Airline Passenger Transportation System: Structure and Dynamics. Lance Sherry 04/2101
|
|
- Anna Brown
- 5 years ago
- Views:
Transcription
1 Airline Passenger Transportation System: Structure and Dynamics Lance Sherry 0/0
2 PreTest A flight from DFW to ABQ has an ontime performance of 70%. For delayed flights the average delay is 0 minutes. The flight is cancelled % of the time. For passengers on cancelled flights the average delay is 0 hours. The typical flight has 00 passengers. The Total Passenger Trip Delay expected is: a) (0.7 * 00 * 0) = 00 mins b) (0. * 00 * 0) = 900 mins c) (0. * 00 * 0) + (0. * 00 * 0) = 000 mins d) (0. * 00 * 0) + (0. * 00 * 600) = 6900 mins
3 Organization. Passenger Transportation System. Itinerary Performance. Network System Performance
4 Passenger Trip Direct Itinerary: Origin Destination Scheduled Departure Time Origin (as ticketed) Scheduled Arrival Time Destination (as ticketed) Flight Number Flight Seat Capacity Type: Direct D H Direct Connectiing Time Connecting Itinerary Origin Hub Destination OriginHub Scheduled Departure Time origin (as ticketed) Scheduled Arrival Time Hub (as ticketed) Flight Number Flight Seat Capacity HubDestination Scheduled Departure Time origin (as ticketed) Scheduled Arrival Time Hub (as ticketed) Flight Number Flight Seat Capacity Type: Direct O
5 Itinerary Performance 5
6 Itinerary Performance Passenger Trip Delay = Actual Passenger Arrival Time Scheduled (i.e. Ticketed) Arrival Time Disruptions resulting in Passenger Trip Delays. Delayed flights. Cancelled flights. Diverted flights. Denied Boarding 5. Missed Connections 6
7 Passenger Trip Delays Direct Itin Delayed Flight Pax Trip Delay Ticketed Arrival Time Actual Arrival Time 5 min D DelayedFlight Probability of Pax Trip Delay Probability Flight Delay > 5 minutes P DelayedFlight () D O Probability Pax Trip Delay 5 min Pax Delay Average Delay > 5 mins 7
8 Passenger Trip Delays Direct Itin Cancelled Flight Pax Trip Delay Ticketed Arrival Time Actual Arrival Time D CancelledFlight = f (Frequency of Service OD) Probability of Pax Trip Delay Probability Flight Cancelled P CancelledFlight () D O X 5 min Pax Delay 8
9 Passenger Trip Delays Connected Itin Probability Pax Trip Delay Delayed Flight Pax Trip Delay Ticketed Arrival Time Actual Arrival Time 5 min D DelayedFlight HD = f (Frequency of Service OD) Probability of Pax Trip Delay Probability HD Flight Delay > 5 minutes P DelayedFlight HD D H O 5 min Pax Delay Min Connecting Window Average Delay > 5 mins 9
10 Passenger Trip Delays Connected Itin Cancelled Flight (OH) Pax Trip Delay Ticketed Arrival Time Actual Arrival Time 5 min D CancelledFlight withconnection = f (Frequency of Service OH, HD) Probability of Pax Trip Delay Probability OH Cancelled P CancelledFlightOH () D H O X Pax Delay Min Connecting Window 0
11 Passenger Trip Delays Connected Itin Cancelled Flight (HD) Pax Trip Delay Ticketed Arrival Time Actual Arrival Time 5 min D CancelledFlight = f (Frequency of Service HD) Probability of Pax Trip Delay Probability HD Cancelled P cancelledflightoh () D H O X Pax Delay Min Connecting Window
12 Passenger Trip Delays Connected Itin Missed Connection Flight Pax Trip Delay Ticketed Arrival Time Actual Arrival Time 5 min D MissedConnectionFlight = f (Frequency of Service OD) Probability of Pax Trip Delay Probability OH Flight Delay > 5 minutes AND Probability Pax Misses Connection P DelayedFlightOH * P MissedConnection () D H O Pax Delay Min Connecting Window Probability Missed Connection = Probability OH is Delayed beyond Min Connecting Window to HD
13 Passengers on Cancelled Flights (.8%, Avg hours) Passengers on Diverted Flights (0.%, Avg.5 hours) Passengers Denied Boarding on Oversold Flights (<0.00%) Passengers on Delayed Flights (.9%, Avg 57 minutes) Passengers OnTime < 5 Minutes Delay (7%) The Passenger Trip Game Wheel Not drawn to scale
14 Passenger Itin Load Factor Flight Performance For Each Passenger Itinerary O to H Cancelled Connecting Itin H to D Cancelled Compute Flight Delay for Diverted Flight Missed Connectio n O to H Diverted Direct or Connecting H to D Diverted Direct Itin O to D Cancelled Compute Flight Delay for Diverted Flight Compute Pax Delay for Diverted Pax Denied Boarding Not Shown, same as cancelled O to D Diverted Compute Pax Delay For Delayed Flight H to D Delayed Compute Pax Delay for Diverted Pax Missed Connection O to H Delayed Rebook Pax O to D and Compute Pax Delays Rebook Pax H to D and Compute Pax Delay Compute Pax Delay For Delayed Flight H to D Delayed
15 Calculating Passenger Trip Delay Scheduled Departure Time Schduled Arrival Time Seats # Pax Flight Status Delay Pax Trip Delay OD 06:00 08: Delayed 0 mins 00* 0 OD 06:0 08: Cancelled (0 * 0) +(50 * (0 +0)+ +(0 * 60) OHD 06:0 0: OnTime 0 OD 09:0 : Delayed 0 mins 00*0 OHD :00 5: OnTime 0 5
16 Passenger Trip Delays Passengers on Direct Itinerary: Expected Pax Trip Delay = ( P DelayedFlight () * D DelayedFlight ) + (P CancelledFlight () * D CancelledFlight * f (Frequency of Service OD) Probability of Disrupted Trip = ( P DelayedFlight () + (P CancelledFlight () ) 6
