Airline Industry Consortium

The MIT Airline Industry Consortium engages industry stakeholders in forward-looking aviation research and provides a forum for addressing key issues facing the airline industry. Consortium membership includes airlines, aircraft manufacturers, aviation consultants, information technology suppliers, airports and infrastructure providers, labor groups and government agencies. Consortium members are invited to participate in several events each year, including an annual review of our research activities as well as Executive Education Programs that focus on key industry issues. 

Research funded by the Consortium addresses aspects of the economics, management and operations of airlines and the air transportation system.  Recent research themes have included:

• Economics, Productivity and Competition
• Labor and Human Resource Issues
• Operations Management and Network Considerations
• Safety and Security
• Infrastructure Capacity and Costs

PI: Peter Belobaba

Development of Super-Short Takeoff and Landing Aircraft

The Super-STOL project examines the application of distributed electric propulsion technology to fixed wing aircraft with the goal of enabling short field performance that it is competitive with vertical takeoff and landing (VTOL) concepts in terms of the required ground infrastructure. This notionally translates into ground rolls of 100ft or less for a GA-size aircraft. This short field performance is achieved using blown lift, which is a high lift system where the wake from propellers lining the leading edge of the wing is deflected by trailing edge flaps, increasing the lifting capability of the wing. SSTOL aircraft would be useful for highly infrastructure-constrained urban air mobility missions, which focus on moving passengers and cargo in and around large urban areas and the surrounding regions. Compared to the VTOL vehicles being widely proposed for these missions, SSTOL vehicles may be easier to certify and have improved payload and/or range capability. Current areas of ongoing research are studying the conceptual benefits of the SSTOL vehicles, wind tunnel testing of various blown wing designs, and flight testing of a 13 ft span vehicle.

Sponsor: This project is sponsored by Aurora Flight Sciences: A Boeing Company.

PI: R. John Hansman
Researchers: Chris Courtin, Trevor Long

Airline Revenue Management Research – PODS Consortium

The Passenger Origin-Destination Simulator (PODS), first developed by Boeing in the early 1990s, has since been modified and expanded by MIT to realistically simulate the passenger booking and choice process in competitive airline markets. PODS simulates the decisions of individual business and leisure passengers in terms of their choice of airline flight and fare options, given two or more competitors offering different route networks, aircraft capacities, departure schedules, and multiple fare levels (each with associated restrictions) in hypothetical network environments.

The PODS Consortium at MIT is funded by 14 industry members that in 2020 include Air Canada, Alaska, Amadeus, ATPCO, Boeing, Delta, Etihad, IAG, LATAM, Lufthansa Group, PROS, Qatar, Sabre and United. With guidance from the members, PODS is used by MIT graduate students to test the revenue impacts of existing and new models for demand forecasting and seat availability optimization in airline revenue management systems. Examples of recent and current PODS research projects and Master’s thesis topics include:

• Exploration of the potential for dynamic and/or customized availability and fare quotes under the New Distribution Capability (NDC) industry standard
• Forecasting and optimization in a class-free RM environment and its competitive impacts
• Estimation of passenger willingness-to-pay based on booking data
• Optimization models that incorporate ancillary revenues into airline RM systems
• Joint pricing and optimization of bundled flight and ancillary services through Dynamic Offer Generation (DOG)

PI: Peter Belobaba
Researchers: Yuxuan Lu, Alexander Papen, Bazyli Szymanski, Kevin Wang

A Commercial Space Operator Cost Model and Analysis of Launch Delay Costs

There is currently a need for the FAA to develop a better understanding of the operational strategies and cost structures for commercial space operators in the U.S. National Airspace System (NAS). Commercial space launches in the U.S. are expected to more than double in the coming decade, requiring the FAA to make an increasing number of decisions each year on how to best share the NAS between air traffic and commercial space operators. The goal when making these decisions is to find an equitable balance between air traffic and commercial launch operations, and to then implement actions that are Pareto improvements, that is, when one NAS operator becomes better off without the other operator becoming worse off. Ultimately, finding this equitable balance and, therein implementing Pareto operational strategies, depends on cost and financial information for both commercial airlines and commercial space companies. Such information is available for commercial airlines; however, no cost and financial data exists for commercial space companies. The corresponding objective of this project is to develop a cost model that will quantify commercial space costs, specifically, the cost of commercial launch vehicles, their payloads, their operations, and their reentry and recovery operations. In addition, the model estimates the cost of launch delays to commercial launch vehicle providers.

