline and its costs. This econometric approach avoids some of the oversimplified assumptions and shortcomings of competing approaches. It is also rigorous, methodologically sophisticated, and probably more accurate. The econometric model is not, however, free of limitations with the major one being its intensive data requirements and its applicability at only a relatively aggregate level. The selection of the appropriate delay cost estimation approach should consider explicitly the scope/context of analysis and required level of detail. The authors argue that the existing estimates of the cost of air traffic delays in the US are somewhat re-assuring in that they are of roughly similar magnitude, despite the fundamental methodological differences between the various approaches utilized.

The next chapter, written by Hansen, Ryerson and Marchi, shifts the focus to externalities of airport operations other than delay-related measures. Chapter 6 discusses four key ­undesirable byproducts of airport and aviation operations: noise, water run-off, air pollutants, and Greenhouse Gas (GHG) emissions. It reviews these pollutants and their impact on airports and the surrounding environment. Furthermore, it discusses relevant mitigation policies and presents current methods/models for analysing and mitigating the GHG and noise impacts of airports, as well as the policy challenges faced in controlling these impacts. The chapter ­concludes with the development of an integrated modelling framework which combines ­environmental impact models with environmental policy impact models. Environmental impact models assess the level of emissions and resulting ecological and welfare impact from a given aviation system, while environmental policy impact models estimate how the system will evolve in response to a given environmental policy.

The analysis of the impacts of airport operations (Section II) concludes with Chapter 7 by Roelen and Blom dealing with aspects of safety performance. The chapter makes use of ­historical data of worldwide accidents of scheduled commercial flights by fixed wing aircraft with a maximum take-off weight of more than 5700 kg over the period 1990–2008 in order to analyse how safety performance has evolved for the ground segment of a flight relative to the airborne segment. It provides a systematic comparison of the evolution of accident rates over this period for Take-off, Landing and Ground Operations versus other accident categories such as Airborne and Weather. The comparative analysis reveals that the accident rate for Take-off, Landing and Ground Operations is not really improving, a fact that is in contrast with the overall improvements in the safety statistics of commercial aviation (decrease of safety risk per flight) during the period. A more detailed analysis of the accidents related to the ground segment of a flight at the level of the main accident categories (e.g. runway excursion/­incursion, abnormal runway contact, ground collision) shows that the non-decreasing accident rate applies to each of these main accident categories. Overall, the authors claim that the decrease of safety risk per flight during the last two decades has been caused predominantly from a reduction in airborne and aircraft related accidents rather than a reduction in accidents during take-off, landing and ground operations. The chapter concludes with a discussion of current as well as recommended safety initiatives (e.g. Flight Safety Foundation, Commercial Aviation Safety Team, FAA/Eurocontrol Action Plan 15) and driving mechanisms (e.g. ­technological developments, regulation, safety culture) addressing both the airborne and ground segments of a flight.

Section III starts with Chapter 8 by Klingebiel, Kösters and Reichmuth that deals with the efficiency of the slot scheduling and coordination process. The chapter analyses the airport’s scheduling performance based on the ‘scheduled delays’ criterion expressing the difference between requested and allocated slot times during initial slot coordination. The authors ­introduce a deterministic modelling approach aiming to calculate scheduled delays depending on the level of slot utilization. The model uses declared capacity restrictions and initial slot requests as input parameters to provide a first estimate of the scheduled delays as a result of conflict resolution within the initial slot coordination. The impact on airport scheduling performance of both varying declared capacity restrictions and different slot demand and ­utilization patterns are demonstrated and further analysed with the use of the model. The ­validation of the model at five German coordinated airports produced results of sufficient accuracy for certain levels of slot utilization and led to recommendations for further research and calibration efforts towards incorporating crucial coordination parameters (e.g. priority classes per slot request, grandfather rights). The authors suggest that future research be focused on the estimation of minimum declared capacity values being capable of complying with desired scheduling performance indicators and the benchmarking of actual coordination results against ideal, optimization-based slot allocation outcomes.

