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Spot and Runway Departure Advisor

Operational Challenges

Under current airport surface operations, the management of surface traffic is distributed amongst many different operators, who frequently lack a common set of information about airport conditions, and who often operate independently and reactively to the traffic conditions. Airport ramps (also called aprons or non-movement areas) are the areas outside taxiways and runways used for airplane parking, loading/unloading, refueling, and maintenance. Most large airports in the US have ramp towers operated by airlines, airports, third-party companies, or the local municipalities. Controllers in the ramp towers ensure safety and efficiency in ramp areas and oversee aircraft traffic as well as other servicing activities. The ramp controllers direct departures on a first-come-first-served basis.

The Federal Aviation Administration (FAA) manages the Air Traffic Control Tower (ATCT). Ground and Local controllers manage traffic on the taxiways and runways respectively, providing taxiway and runway clearances using a first-come-first-served policy, based on the order that aircraft arrive at the spots (the boundary between the ramp and the taxiways) and the runways.

There are two main sources of inefficiencies on the surface. One is peak traffic due to multiple aircraft with similar departure times. These aircraft call for pushback from their gates at around the same time and compete for limited resources (the taxiways and runways). This leads to many aircraft taxiing to the runway simultaneously, causing long runway queues and congestion on taxiways. Stop-and-go taxi operations resulting from surface congestion can potentially delay actual takeoff times and limit airport throughput.

The second source of surface inefficiencies results when relevant planning information is not shared between various airport surface stakeholders such as the ramp and ATCT controllers. Thus, decisions made by each entity may not be the most efficient and sometimes may even be counterproductive to overall operations.

This image shows a cartoon of an airport's surface. In the top left there is an airport ramp tower adjacent to a row of gates. At one of the gates, there is an aircraft icon. There is another set of tower, gates and airplane to the right of the first set. In between the two sets is a block that says Gate Pushback Schedule and a lightning bolt representing data exchange. Below the towers and gates are taxiways and runways. There are two airplanes at the spots just at the entrances to the taxiway. These are labeled Spot Release Schedule. There is an aircraft taking off, an aircraft crossing runways, and three aicraft queueing up for takeoff. These are labeled Optimal Runway Schedule. In the bottom right corner is a local tower. There is a lightning bolt between the local tower and a cloud labeled Data Exchange and another bolt between the cloud and the second airport ramp tower.
SARDA creates metering advisories for runway usage, spot release into taxiways, and gate pushbacks. (Click image to enlarge.)

NASA's Solution

The Spot and Runway Departure Advisor, or SARDA, is NASA's contribution to improving the efficiency of airport surface operations. It is the centerpiece of a partnership among airlines, airports, and air traffic controllers to improve operations at the nation’s busiest airports.

SARDA uses time-based metering of aircraft to reduce the congestion on the airport surface and both assumes and facilitates a collaboration amongst the various airport surface stakeholders for obtaining better situational awareness of flight operations information. Then, for each aircraft, SARDA provides metering advisories at three main locations: gate, spot, and runway. By controlling the release of aircraft from the gates and the spots, SARDA effectively shifts the delays from the taxiways and runways to the gates. By incurring delays at the gates, with aircraft engines off, fuel and emissions are reduced. Metering of aircraft at the gates also reduces the number of aircraft on the movement area at any time, increasing predictability.

The main algorithm for SARDA operates in two-stages to generate metering advisories. The first stage provides an optimal sequence and times for runway usage (takeoff times for departures and runway crossing times for arrivals). The generated runway schedule complies with various constraints, such as wake vortex separation and Traffic Management Initiatives. The second stage determines times to release aircraft from gates or spots. Dynamic surface conditions are detected and mitigated by executing the algorithm periodically to generate updated optimized solutions.

The SARDA concept has been evaluated in human-in-the-loop (HITL) simulations at NASA Ames Research Center’s Future Flight Central (FFC) facility. The FFC facility provides a 360-degree, full-scale, computer-generated out-the-window view of an airport. Aircraft traffic was simulated on the surface or in the airspace near the airport and displayed on radar maps. Metering advisories from the optimization algorithm were either shown to ATCT controllers through an Electronic Flight Strip (EFS) display system or to ramp controllers through NASA's Ramp Traffic Console (RTC).

Photo of an air traffic controller seated an an out-the-window display and SARDA ramp traffic console inside of FutureFlight Central.
A controller uses the SARDA Ramp Traffic Console (closeup below) during a simulation of Charlotte/Douglas International Airport operations.

A closeup screenshot of the SARDA Ramp Traffic Console.
The SARDA Ramp Traffic Console shows SARDA advisories for departures at gates. (Click image to enlarge.)

Three sets of HITL simulations have been successfully conducted, modeling SARDA in operation at Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and at Charlotte/Douglas International Airport (CLT) in 2014. In the 2012 simulation of surface operations on the east side of DFW, researchers observed SARDA could achieve reductions of up to 60% in taxi delays and estimated 33% in fuel and emissions. In the CLT simulations, SARDA advisories were found to reduce the departure taxi delay by one minute per flight and the fuel consumption of departing flights by 10-12%. Wait times in the departure runway queue were also found to be reduced, which suggests SARDA improved takeoff time conformance and lowered tower controller workload.

Looking ahead, plans are underway to conduct a joint field test with American Airlines in 2016. Prototype SARDA ramp decision support automation will be tested with operations at CLT.