Sponsor: This research project is sponsored by the FAA.

PI: R. John Hansman
Researcher: Greg O’Neill

Evaluating the Applicability of the ACAS-X Airborne Collision Avoidance System for Small Unmanned Aircraft Systems (sUAS)

Small unmanned aircraft systems (sUAS) are an emerging technology with a variety of potential civil and commercial applications. However, as sUAS take to the skies, care must be taken to mitigate the potential of midair collision in increasingly crowded airspace. Power and weight limitations preclude many sUAS from equipping the transponders required on larger aircraft. This prevents sUAS from utilizing current collision avoidance systems such as TCAS. Airborne Collision Avoidance System (ACAS) X, currently in development at Lincoln Laboratory, offers a possible solution to this problem. Unlike TCAS, ACAS X does not require a transponder and could use surveillance data shared over ADS-B or through the cellular network. Adjusting and optimizing ACAS X to the operational and performance constraints of sUAS could allow for the safe integration of sUAS into the national airspace system (NAS).

Sponsor: This research project is sponsored by MIT Lincoln Laboratory.

PI: R. John Hansman
Researcher: John L. Deaton, 2d Lt, USAF

Cruise Altitude and Speed Optimization Decision Support Tool

Changing weather, turbulence encountered en route, and air traffic constraints, among other factors, can result in airliners flying at suboptimal altitudes, creating significant fuel burn inefficiencies. However, current aircraft crews, working with flight plans and weather information that may be several hours old, have limited information to support replanning a flight en route when those situations are encountered. As a result, a decision support tool for cruise altitude and speed optimization is being developed for use in the cockpit, integrating an optimization framework, the most recent weather forecasts, and a graphical visualization interface to assist pilots in making strategic altitude and speed decisions in real time. The decision support tool is able to provide an optimized flight plan, as well as capabilities for rapidly assessing the impact of various flight plan options on fuel, time, and expected ride quality across the length of the flight.

Sponsor: This research project is sponsored by the FAA.

PI: R. John Hansman
Researcher: Clement Li

Analysis of Urban Air Mobility Operational Constraints

Urban air mobility (UAM) refers to a set of proposed operations and technologies that aim to provide on-demand air transportation services within a metropolitan area. This project investigates potential operational constraints that could arise during the implementation, operation, or scale-up of a UAM system. Exploratory case studies in Los Angeles, Boston, and Dallas identified a set seven UAM operational constraints. The top three prioritized constraints concern aircraft noise, takeoff and landing area availability, and air traffic control scalability. These constraints directly aligned with previous literature from helicopter passenger networks and indicate new electric aircraft, automation, and telecommunications technologies may not directly address the significant operation constraints of UAM networks. Continued efforts are therefore investigating approaches to mitigate the impacts of these three constraints, particularity through a new concept of operations for low altitude air traffic control. The results of this project support NASA and FAA decision makers and may inform requirement definition for UAM aircraft and networks.

Sponsor: This research project is sponsored by NASA.

PI: R. John Hansman
Researcher: Parker Vascik

Capacity Impacts of NextGen era Enhanced Wake Vortex Mitigation Processes

A key limitation for airport capacity improvements is wake turbulence in the terminal area. The project studies airport capacity and delay impacts of the new NextGen procedures considering wake vortex interactions. This study looks at arrival and departure scenarios to minimize wake encounter risk and to enhance airport throughput. Separation standards between aircraft are investigated to identify potential runway capacity benefits of wake vortex mitigation processes and procedures. Fast-time computer simulation models for several terminal areas in the National Airspace System will be studied to examine the impacts of the new NextGen environment. The results of this project will provide FAA decision makers with realistic capacity impacts of various NextGen procedures.

Sponsor: This research project is sponsored by the FAA.