17 Passenger Trip Delay Passenger on Connecting Itinerary: Expected Pax Trip Delay = ( P DelayedFlight () HD * D DelayedFlight ) + ( P DelayedFlight () OH * P MissedConnection () * D DelayedFlight ) + (P CancelledFlight () OH * D CancelledFlight * f (Frequency of Service OD) ) + (P CancelledFlight () HD * D CancelledFlight * f (Frequency of Service OD) ) Probability of Disrupted Trip = ( P DelayedFlight () HD ) + ( P DelayedFlight () OH * P MissedConnection () ) + (P CancelledFlight () OH ) + (P CancelledFlight () HD ) 7
18 Itinerary Performance Expected Pax Trip Delay ( P DelayedFlight () HD * D DelayedFlight ) + ( P DelayedFlight () OH * P MissedConnection () * D DelayedFlight ) + (P CancelledFlight () OH * D CancelledFlight = f (Frequency of Service OD) ) + (P CancelledFlight () HD * D CancelledFlight = f (Frequency of Service OD) ) ( P DelayedFlight () * D DelayedFlight ) + (P CancelledFlight () * D CancelledFlight = f (Frequency of Service OD) Direct Itin 0% Connecting Itin/ 70% Direct Connecting Itin 8
19 Network Performance 9
20 Passenger Trip Delays in a Transportation System Markets Five Located in same Time Zone Equal distance apart Transportation Service at each Market Each market has own airport Travel time = Unit Time between airports (e.g. Travel Time to = ) 5 0
21 Transportation Demand Transportation demand 00 trips to each Destination Market 00 trips from each Origin Market trips from each Origin market to each Destination Market 500 trips total Passengers are required to be at Destination for start of day Demand for travel at each Origin to arrive at Destination at start of day (shown on right) 00 pax leave each market 00 pax arrive at each market 5 Demand to each Market Start of Day at Destination Time of Day
22 Direct Flight Network Total Passengers = 500 Total Itineraries = 0 # Flights = * 5 = 0 Aircraft Size seats Distance Traveled = = 0 Total Trip Time = 0 Total Arrival Displacement Time = 0 (all pax arrive at required time) Average Trip Time = 0/ + 0/ + 7/ + 7/ + 6/ Max Simultaneous Arrivals at each airport = (at each airport) Max Simultaneous use of airspace = 5 (at each TRACON) 5 Desired Arrival Time
23 Direct Flight Network Origin Originating Pax Destination Itinerary = Flights 5 5 Pax per Itineray = Flight Trip Time Arrival Displacement TOTAL
24 HubnSpoke Network Total Passengers = 500 Total Itineraries = 0 # Flights = + = 8 Aircraft Size = 00 seats Distance Traveled = Total Trip Time = (+++5) + (+++)+ (+++)+ (+++)+ (5+++)=60 Total Arrival Displacement Time = (some pax arrive earlier than needed) Average Trip Time = 60/6 Max Simultaneous Arrivals at each airport = (at hub only) Max Simultaneous use of airspace = (at hub TRACON only) 5 Start of Day
25 HubnSpoke: Itinerary Table Origin Originating Pax Destinatio n Itinerary Pax per Itinerary Total Trip Time 5 5 Arrival Displacement (Early) TOTAL
26 HubnSpoke: Flight Table Origin Destination Pax per Flight Total Trip Time
27 Passenger Transportation System: Network Performance Airport & Airspace Capacity Flight Schedules = Frequency of Service, Turnaround Times Flight Performance P(D), P(C), P(MC) Ddelay, Dcancelled, DMissedConn Itinerary (Direct., Connecting) Load Factor Seat Capacity Pax Transportation Performance Total Pax Trip Delay % Disrupted Pax, Disrupted Pax Delay Performance Characteristics Performance Metrics 7
28 Network Performance Characteristics Transportation System has: 6 itineraries 500 trips Transportation Service is provided by: Network Structure Direct Flights vs. HubnSpoke Each Flight has: Seat Capacity = SC Seat Utilization = Load Factor = LF Likelihood of experiencing delay = P(D) Likelihood of cancellation = P(C) Each Trip has Average Trip Delay Trip Delay due to Delayed Flight = DDelayedFlight Trip Delay due to Cancelled Flight = DCancelledFlight Trip Delay due to Missed Connection = DMissedConnection 8
29 Network Performance Total Passenger Trip Delays = Total Passenger Trip Delay from Delayed Flights + Total Passenger Trip Delay from Cancelled Flights Total Passenger Trip Delay from Delayed Flights = i=,n, j=,n LF OiDj *SC OiDj * P(D) OiDj * D DelayedFlight OiDj Total Passenger Trip Delay from Cancelled Flights = i=,n, j=,n LF OiDj *SC OiDj * P(C) OiDj * D CancelledFlight OiDj 9
30 Network Performance Under assumption of homogeneous fleet, flight leg performance. LF OD = LF OD =LF OD = = LF SC OD = SC OD = SC OD = = SC P(D) OD = P(D) OD= P(D) OD = = P(D) D DelayedFlight OD = D DelayedFlight OD =. = D DelayedFlight Total Passenger Trip Delay from Delayed Flights = i=,n, j=,n LF OiDj *SC OiDj * P(D) OiDj * D DelayedFlight OiDj = #Flights * LF * SC * P(D) * D DelayedFlight 0
31 Performance Metrics. % Disrupted Passengers Total Disrupted Passengers Passengers on Delayed Flights Passengers on Cancelled Flights. Total Passenger Trip Delay. Average Passenger Trip Delay. Average Disrupted Passenger Trip Delays Average Passenger Trip Delays due to Delayed Flights Average Passenger Trip Delays due to Cancelled Flights Average Passenger Trip Delays due to Missed Connections