The subsequent chapter by Madas and Zografos (Chapter 9) covers a wide range of airport demand management approaches and strategies aiming at mitigating airport congestion through the allocation of scarce capacity (slots) at European Union’s (EU) airports. It provides initial evidence on the need for a new slot allocation regime (e.g. slot misuse, allocation ­inefficiencies, declared capacity considerations, barriers to new entrants, pricing effectiveness) and provides some quantitative insights into the potential impacts of a new congestion management regime. In particular, the authors demonstrate that the aggregate impact is significant in both operational and economic terms. By quantifying delays and their associated costs and comparing them with the existing landing fee scheme applied at European airports, they also show that the actual pricing system of scarce airport infrastructure is quite far from perfect, thus rendering some (mainly the largest and busiest) European airports extremely under-priced. Furthermore, the chapter presents a strategic policy framework ­aiming to provide guidance for the implementation of a new ­congestion-based pricing regime at different types of EU airports. The proposed framework addresses directly the airport ­congestion problem by means of varying congestion fees. It is simple and inexpensive to implement since it is directly compatible with the IATA schedule coordination approach ­currently in use worldwide, but can be also easily customized with local airport needs. The chapter concludes with a discussion of recent efforts and future research directions towards improving or complementing, rather than substituting, the existing slot allocation practice by means of optimization models aimed at controlling strategically the distribution of traffic at the airport level.

The concluding chapter (Chapter 10) of Section III by Ball, Hansen, Swaroop and Zou ­provides the US perspective and experiences with airport congestion management. This chapter provides a critical review of recent attempts in the United States to implement a slot control system that includes the use of auctions for allocating some of the slots. It also ­discusses institutional and political considerations that led to the existing congestion management regime in the United States. Furthermore, the chapter gives an overview of models that provide economic justification of slot controls and discusses a number of design issues/considerations such as the definition of appropriate slot levels, access to small ­communities, (re)distribution of slot revenues, and slot ownership. The authors also address the trade-off between queuing delay and schedule delay as a key determinant of the need for slot controls and the optimal slot control levels. They estimate the slopes of the two curves (queuing and schedule delay) for the largest 35 US airports using two alternative models that attempt to capture the reaction of airlines to reductions in available slots. Despite the ­substantial reluctance to implement slot controls in the United States, the analysis supports the hypothesis that many US airports are overscheduled and provides strong justification for setting slot limits to a number that is often less than the peak airport capacity.

References

Ball, M.O., Barnhart, C., Dresner, M., et al. (2010) Total Delay Impact Study: A Comprehensive Assessment of the Costs and Impacts of Flight Delay in the United States. NEXTOR Technical Report, October 2010.

Eurocontrol (2008) Long-Term Forecast: IFR Flight Movements 2008–2030. Forecast prepared as part of the Challenges of Growth 2008 project, Brussels, Belgium.

Eurocontrol Central Office for Delay Analysis (CODA) (2012) CODA Digest: Delays to Air Transport in Europe (Annual 2011). Report prepared by Eurocontrol’s Central Office for Delay Analysis (CODA), issue published on 14 March, 2012, Brussels, Belgium.

Federal Aviation Administration (2011). FAA Aerospace Forecast: Fiscal Years 2011–2031. [Online] Available from: http://www.faa.gov/about/office_org/headquarters_offices/apl/aviation_forecasts/aerospace_forecasts/2011-2031/media/2011%20Forecast%20Doc.pdf [Accessed 9 December, 2012].

1

Modeling Airport Landside Performance

Anderson Ribeiro CorreiaA and S. C. WirasingheB

A Department of Air Transportation, Aeronautics Institute of Technology, BrazilB Schulich School of Engineering, University of Calgary, Canada

1.1 Motivation for Level of Service Modeling

The motivation for developing level of service (LOS) measures is twofold. First, given that one of the goals of airport planning is to improve, or at least maintain, the level of service experienced by the airport user, it is necessary to be able to measure LOS in order to know whether this goal is being achieved. Second, airport passenger terminal improvements rarely are without expense. To know whether a particular expenditure is justified it is necessary to be able to measure the change in LOS resulting from it (Gosling, 1988).

Establishing measures to evaluate operational performance of the airport landside and quality of service is one of the major problems facing the airlines and airport operators. Humphreys and Francis (2000) affirm that LOS evaluation in American airports have been undertaken at individual airports, with no standard method or reporting system on a national scale. Research is also needed in developing countries, mainly to generate references for planning airport infrastructure. In this regard, Fernandes and Pacheco (2002) stress that the lack of studies, for example in Brazil, to enable parameters reflecting local conditions to be estimated means that estimates made on the basis of conditions at foreign airports are used without proper evaluation. According to them, the issues of domestic traffic, in particular, deserve special attention in terms of Brazilian specifics.