PI: R. John Hansman

Small Community Air Service White Paper Series

There are over 500 commercial service airports in the United States, and a majority of these airports serve fewer than 100,000 passengers per year. For many small communities, these local airports provide vital connections to social and economic opportunities throughout the country and around the globe. The MIT Small Community Air Service White Paper Series focuses on providing quantitative analysis of trends and forces shaping small community air service, including connectivity, fares, airport accessibility, and the looming pilot shortage in the regional airline industry. The results of MIT ICAT studies on small community air service have been featured in major media outlets and cited multiple times by the Government Accountability Office and the U.S. Congress.

Representative studies:

Wittman, M.D and W.S. Swelbar. 2013. Trends and Market Forces Shaping Small Community Air Service in the United States. MIT Small Community White Paper No. 1. Report No. ICAT-2013-02.

Wittman, M.D. 2014. Public Funding of Airport Incentives in the United States: The Efficacy of the Small Community Air Service Development Program. Transport Policy 35: 220-228.

PI: Peter Belobaba

Modeling to Support the Cost Benefit Analysis of an Aircraft CO2 Standard

Sponsor: This research project is sponsored by the DOT/FAA.

PI: R. John Hansman

Air Transport Connectivity

Commercial air service helps link airports of all sizes with the global air transportation network. This research focuses on quantifying the market access provided by commercial air transport through innovative connectivity metrics that consider not only the frequency of nonstop and connecting service, but also the economic strength of the destinations served. The results provide new perspectives on how recent airline industry trends have affected airports large and small, as well as the economic benefits these airports provide to the residents, businesses, and communities they serve.

Representative studies:

Allroggen, F., M.D. Wittman, and R. Malina. 2015. How Air Transport Connects the World - A New Metric of Air Connectivity and Its Evolution between 1990 and 2012. Transportation Research Part E 80: 184-201.

Wittman, M.D. and W.S. Swelbar. 2013. Capacity Discipline and the Consolidation of Airport Connectivity in the United States. Transportation Research Record  2449: 72-78.

PI: Peter Belobaba

North Atlantic Space Based ADS-B Predictability and Flexibility Benefits

The North Atlantic region is one of the busiest oceanic traffic regions in the world. Current operational procedures, however, limit the amount of flexibility and predictability that is available to flights operating in this region. Space based ADS-B and increased surveillance can allow for changes in the current operational procedures, allowing for increased flexibility and predictability. This project studies the effects of increased flexibility and predictability in the North Atlantic region. This project aims to develop a benefit case for improved surveillance over this region. Current analyses reveal that increased flexibility and predictability can allow for more fuel-efficient aircraft trajectories, creating a benefit pool in terms of reduced fuel usage, and increased capacity through the North Atlantic.

Sponsor: This research project is sponsored by the FAA.

PI: R. John Hansman

Airline Data Project

Updated yearly since 2008, MIT's Airline Data Project (ADP) remains the most comprehensive free source of data and analysis regarding the U.S. airline industry. The ADP collects and processes U.S. Department of Transportation Form 41 data to provide a 20-year history of key operating metrics such as cost per available seat mile (CASM), passenger yield, load factors, and airline profitability. The Airline Data Project is a unique repository of data and analysis that has allowed for those interested in aviation--from students and researchers of air transportation to the news media to the financial community--to monitor the evolution of the U.S. commercial airline industry.

http://airlinedataproject.mit.edu

PI: Peter Belobaba

Airport surface operations management from a network congestion control perspective

We have modeled the airport surface as a network, with taxiways as links and their major intersections as nodes. The time required to travel over each link is random, and follows a set of stochastic processes. Our objective is to define a control strategy for this network, with the objective of minimizing aircraft surface fuel burn and emissions, as well as reducing takeoff delays. The approach that we have proposed has the advantage of explicitly accounting for uncertainty in surface operations, while still aiming to realize a large proportion of the potential benefits from congestion mitigation.