32 Performance: Direct Network Total Disrupted Passengers = [P(D) + P(C)] *(#Flights*LF*SC) % Passengers Disrupted = P(D)+P(C) Total Passenger Trip Delay = #Flights*LF*SC [(P(D)* D DelayedFlight )+ (P(C)* D CancelledFlight )] Average Trip Delay = Total Passenger Trip Delay/#Pax Average Disrupted Passenger Trip Delays = Total Passenger Trip Delay/Total Disrupted Passengers
33 Performance: HubnSpoke Network Total Disrupted Passengers = ( P(D) HD * #Flights HD * LF*SC) + (P(D) OH * P(MC) * #Flights HD * LF*SC) + (P(C) OH *#Flights OH *LF*SC) + (P(C) HD *#Flights HD *LF*SC) % Passengers Disrupted = P(D) + [P(D)*P(MC)] + P(C) Total Passenger Trip Delay = ( P(D) HD * #Flights HD * LF * SC *D DelayedFlight ) + (P(D) OH * P(MC) * #Flights HD * LF*SC *D MissedConnection ) + (P(C) OH * #Flights OH * LF* SC * D CancelledFlight ) + (P(C) HD * #Flights HD * LF * SC * D CancelledFlight ) Average Trip Delay = Total Passenger Trip Delay/#Pax
34 Network Performance Total Pax Trip Delay ( P(D) HD * #Flights HD * LF*SC *D DelayedFlight ) + (P(D) OH * P(MC) * #Flights HD * LF*SC *D MissedConnection ) + (P(C) OH *#Flights OH *LF*SC*D CancelledFlight ) + (P(C) HD *#Flights HD *LF*SC*D CancelledFlight ) #Flights*LF*SC [(P(D)* D DelayedFlight )+ (P(C)* D CancelledFlight )] Direct Itin 0% Connecting Itin/ 70% Direct Connecting Itin
35 PASSENGER Change Change TRIP DEMAND to to 09 AND CAPACITY Passenger Itineraries (M) % 9% Direct (M) % 0% Connecting(M) 7 96 % 6% % Connect 0 +% +% Flights (millions) % 8% Frequency of Service (average flights per day) % 8% DISRUPTED Change Change PASSENGERS 07 to to 09 % Passengers % 0% 7% 0% 6% Total Passengers Disrupted % % (millions) Average Disrupted Passenger Trip Delay (minutes) % % OF PASENGERS ON Delayed Flights Cancelled Flights Diverted Flights Missed Connections % 6.5 % Change 07 to 08 Change 08 to 09 %.5% 9.8%.7%.6%.% 9% % 0.% 0.% 0.% +7.8% 5.8%.7%.5%.% % % AVERAGE TRIP DELAY Passengers on Delayed Flights (mins) Passengers on Cancelled Flights (mins) Passengers on Diverted Flights (mins) Passengers with Missed Connections (mins) TOTAL DISRUPTED PASSENGERS Change 07 to 08 TOTAL PASSENGER TRIP DELAYS Total Passenger Trip Delays (million hours) Average Passenger Trip Delay (minutes) Change 08 to % 0% % 8.6% %.% 9 0.8% 7.% % OF TOTAL PASSENGER TRIP DELAY Passengers on Delayed Flights (mins) Passengers on Cancelled Flights (mins) Passengers on Diverted Flights (mins) Passengers with Missed Connections (mins) Change 07 to 08 Change 08 to % 6% 6 6% % Change 07 to 08 Change 08 to 09 % % % % 5% 5% 5% 9% 0% % 0% 0% % % 69% % % 6% 7% % % OF TOTAL PASSENGER TRIP DELAY Passengers required to stay overnight % of Total Itineraries 0.% 0.% 0.% % of Cancelled Itineraries.6%.8% 9.9% 5
The Journal of Air Traffic Control, Volume 53, #3, August 2011
Modeling Passenger Trip Reliability: Why NextGen may not Improve Passenger Delays Lance Sherry Center for Air Transportation Systems Research at George Mason University Director/Associate Professor The
More informationVista Vista consultation workshop. 23 October 2017 Frequentis, Vienna
Vista Vista consultation workshop 23 October 2017 Frequentis, Vienna Objective of the model Vista model aims at: Simulating one day of traffic in Europe to the level of individual passengers Being able
More informationRUNWAY OPERATIONS: Computing Runway Arrival Capacity
RUNWAY OPERATIONS: Computing Runway Arrival Capacity SYST 560/460 USE Runway Capacity Spreadsheet Fall 2008 Lance Sherry 1 CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH Background Air Transportation System
More informationAirline Scheduling Optimization ( Chapter 7 I)
Airline Scheduling Optimization ( Chapter 7 I) Vivek Kumar (Research Associate, CATSR/GMU) February 28 th, 2011 CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH 2 Agenda Airline Scheduling Factors affecting
More informationModelling Airline Network Routing and Scheduling under Airport Capacity Constraints
Modelling Airline Network Routing and Scheduling under Airport Capacity Constraints Antony D. Evans Andreas Schäfer Lynnette Dray 8 th AIAA Aviation Technology, Integration, and Operations Conference /
More informationIAB / AIC Joint Meeting, November 4, Douglas Fearing Vikrant Vaze
Passenger Delay Impacts of Airline Schedules and Operations IAB / AIC Joint Meeting, November 4, 2010 Cynthia Barnhart (cbarnhart@mit edu) Cynthia Barnhart (cbarnhart@mit.edu) Douglas Fearing (dfearing@hbs.edu
More informationCongestion. Vikrant Vaze Prof. Cynthia Barnhart. Department of Civil and Environmental Engineering Massachusetts Institute of Technology
Frequency Competition and Congestion Vikrant Vaze Prof. Cynthia Barnhart Department of Civil and Environmental Engineering Massachusetts Institute of Technology Delays and Demand Capacity Imbalance Estimated
More informationAbstract. Introduction
COMPARISON OF EFFICIENCY OF SLOT ALLOCATION BY CONGESTION PRICING AND RATION BY SCHEDULE Saba Neyshaboury,Vivek Kumar, Lance Sherry, Karla Hoffman Center for Air Transportation Systems Research (CATSR)
More informationAirline Schedule Development Overview Dr. Peter Belobaba