Airport landside LOS and capacity have been topics of research interest over the past two decades or so. More recently, owing to the critical nature of airport LOS issues, a number of studies have been initiated on the identification of the landside problem in general, and on capacity and service measures in particular. Despite all the airport LOS studies developed in the last two decades, the subject is in a rudimentary state of development in comparison with the status of LOS analysis in highway engineering. In 1986 the FAA responded to concerns of inadequate understanding of landside capacity constraints by commissioning the Transportation Research Board to conduct a study of ways to measure airport landside capacity. This study (TRB, 1987) recognized that the capacity of any given landside facility cannot be evaluated without defining acceptable LOS standards, but that there is currently little agreement on how to do this. Lemer (1988) reviewed the study’s principal findings and recommendations. He concluded that the effort represented a valuable first step toward definitive guidelines for capacity assessment, but that much remained to be done. Thus, the development of appropriate ways to measure airport landside LOS is a critical research need.

The measurement of LOS of airport passenger terminals is also an important issue ­considering the recent trends for airport privatization and the need for regulation of privatized facilities. There are concerns that efforts to regulate the prices charged by airports can result in under-investment and decline of service standards. In Australia for example, newly privatized airports would be subjected to price regulation in the form of price-caps on aeronautical charges; there is a concern about their effect on the incentive faced by the enterprise to downgrade quality (Forsyth, 1997). This makes it important to monitor not only the cost-efficiency and cost-effectiveness, but also the service effectiveness of airports (Hooper and Hensher, 1997). Gillen and Lall (1997) agree and state that while airports should be asked to adhere to private financial standards, they must also be judged in the context of their overall goals.

This chapter is composed of three main sections. The first section (Airport Landside Components) provides an overview of current LOS standards developed by researchers or industry organizations. Additionally, this section provides basic recommendations for the use of such standards at planning and management levels. The second section (Methodology for Deriving Quantitative Standards for Individual Components) presents a method, based on the psychometric scaling technique, that any airport authority or organization could apply to develop standards. Finally, the third section (Degree of Importance of Landside Components and Attributes) presents a method, based on the Analytical Hierarchy Process, aimed at obtaining the importance that passengers attribute to individual components and attributes. These measures could be used to obtain an overall terminal LOS evaluation.

1.2 Relationship between Measures of Capacity and Level of Service

LOS and capacity measures are intrinsically correlated. Generally, the efficiency of an airport landside component is evaluated by comparing its capacity values with standard measures of the LOS to passengers. In this concern, the IATA (1995), in its airport development reference manual, has proposed LOS standards in order to evaluate the capacity of airport landside components. Some of these LOS standards will be presented in the next sections. Another initiative to evaluate the relationship between LOS and capacity was developed by Brunetta et al. (1999); in that paper, the authors proposed a model, called SLAM (Simple Landside Aggregate Model), in order to measure capacity and to identify reference values for LOS standards.

Since LOS measures, as space standards, directly affect the capacity of any airport landside component, airport managers and planners should also give special attention to dwell time in these components. Among the several alternatives to improve the efficiency of airport operations and thus decreasing dwell time, include (de Neufville and Odoni, 2002): (1) using electronic check-in kiosks, (2) accelerating board of aircraft, and (3) speeding up passport control processing times.

1.3 Airport Landside Components

In this section, we present the level of service standards and general recommendations for the main domestic airport passenger terminal components: emplaning curbside, check-in counter, security screening, departure lounges and baggage claim.

1.3.1Emplaning Curbside

1.3.1.1 Level of Service Standards

The function of the curbside is to provide an interface between ground access and the airport passenger terminal. It is the first airport component that most passengers pass through for their departing trip. For this reason, the LOS of this facility can influence the first impression ­passengers have regarding the whole airport. In addition to that, because the main function of a curbside is to transfer passengers from the ground transportation system to the terminal building, the entire ground/air linkage will be unbalanced if this area does not operate properly.

For many years, approaches to LOS and capacity problems at the curbside have dealt with vehicles rather than people (Siddiqui, 1994). Most of the previous studies dealt primarily with the length of curbside areas, not considering passengers’ perceptions of other attributes that might influence the LOS evaluation of these facilities, including minimizing walking distances, reducing level changes, and providing space availability for circulation, weather protection, better visual information, lighting and aesthetics.