PI: Hamsa Balkrishnan

Big Aviation Data Mining for Robust, Ultra-Efficient Air Transportation

The growing availability of massive aviation data creates an opportunity for developing analytical tools that can be useful for post-event efficiency assessment, monitoring and alerting and real time decision support in the air traffic management system. Data types in the US National Air Transportation System (NAS) include planned and actual demand (e.g., airline schedules, wheels off times), air traffic control facility state (e.g., weather information, airport arrival rates) and planned and actual aircraft operations (e.g., flight plans, surveillance tracks). Many of the existing data sets are large volume (e.g., over 200 GB of weather data and 1.2 GB of flight track/plan data per day), large velocity (streaming continually) and large variety (different formats, data types, etc.). These characteristics make rapidly-evolving “Big Data” techniques particularly attractive to handle and convert the system raw data into useful information for system improvement.

The goal of this research project is to develop and demonstrate an interpretable, scalable and generalizable “Big Data” analytic framework for identifying patterns of air transport system behavior at various spatial and temporal scales. As an example, current research efforts include the characterization of NAS-wide network delay propagation dynamics at the strategic level and the characterization of air traffic flows in the transition/terminal airspace at the tactical level using data mining algorithms. The outcomes of the framework can be used to assess operational performance, identify and mitigate inefficiencies, identify operational best practices and generate inputs for descriptive and predictive models.

PI: R. John Hansman

Multi-Agent Modeling for Design and Evaluation of Airline Voting Mechanisms for Determination of Air Traffic Flow Management (ATFM) Initiatives

Parameter selection for the Air Traffic Flow Management (ATFM) initiatives is performed by the regulatory authorities such as the Federal Aviation Administration (FAA), after accounting for airline preferences. We design voting schemes that can replace the existing ad-hoc methods. Strategic behavior by each airline is modeled using an integer programming (IP) formulation which explicitly accounts for the tie-breaking rules. We solve for a Nash equilibrium outcome using best response heuristics. Using actual data on airline operations in the United States, we evaluate the equilibrium properties of these games, including existence, uniqueness, convergence, system optimality and pareto optimality and recommend mechanisms with most desirable properties.

Sponsor: Federal Aviation Administration (FAA)

PI: Cynthis Barnhart

Methods for Evaluating Environmental-Performance Tradeoffs for Air Transportation Systems

There is an increasing emphasis on considering environmental objectives along with traditional objectives such as performance and cost for the design and operation of air transportation systems.  Consequently, selecting the “best” or “optimal” design and operation of a system has become more challenging due to the need to resolve multiple, competing environmental-performance tradeoffs.  In order to facilitate the development of methods to analyze air transportation system tradeoffs, a framework was developed in this research.  The framework was applied to two test cases.  The first case analyzes environmental-performance tradeoffs for aircraft cruise operations.  And the second case analyzes the tradeoffs associated with using Required Area Navigation and Performance (RNAV/RNP) for approach procedures.  In the analyses corresponding to these two cases, several important aspects of analyzing competing tradeoffs are considered.  These include valuation theory, for quantifying a stakeholder’s relative preference amongst a set of tradeoffs, and hyperspace visualization, for identifying the most dominant tradeoffs.

Sponsor: This research project is sponsored by NASA.

PI: R. John Hansman

Estimation of Aircraft Surface Fuel Burn

We use Flight Data Recorder information from an operational fleet, to model the fuel burn of aircraft on the surface. A set of processes that may govern the total fuel burn were investigated, and the statistically significant ones were included in the model. It was found that the fuel consumption could vary by a substantial amount, based on the velocity profile of the aircraft on the surface. The same techniques can be applied to model aircraft emissions, creating opportunities for further research with a direct impact on air quality and carbon emissions.

PI: Hamsa Balakrishnan

A longitudinal study of historical passenger delay in the United States National Aviation System

Flight delays continue to be a concern within the US National Aviation System despite slowed growth over the past few years due to the economic downturn. The problem is even greater at a number of key airports, such as those in the New York region, which affect passengers flying to all parts of the Nation. To further complicate the question of delay effects, our study has shown that average passenger delay is, on average, nearly twice of average flight delay, accounting for the effects of missed connections and cancellations. Both flight delays and passenger delays are significantly affected by airline scheduling and networks, which have seen changes in recent years due to airline mergers, market growth and changes in banking structures at congested hubs. The impact of these changes have not, however, been quantified and are not currently well understood. MIT has developed the capability to estimate passenger delays in the NAS given historical flight delay data using the MIT passenger delay model. This model incorporates a discrete choice model for estimating historical passenger itinerary travel, and a greedy re-accommodation heuristic for estimating the resulting passenger delays. The next steps in ongoing research is to extend this work to quantify passenger delays for a number of years and to conduct a longitudinal study identifying the impacts of some significant developments in the US airline industry over recent years, including regulatory changes and airline strategic decisions.