Airline Schedule Development Overview Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 18 : 1 April 2016
More informationRoute Planning and Profit Evaluation Dr. Peter Belobaba
Route Planning and Profit Evaluation Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 9 : 11 March 2014
More informationNAS Performance Models. Michael Ball Yung Nguyen Ravi Sankararaman Paul Schonfeld Luo Ying University of Maryland
NAS Performance Models Michael Ball Yung Nguyen Ravi Sankararaman Paul Schonfeld Luo Ying University of Maryland FAA Strategy Simulator: analyze impact on NAS of major policy initiatives/changes significant
More informationFundamentals of Airline Markets and Demand Dr. Peter Belobaba
Fundamentals of Airline Markets and Demand Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 10: 30 March
More informationAssignment 3: Route Fleet Assignment Michael D. Wittman
Assignment 3: Route Fleet Assignment Michael D. Wittman Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module A3 : 12 March 2014
More informationOverview of Boeing Planning Tools Alex Heiter
Overview of Boeing Planning Tools Alex Heiter Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 16: 31 March 2016 Lecture Outline
More informationDanyi Wang and Dr. Lance Sherry 1
Danyi Wang and Dr. Lance Sherry 1 Trend Analysis of Airline Passenger Trip Delays Danyi Wang (Ph.D Candidate) Email: dwang2@gmu.edu Phone: 571-277-0287 Lance Sherry (Ph.D) Email: lsherry@gmu.edu Phone:
More informationCDM Quick Reference Guide. Concepts I Need to Know for the Exam
CDM Quick Reference Guide Concepts I Need to Know for the Exam 1 What is the principle behind CDM? Sharing information between: ATC (al parts System Command & Control, Centers, TRACONS, Towers) Airlines
More information(Avg Airfare * AS) 2. Column 3: Calculate the Total Revenue for each combination of Average Airfare and Cumulative Passenger Travel Demand (20 pts)
Air Transportation Economics (210 pts) Eventually Airlines has plans to offer service between an Origin and a Destination for a specified time period (i.e. 6a.m. to 10a.am.). You are responsible for determining
More informationQUANTIFYING THE BENEFITS OF PRE-EMPTIVE REBOOKING: A CASE STUDY FOR A NETWORK CARRIER (JAN 12, 2012)
QUANTIFYING THE BENEFITS OF PRE-EMPTIVE REBOOKING: A CASE STUDY FOR A NETWORK CARRIER (JAN 12, 2012) Lance Sherry (Ph.D.), Sanja Avramovic (Ph.D. Candidate) Center for Air Transportation Systems Research
More informationNAS Performance and Passenger Delay
NAS Performance and Passenger Delay Michael Ball NEXTOR University of California, Berkeley & University of Maryland Coauthors: Andy Churchill, Bargava Subramanian, Alex Tien On-Time Performance On-Time
More informationAircraft Arrival Sequencing: Creating order from disorder
Aircraft Arrival Sequencing: Creating order from disorder Sponsor Dr. John Shortle Assistant Professor SEOR Dept, GMU Mentor Dr. Lance Sherry Executive Director CATSR, GMU Group members Vivek Kumar David
More informationDemand, Load and Spill Analysis Dr. Peter Belobaba
Demand, Load and Spill Analysis Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 13 : 12 March 2014 Lecture
More informationMIT ICAT. MIT ICAT M I T I n t e r n a t i o n a l C e n t e r f o r A i r T r a n s p o r t a t i o n
M I T I n t e r n a t i o n a l C e n t e r f o r A i r T r a n s p o r t a t i o n BENEFITS OF REVENUE MANAGEMENT IN COMPETITIVE LOW-FARE MARKETS Dr. Peter Belobaba Thomas Gorin IATA REVENUE MANAGEMENT
More informationNew Developments in RM Forecasting and Optimization Dr. Peter Belobaba
New Developments in RM Forecasting and Optimization Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 24
More informationInter-modal Substitution (IMS) in Airline Collaborative Decision Making
Inter-modal Substitution (IMS) in Airline Collaborative Decision Maing Yu Zhang UC Bereley NEXTOR Seminar Jan. 20, 2006 FAA, Washington D.C. 1 Road Map Introduction Delay In National Airspace System (NAS)
More informationCorporate Productivity Case Study
BOMBARDIER BUSINESS AIRCRAFT Corporate Productivity Case Study April 2009 Marketing Executive Summary» In today's environment it is critical to have the right tools to demonstrate the contribution of business
More informationDanyi Wang and Dr. Lance Sherry 1
Danyi Wang and Dr. Lance Sherry 1 Trend Analysis of Airline Passenger Trip Delays Danyi Wang (Ph.D Candidate) Email: dwang2@gmu.edu Phone: 571-277-0287 Lance Sherry (Ph.D) Email: lsherry@gmu.edu Phone:
More informationMetrics and Representations
6th International Conference in Air Transport 27th-30th May 2014. Istanbul Technical University Providing insight into how to apply Data Science in aviation: Metrics and Representations Samuel Cristóbal
More informationApproximate Network Delays Model
Approximate Network Delays Model Nikolas Pyrgiotis International Center for Air Transportation, MIT Research Supervisor: Prof Amedeo Odoni Jan 26, 2008 ICAT, MIT 1 Introduction Layout 1 Motivation and
More informationAir Carrier E-surance (ACE) Design of Insurance for Airline EC-261 Claims