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Fuel Consumption and Emissions from Airport Taxi Operations
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NASA researchers discuss SARDA field testing with American Airlines Charlotte Airport Ramp Managers
May 1, 2015
NASA researchers visited the American Airlines Ramp Tower at Charlotte Douglas International Airport (North Carolina) April 14-15, 2015.
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Spot and Runway Departure Advisor (SARDA) Operational Field Test Planning Meeting
January 30, 2015
Division managers and researchers supporting NASA's airport surface research effort, as well as planning team members from the Airspace Technology Demonstration-2 (ATD-2) planning team met in Fort Worth, TX, January 20-21, 2015 with American Airlines (AA) staff.
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Completion of SARDA Human-in-the-Loop Simulation Data Collection
November 14, 2014
The Spot and Runway Departure Advisor (SARDA) airport surface research team performed three-weeks of data collection September 29 to October 24 in NASA Ames Research Center's FutureFlight Central (FFC) facility.
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"Predictability in Airport Surface Operation Management,"
Liu, Y., Hansen, M., Wang, Z., Gupta, G., and Malik, W., 2013 AIAA Aviation Technology, Integration, and Operations Conference, Los Angeles, CA, 12-14 Aug. 2013.
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"Performance Evaluation of Individual Aircraft Based Advisory Concept for Surface Management,"
Gupta, G., Malik, W., Tobias, L., Jung, Y., Hoang, T., and Hayashi, M., 10th USA/Europe ATM R&D Seminar (ATM2013), Chicago, Illinois, 10-13 June 2013.
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"Usability Evaluation of the Spot and Runway Departure Advisor (SARDA) Concept in a Dallas/Fort Worth Airport Tower Simulation,"
Hayashi, M., Hoang, T., Jung, Y., Gupta, G., Malik, W., Dulchinos, V., 10th USA/Europe ATM R&D Seminar (ATM2013), Chicago, Illinois, 10-13 June 2013.
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"Towards a Fast-time Simulation Analysis of Benefits of the Spot and Runway Departure Advisor,"
Windhorst, R.D., AIAA-2012-4975, AIAA Guidance, Navigation, and Control (GNC) Conference, Minneapolis, MN, 13-16 Aug. 2012.
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“Detailed Estimation of Fuel Consumption and Emissions During Aircraft Taxi Operations at Dallas/Fort Worth International Airport,”
Nikoleris, T., Gupta, G., and Kistler, M., Journal Transportation Research Part D: Transport and Environment, Vol. 16D, Issue 4, June 2011.
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"Tower Controllers' Assessment of the Spot and Runway Departure Advisor (SARDA) Concept,"
Hoang, T., Jung, Y., Holbrook, J., and Malik, W., 9th USA/Europe ATM R&D Seminar (ATM2011), Berlin, Germany, 14-17 June 2011.
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"Performance Evaluation of a Surface Traffic Management Tool for Dallas/Fort Worth International Airport,"
Jung, Y., Hoang, T., Montoya, J., Gupta, G., Malik, W., Tobias, L., and Wang, H., 9th USA/Europe ATM R&D Seminar (ATM2011), Berlin, Germany, 14-17 June 2011.
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"A Concept and Implementation of Optimized Operations of Airport Surface Traffic,"
Jung, Y. C., Hoang, T., Montoya, J., Gupta, G., Malik, W., and Tobias, L., 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, Fort Worth, TX, 13-15 Sep. 2010.
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"Incorporating Active Runway Crossings in Airport Departure Scheduling,"
Gupta, G., Malik, W., and Jung, Y. C., American Institute of Aeronautics and Astronautics (AIAA) Guidance, Navigation, and Control (GNC) Conference and Modeling and Simulation Technologies (MST) Conference, Toronto, Canada, 2-5 Aug. 2010.
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"Managing Departure Aircraft Release for Efficient Airport Surface Operations,"
Malik, W., Gupta, G., and Jung, Y.C., American Institute of Aeronautics and Astronautics (AIAA) Guidance, Navigation, and Control (GNC) Conference and Modeling and Simulation Technologies (MST) Conference, Toronto, Canada, 2-5 Aug. 2010.
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"A Mixed Integer Linear Program for Airport Departure Scheduling,"
Gupta, G., Malik, W., and Jung, Y. C., AIAA-2009-6933. AIAA Aviation, Technology, Integration, and Operations (ATIO) Conference and Aircraft Noise and Emissions Reduction Symposium (ANERS), Hilton Head, SC, Sep. 21-23, 2009.
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"A Generalized Dynamic Programming Approach for a Departure Scheduling Problem,"
Rathinam, S., Wood, Z., Sridhar, B., and Jung, Y., AIAA-2009-6250, AIAA Guidance, Navigation, and Control Conference, Chicago, IL, 10-13 Aug. 2009.
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"An Optimization Model for Reducing Aircraft Taxi Times at the Dallas Fort Worth International Airport,"
Rathinam, S., Montoya, J., and Jung, Y., 26th International Congress of the Aeronautical Sciences (ICAS) 2008, Anchorage, AK, 14-19 Sep. 2008.
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Best Paper in Track at the 2011 USA/Europe ATM R&D Seminar
NASA Ames researchers earned the best paper in the “Airport” track for their paper describing the development and testing of airport surface scheduling algorithms.
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NASA Fact Sheet
Download the NASA Fact Sheet on SARDA.
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Last Updated: September 28, 2015

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