Sponsor: Federal Aviation Administration (FAA)/NEXTOR II

PI: Cynthia Barnhart

Modeling of Secondary Benefits of PBN Procedures

RNAV approach procedures with Required Navigation Performance (RNP) have been a recent focus of NextGen efforts to modernize navigation in the NAS. Unlike traditional types of instrument procedures such as ILS, RNP approaches can be flown without the aid of ground beacons such as VOR stations. By instead relying on satellite and inertial navigation systems, RNP approaches can be designed with a higher degree of flexibility and flown more precisely.

With the recent implementation of public RNAV RNP procedures at major airports in the United States, real tracking data can now be obtained for flights that make use of these approaches. In this study, we aim to use this real-world data to evaluate the benefits of RNP approaches. Of special interest in this study are the potential safety benefits of RNP procedures related to approach stability on final approach, which are evaluated using ASDE-X airport surveillance data.

PI: R. John Hansman

Fuel Burn Reduction Potential from Delayed Deceleration Approaches

Various strategies are being pursued to reduce fuel burn and mitigate the environmental impacts from aviation. Among them, operational changes have limited overall mitigation potential, but can also be implemented in much shorter timeframes with existing aircraft types. In particular, one mitigation identified in this way was the wider use of Delayed Deceleration Approaches (DDAs).

Delayed Deceleration Approaches occur when airspeed is maintained above the initial flaps speed for as long as possible during approach. This lowers drag and engine thrust requirements, leading to significant reductions in fuel burn and emissions during the descent and approach phases of flight. However, analysis of operational data suggests many flights decelerate earlier than this ideal approach speed profile suggests. This project investigates potential reasons behind the early decelerations and identifies opportunities for increased Delayed Deceleration Approach use.

Sponsor:  This research project is sponsored by FAA, through the PARTNER Center of Excellence

PI: R. John Hansman

Development of an Integrated Flight and Passenger Delay Model

While the passenger delay model developed by researchers at MIT provides a useful capability for analyzing historical passenger delays, it does not provide a “what-if” capability that would allow analysis of the impact of potential changes within the National Aviation System on flight and passenger delay. In other words, it does not simulate flight delay. However, MIT has also developed the Airport Network Delays (AND) model which is a stochastic and dynamic queuing model that computes flight delays at individual airports in a network, and captures the propagation of flight delays through this network. Integration of the AND model with the MIT passenger delay model would provide such a “what-if” capability. The next steps in this project include combining the AND model and the passenger delays model and then enhancing this combined model by integrating a model of airline recovery process into the overall simulator.

Sponsor: Federal Aviation Administration (FAA)/NEXTOR II

PI: Cynthia Barnhart

Analytical Approach for Quantifying Noise from Advanced Operational Procedures

The objective of the research is to develop an analytical approach for evaluating the noise impacts of advanced operating procedures. Older generations of jet engines produced significantly more noise than current-generation products. The assumption that jet noise dominates aerodynamic sources may have been reasonable in previous environmental impact studies. However, for new advanced approach and departure procedures, aerodynamic noise reduction may contribute strongly to environmental benefits. For example, in a delayed deceleration approach (DDA), deployment of landing gear and high-lift devices can be delayed until later stages in an approach, reducing aerodynamic noise. This effect is not captured using current noise-power-distance (NPD) noise calculation tools now in common use throughout the aerospace industry. This illustrates a gap in noise analysis capability for advanced operational procedures.

Sponsor: This research project is sponsored by the FAA.

PI: R. John Hansman

Preventing Mid-Air Collisions in the General Aviation Community: ADS-B enabled Traffic Situation Awareness

Due to high nuisance alarm rates, current traffic alerting systems have limited usability in the airport environment where a majority of mid-air collisions occur. As part of NextGen, ADS-B will become the primary surveillance source in the National Airspace System. Using the higher quality surveillance information available via ADS-B, the Traffic Situation Awareness Application (TSAA) will be the next generation of traffic alerting for General Aviation. TSAA will provide timely alerts to the flight crew in order to increase their traffic situation awareness.