Air Carrier E-surance (ACE) Design of Insurance for Airline EC-261 Claims May 06, 2016 Tommy Hertz Chris Saleh Taylor Scholz Arushi Verma Outline Background Problem Statement Related Work and Methodology
More informationFrom Planning to Operations Dr. Peter Belobaba
From Planning to Operations Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 16 : 13 March 2014 Lecture
More informationOnline Appendix to Quality Disclosure Programs and Internal Organizational Practices: Evidence from Airline Flight Delays
Online Appendix to Quality Disclosure Programs and Internal Organizational Practices: Evidence from Airline Flight Delays By SILKE J. FORBES, MARA LEDERMAN AND TREVOR TOMBE Appendix A: Identifying Reporting
More informationTarmac Delay Policies: A Passenger-Centric Analysis
Tarmac Delay Policies: A Passenger-Centric Analysis Chiwei Yan a,1, Vikrant Vaze b, Allison Vanderboll c and Cynthia Barnhart a a Operations Research Center, Massachusetts Institute of Technology, USA
More informationService Reliability Measurement using Oyster Data
Service Reliability Measurement using Oyster Data - A Framework for the London Underground David L. Uniman MIT TfL January 29 1 Introduction Research Objective To develop a framework for quantifying reliability
More informationSERVICE NETWORK DESIGN: APPLICATIONS IN TRANSPORTATION AND LOGISTICS
SERVICE NETWORK DESIGN: APPLICATIONS IN TRANSPORTATION AND LOGISTICS Professor Cynthia Barnhart Massachusetts Institute of Technology Cambridge, Massachusetts USA March 21, 2007 Outline Service network
More informationmaking air travel smarter 2016 Resilient Ops, Inc.
making air travel smarter Don t just react to flight delays manage them ~30,000 passengers will fly into Orlando from within the US each day On average, 2,500 of those passengers will have their plans
More informationepods Airline Management Educational Game
epods Airline Management Educational Game Dr. Peter P. Belobaba 16.75J/1.234J Airline Management March 1, 2006 1 Evolution of PODS Developed by Boeing in early 1990s Simulate passenger choice of airline/paths
More informationREAL-TIME ALERTING OF FLIGHT STATUS FOR NON-AVIATION SUPPLIERS IN THE AIR TRANSPORTATION SYSTEM VALUE CHAIN
REAL-TIME ALERTING OF FLIGHT STATUS FOR NON-AVIATION SUPPLIERS IN THE AIR TRANSPORTATION SYSTEM VALUE CHAIN Abstract: Lance Sherry (Ph.D.), Oleksandra Snisarevska (M.Sc. Candidate), lsherry@gmu.edu Center
More informationSimulation of disturbances and modelling of expected train passenger delays
Computers in Railways X 521 Simulation of disturbances and modelling of expected train passenger delays A. Landex & O. A. Nielsen Centre for Traffic and Transport, Technical University of Denmark, Denmark
More informationAirline Network Structures Dr. Peter Belobaba
Airline Network Structures Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 8: 11 March 2014 Lecture Outline
More informationIstanbul Technical University Air Transportation Management, M.Sc. Program Aviation Economics and Financial Analysis Module November 2014
Pricing Istanbul Technical University Air Transportation Management, M.Sc. Program Aviation Economics and Financial Analysis Module 11 14 November 2014 Outline Revenue management Fares Buckets Restrictions
More informationInvestigating the Effect of Flight Delays and Cancellations on Travel from Small Communities
University of Massachusetts Amherst ScholarWorks@UMass Amherst Tourism Travel and Research Association: Advancing Tourism Research Globally 2015 ttra International Conference Investigating the Effect of
More informationEstimating Avoidable Delay in the NAS
Estimating Avoidable Delay in the NAS Bala Chandran Avijit Mukherjee Mark Hansen Jim Evans University of California at Berkeley Outline Motivation The Bertsimas-Stock model for TFMP. A case study: Aug
More informationOverview of PODS Consortium Research
Overview of PODS Consortium Research Dr. Peter P. Belobaba MIT International Center for Air Transportation Presentation to ATPCO Dynamic Pricing Working Group Washington, DC February 23, 2016 MIT PODS
More informationAirline network optimization. Lufthansa Consulting s approach
Airline network optimization Lufthansa Consulting s approach A thorough market potential analysis lays the basis for Lufthansa Consulting s network optimization approach The understanding of the relevant
More informationMIT ICAT. Robust Scheduling. Yana Ageeva John-Paul Clarke Massachusetts Institute of Technology International Center for Air Transportation
Robust Scheduling Yana Ageeva John-Paul Clarke Massachusetts Institute of Technology International Center for Air Transportation Philosophy If you like to drive fast, it doesn t make sense getting a Porsche
More informationEstimating Domestic U.S. Airline Cost of Delay based on European Model
Estimating Domestic U.S. Airline Cost of Delay based on European Model Abdul Qadar Kara, John Ferguson, Karla Hoffman, Lance Sherry George Mason University Fairfax, VA, USA akara;jfergus3;khoffman;lsherry@gmu.edu
More informationHOW MUCH MONEY COULD PASSENGERS EARN IF THE U.S. HAD EUROPEAN AIRLINE CONSUMER PROTECTION LAWS?