The traditional approach for curbside LOS evaluation is assessing the curbside utilization as proposed by Mandle et al. (1982), which adopted definitions of LOS for airport curbside planning and design, on the range from A to E, as follows:

Level A: No traffic queues, no double parking.

Level B: Effective curb utilization equal to 1.1 times actual curb frontage.

Level C: Effective curb utilization equal to 1.3 times actual curb frontage.

Level D: Effective curb utilization equal to 1.7 times actual curb frontage.

Level E: Operational breakdowns, effective curb utilization equal to 2.0 times actual curb frontage.

The effective curb utilization is defined as the effective length of the area occupied by vehicles as the actual curb length may differ from effective curb length, due to double or triple parking or undesirable loading/unloading areas. In this viewpoint, the effective length of curb is directly related to the LOS provided at the curb (Figure 1.1).

Figure 1.1 Airport curbside levels of service (Mandle et al., 1982)

1.3.1.2 General Recommendations

Two things can be done to reduce the ECU, (1) increasing the length of the curbside or (2) decreasing the virtual length of cars. The first action is usually adopted at the planning level of a terminal. The length of the curbside required for unloading passengers and baggage is determined by the type and volume of ground vehicle traffic anticipated in the peak period of the design day. The curbside geometry is usually conformed to the geometry of the terminal; any further improvements to this area might not be practical. On the other hand, the virtual (total) length of vehicles can be decreased by reducing the demand on the curbside or reducing the interval that vehicles stay at the curbside. The virtual (total) length of vehicles can also be decreased by reducing their size (e.g., segregating the buses in a special remote area).

Several airports provide free short-term parking. In most of the cases, this time is usually enough to drop off or pick up a passenger. Consequently, the curbside is rarely operated over its capacity. Adding new transit alternatives to the airport can alleviate the demand for the use of cars at the curbside. Some airports are also moving in this direction to alleviate the air pollution in its vicinity. However, the transit alternatives are usually very expensive and just a few airports have enough traffic to afford them.

The most economical way to improve the efficiency of the curbside is by reducing the time vehicles stay at the curbside. For instance, if it were possible to reduce the waiting time at the curbside by 50%, this would result in a 100% increase of the ECU. One way to reduce the time vehicles spend at the curbside is to provide a good orientation system so that drivers will spend a minimum of time looking for space at the curbside.

Enforcement has been applied at many airports to make sure cars do not wait too long or Double Park at the curbside. There is also an anecdotal example from Seattle Airport; the management had a tow truck parked at the curbside on a permanent basis. That procedure motivated the curbside users to stay a shorter time than usual, in the face of the practical ­possibility of having the car towed away (Correia, 2009).

1.3.2Check-in Counter

1.3.2.1 Level of Service Standards

The check-in counter is the most studied airport passenger terminal component. It is usually the first processing component in the terminal, through which passengers pass during the enplaning trip. In this facility, passengers can get their seats assigned, baggage checked, and receive a boarding pass which includes the gate number. However, it is noted that passengers can bypass the check-in at many modern airports if they have no checked baggage and have printed their own boarding pass at home.

The level of service provided at the check-in counter reflects both the airport and airline images. In addition to that, because it is one of the first components in the passenger’s pathway, it can cause delay to other activities and flights. Not only can a poor level of service cause operational problems to airlines and airport administration, it can add to passenger stress, when they are trying to get to the airplane as soon as possible.

One of the first approaches to evaluate check-in LOS, developed by Mumayiz (1985), defined three LOS according to passenger perception of delay. The levels for check-in ­subsystems for scheduled long-haul flights, for example, are defined as:

Level A (good): T < 15 min;

Level B (tolerable): 15 min < T < 25 min;

Level C (bad): T > 25 min.

where T is the time spent at check-in (including waiting).

Table 1.1 represents LOS standards obtained from a study of user perceptions at two ­airports (São Paulo International Airport and Calgary International Airport). The range of waiting time values from LOS A to LOS E at São Paulo is greater than the range at Calgary. That might be due to the fact that in São Paulo there is more variability of flight types than in Calgary. Most of the flights from Calgary have destinations in North America with a few to Europe, as opposed to flights from São Paulo that have domestic destinations, as well as inter-continental flights to Europe, Africa, Asia, North America and Australia. It is also clear that passengers in South America may have very different perceptions about time spent at check-in in comparison with North American passengers. These differences might indicate that LOS standards might differ depending on the flight type (international/intercontinental or domestic/transborder) and the country.

