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Capacity Impacts of NextGen era Enhanced Wake Vortex Mitigation Processes

Wake VortexA 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.

This research project is sponsored by the FAA.

PI: R. John Hansman

Airport surface operations management from a network congestion control perspective

Airport surpface operationsWe 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


Airline Revenue Management Research – PODS Consortium

PODS ConsortiumThe 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 airline members that in 2012 include Air Canada, Air New Zealand, Delta, KLM/Air France, Lufthansa/Swiss, SAS 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:

  • Optimization of alliance network revenues through coordination of partner seat inventory controls
  • Demand forecasting and optimization for “fare family” fare structures being introduced by airlines
  • Estimation of passenger willingness to pay and unconstraining of historical booking data for RM forecasting
  • Joint optimization of multiple aircraft cabins to account for passenger choice and use of shared seat inventories

PI: Peter Belobaba

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

Illustration of Potential Trade-offs between Different Objectives 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.

This research project is sponsored by NASA.

PI: R. John Hansman

Estimation of Aircraft Surface Fuel Burn

Estimation of Surface Fuel BurnWe 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

Distribution of Passenger Delays by CausesFlight 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

Fuel Burn Reduction Potential from Delayed Deceleration Approaches

Fuel Burn graphVarious 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.

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

An Overview of Our Research PlanWhile 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

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

Track geometry of US mid-air over the last 10 yearsDue 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

Simulation Results on Passenger Delays with and without the Tarmac Delay RuleThe 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

Methods for Evaluating Environmental and Performance Tradeoffs for Air Transportation Systems

NextGen ComponentsMIT 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

Slack re-allocation examplesWe 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


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