HOW MUCH MONEY COULD PASSENGERS EARN IF THE U.S. HAD EUROPEAN AIRLINE CONSUMER PROTECTION LAWS? Lance Sherry Center for Air Transportation Systems Research at George Mason University, Fairfax, Virginia
More informationAirline Operating Costs Dr. Peter Belobaba
Airline Operating Costs Dr. Peter Belobaba Istanbul Technical University Air Transportation Management M.Sc. Program Network, Fleet and Schedule Strategic Planning Module 12: 30 March 2016 Lecture Outline
More informationAviation Economics & Finance
Aviation Economics & Finance Professor David Gillen (University of British Columbia )& Professor Tuba Toru-Delibasi (Bahcesehir University) Istanbul Technical University Air Transportation Management M.Sc.
More informationAviation Trends. Quarter Contents
Aviation Trends Quarter 1 2013 Contents Introduction 2 1 Historical overview of traffic 3 a Terminal passengers b Commercial flights c Cargo tonnage 2 Terminal passengers at UK airports 7 3 Passenger flights
More informationREAL OPTIONS ANALYSIS: RUNWAY EXPANSION AT A NEW AIRPORT IN LISBON
REAL OPTIONS ANALYSIS: RUNWAY EXPANSION AT A NEW AIRPORT IN LISBON Julia Nickel December 2007 lass project in ESD.71,Engineering Systems Analysis for Design Massachusetts Institute of Technology Problem
More informationUC Berkeley Working Papers
UC Berkeley Working Papers Title The Value Of Runway Time Slots For Airlines Permalink https://escholarship.org/uc/item/69t9v6qb Authors Cao, Jia-ming Kanafani, Adib Publication Date 1997-05-01 escholarship.org
More informationEvaluation of Predictability as a Performance Measure
Evaluation of Predictability as a Performance Measure Presented by: Mark Hansen, UC Berkeley Global Challenges Workshop February 12, 2015 With Assistance From: John Gulding, FAA Lu Hao, Lei Kang, Yi Liu,
More informationENHANCING AIRLINE HANDLING OF LARGE SCALE FLIGHT CANCELATION EVENTS THROUGH PRE-EMPTIVE REBOOKING
ENHANCING AIRLINE HANDLING OF LARGE SCALE FLIGHT CANCELATION EVENTS THROUGH PRE-EMPTIVE REBOOKING Sanja Avramovic, Ph.D. Lance Sherry, Ph.D., lsherry@gmu.edu, 703-993-1711 Center for Air Transportation
More informationAviation Trends. Quarter Contents
Aviation Trends Quarter 3 2014 Contents Introduction... 2 1. Historical overview of traffic... 3 a. Terminal passengers... 4 b. Commercial flights... 5 c. Cargo tonnage... 6 2. Terminal passengers at UK
More informationUnited s service disruption policies
United s service disruption policies Overview and application guide for travel agency self-service tools April 2015 United makes proactive and reactive waiver tools available Proactive Reactive Exception
More informationANNEX C. Maximum Aircraft Movement Data and the Calculation of Risk and PSZs: Cork Airport
ANNEX C Maximum Aircraft Movement Data and the Calculation of Risk and PSZs: Cork Airport CONTENTS C1 INTRODUCTION C1 C2 SUMMARY OF INPUT DATA C2 C3 AIRCRAFT CRASH RATE C5 C3.1 AIRCRAFT CLASSIFICATION
More informationINCENTIVE PROGRAM
LIMAK KOSOVO INT L AIRPORT J.S.C. PRISTINA INTERNATIONAL AIRPORT "ADEM JASHARI" INCENTIVE PROGRAM 2018 2020 (25 March 2018 28 March 2020) 1 ARTICLE 1: OBJECTIVE The objective of the Incentive Program is
More informationProject: Implications of Congestion for the Configuration of Airport Networks and Airline Networks (AirNets)
Research Thrust: Airport and Airline Systems Project: Implications of Congestion for the Configuration of Airport Networks and Airline Networks (AirNets) Duration: (November 2007 December 2010) Description:
More informationNanaimo Airport Aviation Activity and Forecasts June 2007 B-1 EXECUTIVE SUMMARY
Nanaimo Airport Aviation Activity and Forecasts June 2007 B-1 Introduction EXECUTIVE SUMMARY The Nanaimo Airport Commission engaged Jacobs Consultancy Canada Inc. (JC) to review the historic traffic trends
More informationTHE FUNDAMENTALS OF ROUTE DEVELOPMENT UNDERSTANDING AIRLINES MODULE 3
THE FUNDAMENTALS OF ROUTE DEVELOPMENT UNDERSTANDING AIRLINES AIRLINE ISSUES Low margins Fuel price uncertainty Vulnerability to economic downturn Unpredictable one-time events High profits of airports
More informationSPADE-2 - Supporting Platform for Airport Decision-making and Efficiency Analysis Phase 2
- Supporting Platform for Airport Decision-making and Efficiency Analysis Phase 2 2 nd User Group Meeting Overview of the Platform List of Use Cases UC1: Airport Capacity Management UC2: Match Capacity
More informationANALYSIS OF THE CONTRIUBTION OF FLIGHTPLAN ROUTE SELECTION ON ENROUTE DELAYS USING RAMS
ANALYSIS OF THE CONTRIUBTION OF FLIGHTPLAN ROUTE SELECTION ON ENROUTE DELAYS USING RAMS Akshay Belle, Lance Sherry, Ph.D, Center for Air Transportation Systems Research, Fairfax, VA Abstract The absence
More informationEconomic Impact for Airlines from Air Traffic Control Tower Modernization at LaGuardia Airport
Economic Impact for Airlines from Air Traffic Control Tower Modernization at LaGuardia Airport Presented at SCEA Marc Rose, MCR LLC 202-548-5584 mrose@mcricom 24 June 2007 MCR, LLC MCR Proprietary - Distribution
More informationSchedule Change 300 Mile Radius
Schedule Change 300 Mile Radius Return to Schedule Change - Main Index AA Flights 300-Mile Radius Travel Agents may apply 300-Mile radius for the following reasons: Discontinued service without an alternate
More informationPricing and Revenue Management
Pricing and Revenue Management Dr Robert Mayer Istanbul Technical University Air Transportation Management, M.Sc. Program Strategy Module April 2016 Lecture Overview Pricing and the Marketing Mix Revenue
More informationNO COMPENSATION PAYMENTS PURSUANT TO REGULATION (EC) No. 261/2004 IN CASE OF STRIKES?