Under a contract from the FAA, TSAA is being developed at MIT. The development work involves the design and evaluation of a new conflict alerting algorithm, display design evaluation, human factors testing, flight testing as well as the development of the international standards governing the design of future ADS-B based traffic alerting systems by industry.

This research project is sponsored by the FAA

PI: R. John Hansman

Policies and industry trends and their impacts on passenger delay

The aim of this project is to understand and evaluate how policies and trends in the airline industry impact passenger delays in the US National Aviation System. In particular, we are investigating the three-hour tarmac delay rule, which came into effect in April 2010, as an effort to curb lengthy delays during the taxi-out and taxi-in phases. To study this, we are testing a range of assumptions on cancellation decisions by airlines, and passenger re-booking times, and utilizing the Passenger Delay Calculator, also developed at MIT. As of now, we have obtained passenger delay results for several days in 2007 assuming hypothetical scenarios where the tarmac delays rule existed for those days.

Sponsor: Federal Aviation Administration (FAA)/NEXTOR II

PI: Cynthia Barnhart

Innovation in Unmanned Air Vehicle Development

Small, unmanned aerial vehicles (micro-UAVs) are expanding the capabilities of aircraft systems. However, a gap exists in the size and capability of these aircraft: most micro-UAVs are limited to low-speed flight. Many applications require higher flight speeds: joint missions with manned aircraft, reconnaissance in hostile air space, or serving as a target or decoy. This project addresses the need for more agile micro-UAVs. We develop key technologies for small, fast aircraft capable of sustained transonic flight:

• Propulsion - Ultra-slow-burn solid rocket motors for sustained thrust at any flight Mach number
• Thermal management - Temperature-sensitive structures and electronics are only millimeters away from rocket propellant burning at several thousand degrees. We investigate advanced ablative and insulation solutions to this challenging thermal environment.
• Aerodynamics - Computational and experimental techniques for transonic stability and control analysis
• Deployment - Folding wings and control surfaces for compact packaging; launch and stabilization devices

We integrate these technologies in a demonstration vehicle. Called Firefly, this micro-UAV is about the size of a football and launches from a manned fighter aircraft. After launch, Firefly performs a joint mission with the fighter during several minutes of autonomous, transonic flight. Developing technology in the context of a demonstration vehicle enforces realistic mission and integration requirements. These systems considerations are especially important in the tightly integrated, densely packed configuration of a micro-UAV. With the technologies developed in this project, kilogram-scale UAVs will be able to quickly deploy over tens of kilometers, and fly joint missions alongside manned fighter jets.

Sponsor: This research project is sponsored by MIT Lincoln Laboratories and the US Air Force.

PI: R. John Hansman
Researchers: Kelly Mathesius, Jon Spirnak, Tony Tao and Matt Vernacchia

Methods for Evaluating Environmental and Performance Tradeoffs for Air Transportation Systems

MIT is collaborating with U.S. Department of Transportation Volpe Center to investigate human factors issues with advanced instrument procedures.  FAA is transitioning to performance based navigation (PBN) airspace as part of NextGen. Two main components of PBN framework are Area Navigation (RNAV) and Required Navigation Performance (RNP) procedures.

Implementation of RNAV and RNP procedures has raised many human factors issues, as the new procedures are more complex than conventional instrument procedures. MIT is evaluating the depiction of RNAV and RNP procedures for chart elements contributing to high levels of visual clutter and analyzing potential chart de-cluttering techniques. 

This work is sponsored by the U.S. Department of Transportation Volpe Center and FAA Human Factors Research and Engineering Group.

PI: R. John Hansman

Robust Flight Schedules through Slack Re-Allocation

We investigate slack allocation approaches for robust airline schedule planning. Different models and objectives can affect the distribution of slack in the system in different manners. We evaluate the impacts of the resulting schedules on various performance metrics, including passenger delays and delay propagation. Through the empirical results, we examine how an airline's characteristics can affect the strategy for robust scheduling.

Sponsor: Jeppesen

PI: Cynthia Barnhart