Table 1.1 Suggested check-in counter LOS standards (Correia and Wirasinghe, 2007)

LOS

Waiting Time (min)

São Paulo

Calgary

A

< 1

< 7

B

1–17

7–18

C

17–34

18–26

D

34–58

26–34

E

> 58

> 34

Table 1.2 Suggested check-in counter LOS standards (Correia and Wirasinghe, 2007)

LOS

Processing Time (min)

São Paulo

Calgary

A

< 1

< 5

B

1–14

5–17

C

14–20

17–19

D

20–25

19–20

E

> 25

> 20

Table 1.3 Proposed check-in counter LOS standards

Source: IATA (1995)

Using the same approach, Table 1.2 presents suggested LOS standards for processing times at check-in counters.

Besides considering waiting and processing times, another approach to evaluate check-in LOS is considering space standards, which is the approach proposed by the International Air Transport Association. It provides LOS standards for space available at check-in lines, as follows (Table 1.3).

Past research on LOS for check-in facilities has been concentrated mainly on service times and space available for passengers. A survey with members of the Airports Council International (ACI, 2000) showed that this practice has been widely used. Among the airports surveyed, the main objective criteria used for check-in facilities are the check-in waiting time/queue and check-in transaction time. Nonetheless, Martel and Seneviratne (1990) indicate that, for ­instance, aesthetics is an important attribute of check-in facilities. An objective measurement of the aesthetics variable is difficult to undertake. Obviously any passenger could provide his/her perception about the terminal aesthetics, expressing it by a linguistic variable as good or ­excellent; however, it is difficult to propose any performance variable relative to aesthetics, which could be correlated to the aesthetics LOS passengers ratings. Anyway, it is important that airport planners and managers consider subjective aspects when implementing or managing check-in facilities.

Figure 1.2 Cumulative arrival distribution (TRB, 1987)

1.3.2.2 General Recommendations

An airport will offer a good level of service at the check-in counter when the service is fast and reasonable space is available for passengers. These two characteristics are intrinsically dependent on the number and type of check-in counter desks and automated checking machines and upon the peak demand.

At the planning level, the number of check-in counter desks required is determined as a function of the peak demand and the waiting time acceptable to the passengers. The demand rate at the check-in counter is clearly not uniform.

According to Figure 1.2, during the first 15 min, 6 passengers arrive at a counter at fairly uniform intervals of 2.5 min. The arrival rate then increases, so that by the end of the first half-hour, 10 more people have arrived, for a total of 16. All peak-hour passengers, a total of 20 passengers, have arrived by the end of 55 min. No passenger arrivals are expected during the final 5 min of the peak hour. As it can be noticed, the arrival of passengers is not uniform. This characteristic influences the design and management of check-in counter facilities. In addition to these cumulative arrival distribution curves, there has been a tendency to apply micro-­simulation models to the check-in planning, design and management.

In some markets, a considerable number of passengers may be pre-ticketed, and a higher percentage of automated check-in positions may be warranted either within the terminal building or at the curb front. Self-service kiosks are effective at reducing check-in lines; they can also be equipped with a combination of biometrics to perform identity checks for automated “fast-track” immigration control, self-service check-in or even at security checkpoints (de Barros, 2001). For instance, the adoption of common-use self-service kiosks at Sydney and Melbourne Airports reduced the processing time for check-in to less than one minute (Correia, 2009). Shorter processing times result in shorter waiting times, which mean less people in the queues, reducing the need for space provision. The adoption of common use self-service and/or remote kiosks should be adopted in airport passenger terminals that are faced with long check-in lines.

1.3.3Security Screening

All airline passengers are required to pass through a security screening to ensure in-flight safety. This procedure is required prior to departure both for passengers and for hand luggage before passengers enter the departure lounge. In some airports it is done at the entrance to a concourse. In others, it is done at each gate. The equipment used for this process is X-ray screening and magnetometers, among others. Full body scanners are also rapidly coming into use at international airports for the purpose of secondary screening.

Table 1.4 Suggested security screening LOS standards (Correia, 2009)

LOS

Waiting Time (min)

A

<2

B

2–7

C

7–10

D

10–12

E

>12

Several factors influence the level of service of passenger security areas, including the number of channels, space availability, type of equipment and the courtesy extended by staff. One of the main attributes used to evaluate the level of service of these areas is the waiting time for each passenger. LOS standards for waiting times at the security screening are demonstrated in Table 1.4