[2012] T RAVEL L AW Q UARTERLY 275 NO COMPENSATION PAYMENTS PURSUANT TO REGULATION (EC) No. 261/2004 IN CASE OF STRIKES? Katharina-Sarah Meigel & Ulrich Steppler In this article the authors provide hope,
More informationConsumer Council update for passengers affected by flight cancellations due to the volcanic ash cloud
Consumer Council update for passengers affected by flight cancellations due to the volcanic ash cloud Tuesday 11 May 2010 There are currently no restrictions on UK airspace. The majority of flights to
More informationThe Impact of Baggage Fees on Passenger Demand, Airfares, and Airline Operations in the US
The Impact of Baggage Fees on Passenger Demand, Airfares, and Airline Operations in the US Martin Dresner R H Smith School of Business University of Maryland The Institute of Transport and Logistics Studies
More information15:00 minutes of the scheduled arrival time. As a leader in aviation and air travel data insights, we are uniquely positioned to provide an
FlightGlobal, incorporating FlightStats, On-time Performance Service Awards: A Long-time Partner Recognizing Industry Success ON-TIME PERFORMANCE 2018 WINNER SERVICE AWARDS As a leader in aviation and
More informationPerformance monitoring report 2017/18
Performance monitoring report /18 Gatwick Airport Limited 1. Introduction Date of issue: 20 July 2018 This report provides an update on performance at Gatwick in the financial year /18, ending 31 March
More informationManaging And Understand The Impact Of Of The Air Air Traffic System: United Airline s Perspective
Managing And Understand The Impact Of Of The Air Air Traffic System: United Airline s Perspective NEXTOR NEXTOR Moving Moving Metrics: Metrics: A Performance-Oriented View View of of the the Aviation Aviation
More informationDFLEX (DEPARTURE FLEXIBILITY) When Airport CDM becomes a reality!
DFLEX (DEPARTURE FLEXIBILITY) When Airport CDM becomes a reality! 1 DFlex a step beyond the Airport CDM European Airport CDM: Information Sharing btw airport, aircraft operators, handlers, ATC, NM All
More informationRegional Jets ,360 A319/ , , , ,780
Excel Tab Name: Seats (18 MAP) PASSENGER AIRLINE FLIGHT SCHEDULE CALCULATION RECORD Summary 17.2 MAP flight schedule* (with Southwest Airlines B737-800s changed to B737-700s) Number of Total Seats Avg.
More informationAirport s Perspective of Traffic Growth and Demand Management CANSO APAC Conference 5-7 May 2014, Colombo, Sri Lanka
Airport s Perspective of Traffic Growth and Demand Management CANSO APAC Conference 5-7 May 2014, Colombo, Sri Lanka SL Wong Senior Manager - Technical & Industry Affairs The Question I Try to Answer How
More informationEvaluation of Strategic and Tactical Runway Balancing*
Evaluation of Strategic and Tactical Runway Balancing* Adan Vela, Lanie Sandberg & Tom Reynolds June 2015 11 th USA/Europe Air Traffic Management Research and Development Seminar (ATM2015) *This work was
More informationCustomer service and contingency plans For Flights between Bolivia and the United States
Customer Service Plan Customer service and contingency plans For Flights between Bolivia and the United States The following shall consist of the customer service plan for Boliviana de Aviacion ( BoA ).
More informationSchedule Change 300 Mile Radius
Schedule Change 300 Mile Radius Return to Schedule Change - Main Index AA Flights 300-Mile Radius Travel Agents may apply 300-Mile radius for the following reasons: Additional Ticketing/Itinerary Information
More informationAirport Evolution and Capacity Forecasting
Internet: www.gap-projekt.de Contact: info@gap-projekt.de Airport Evolution and Capacity Forecasting Branko Bubalo GAP/B Research Project branko.bubalo@googlemail.com partner/sponsor: 8 th GARS Aviation
More informationPerformance monitoring report for first half of 2015
Performance monitoring report for first half of 2015 Gatwick Airport Limited 1. Introduction Date of issue: 11 November 2015 This report provides an update on performance at Gatwick in the first half of
More informationAviation Trends Quarter
Aviation Trends Quarter 4 214 Contents Introduction... 2 1. Historical overview of traffic see note 5 on p.15... 3 a. Terminal passengers... 4 b. Commercial flights... 5 c. Cargo tonnage... 6 2. Terminal
More informationNAS/ATM Performance Indexes
FAA-NEXTO NAS/ATM Performance Indexes Dr. Alexander (Sasha) Klein CENTE FO AI Acknowledgments This research was funded by the FAA-NEXTO-GMU contract #DTFAWA-4-D-13 Many thanks to our FAA sponsors: Steve
More informationPresented at the 3rd INFORM Airline Forum, Lisbon, May 2015.
WestminsterResearch http://www.westminster.ac.uk/westminsterresearch New insights into delay propagation? Cook, A.J. Presented at the, Lisbon, 20-22 May 2015. The WestminsterResearch online digital archive
More informationINCENTIVE PROGRAM
LIMAK KOSOVO INTERNATIONAL AIPORT PRISHTINA INTERNATIONAL AIRPORT ADEM JASHARI INCENTIVE PROGRAM 2016-2018 (27 Mar 2016 24 Mar 2018) 100% DISCOUNT ON LANDING FEE FREE AIRCRAFT PARKING PROGRESIVE FINANCIAL
More informationSchedule Compression by Fair Allocation Methods
Schedule Compression by Fair Allocation Methods by Michael Ball Andrew Churchill David Lovell University of Maryland and NEXTOR, the National Center of Excellence for Aviation Operations Research November
More informationEvidence for the Safety- Capacity Trade-Off in the Air Transportation System
Evidence for the Safety- Capacity Trade-Off in the Air Transportation System G. L. Donohue R. C. Haynie D. Wang J. F. Shortle Dept. of Systems Engineering & Operations Research George Mason University
More information12 th Facilitation Division
12 th Facilitation Division The Impact of the A380 Georgina Graham Manager Passenger Facilitation Introduction Significant change will be required to many aspects of existing airport infrastructure and
More informationLONG BEACH, CALIFORNIA
LONG BEACH, CALIFORNIA 1 LONG BEACH, CALIFORNIA Airside Capacity Evaluation Techniques Matt Davis Assistant Director of Planning Hartsfield-Jackson Atlanta International Airport Matt.Davis@Atlanta-Airport.com
More informationBusiness Intelligence Development at Winnipeg Transit
ITS Canada Webinar February 28, 2013 Business Intelligence Development at Winnipeg Transit Bill Menzies Senior Transit Planner, Dillon Consulting Limited Manager of Service Development, Winnipeg Transit
More informationLCCs: in it for the long-haul?
October 217 ANALYSIS LCCs: in it for the long-haul? Exploring the current state of long-haul low-cost (LHLC) using schedules, fleet and flight status data Data is powerful on its own, but even more powerful
More informationINTERRUPTED TRAVEL ASSISTANCE
INTERRUPTED TRAVEL ASSISTANCE united states TO YOU, OUR VALUED CUSTOMER Bringing the World to Africa. Taking Africa to the World. OUR SERVICE MISSION is to provide uncompromising service offerings to our
More informationAPPENDIX D MSP Airfield Simulation Analysis
APPENDIX D MSP Airfield Simulation Analysis This page is left intentionally blank. MSP Airfield Simulation Analysis Technical Report Prepared by: HNTB November 2011 2020 Improvements Environmental Assessment/
More informationAirfield Capacity Prof. Amedeo Odoni
Airfield Capacity Prof. Amedeo Odoni Istanbul Technical University Air Transportation Management M.Sc. Program Air Transportation Systems and Infrastructure Module 10 May 27, 2015 Airfield Capacity Objective:
More informationFuel Cost, Delay and Throughput Tradeoffs in Runway Scheduling
Fuel Cost, Delay and Throughput Tradeoffs in Runway Scheduling Hanbong Lee and Hamsa Balakrishnan Abstract A dynamic programming algorithm for determining the minimum cost arrival schedule at an airport,
More informationCANSO Workshop on Operational Performance. LATCAR, 2016 John Gulding Manager, ATO Performance Analysis Federal Aviation Administration
CANSO Workshop on Operational Performance LATCAR, 2016 John Gulding Manager, ATO Performance Analysis Federal Aviation Administration Workshop Contents CANSO Guidance on Key Performance Indicators Software
More informationThe Evolution of the Low Cost Carrier Business Model Connections, Hubbing and Interlining
The Evolution of the Low Cost Carrier Business Model Connections, Hubbing and Interlining Airneth 5 th Annual Conference Den Haag, 14 th April 2011 Wolfgang Grimme German Aerospace Center (DLR) Institute
More information1) Complete the Queuing Diagram by filling in the sequence of departing flights. The grey cells represent the departure slot (10 pts)
FLIGHT DELAYS/DETERMINISTIC QUEUEING MODELS Three airlines (A, B, C) have scheduled flights (1 n) for the morning peak hour departure bank as described in the chart below. There is a single runway that
More informationTravelWise Travel wisely. Travel safely.
TravelWise Travel wisely. Travel safely. The (CATSR), at George Mason University (GMU), conducts analysis of the performance of the air transportation system for the DOT, FAA, NASA, airlines, and aviation
More informationThe Catch 22 of Cost Based OCC Decisions
AIRLINE FORUM 2015 Airline Operations Control The Catch 22 of Cost Based OCC Decisions The Catch 22 Costs are not the issue Airlines burn money every day Outdated IT Systems Cost based decision making
More informationAppendix B Ultimate Airport Capacity and Delay Simulation Modeling Analysis
Appendix B ULTIMATE AIRPORT CAPACITY & DELAY SIMULATION MODELING ANALYSIS B TABLE OF CONTENTS EXHIBITS TABLES B.1 Introduction... 1 B.2 Simulation Modeling Assumption and Methodology... 4 B.2.1 Runway
More information