ALBERT

Description: During the past decade, the National Aeronautics and Space Administration (NASA) has been developing and evaluating a suite of decision support tools (DSTs) to aid the air traffic controller in the management of traffic. These tools are known collectively as the Center/TRACON Automation System (CTAS). The primary focus of CTAS is increased capacity. As part of a new NASA program called Quiet Aircraft Technology (QAT), the following question is being addressed: Can CTAS technology also support the noise mitigation requirements imposed by the community? Controllers currently support a variety of low noise procedures in low traffic densities but, as traffic increases, these must be abandoned due to excessive spacing requirements for vectoring or inter-arrival spacing requirements needed to handle a spectrum of low noise procedures. NASA is currently investigating how to provide controllers with noise-mitigation-based advisories which address these issues without negatively impacting capacity. These issues are of global concern which must be addressed as the demand for air travel continues to increase.

Description: One of the goals of NextGen is to enable frequent use of Optimized Profile Descents (OPD) for aircraft, even during periods of peak traffic demand. NASA is currently testing three new technologies that enable air traffic controllers to use speed adjustments to space aircraft during arrival and approach operations. This will allow an aircraft to remain close to their OPD. During the integration of these technologies, it was discovered that, due to a lack of accurate trajectory information for the leading aircraft, Interval Management aircraft were exhibiting poor behavior. NASA's Interval Management algorithm was modified to address the impact of inaccurate trajectory information and a series of studies were performed to assess the impact of this modification. These studies show that the modification provided some improvement when the Interval Management system lacked accurate trajectory information for the leading aircraft.

Description: NASA's Airspace Technology Demonstration-2 (ATD-2) integrates arrival, departure, and surface operations to extend integrated traffic sequencing all the way from the gate to the overhead stream and back again for multi-airport, metroplex environments. A key concept of ATD-2 centers on surface scheduling that allows aircraft to taxi, climb, and insert within the overhead stream with minimal interruptions. A core principle is to allow aircraft to absorb delay at the gate prior to engine start in order to reduce overall fuel burn and emissions. To achieve these goals, it is necessary for the scheduler to properly balance the demand at the runway with the available capacity while also predicting accurate takeoff times. This paper provides a data-driven analysis of the runway demand capacity balancing and measures the accuracy of schedules that are generated while running in a live operational environment at the Charlotte Douglas International Airport. We found that using minimum-time wake vortex separation constraints to define runway capacity resulted in scheduling departure operations at a slightly higher rate than the runway was operating and we discovered a surprising relationship between the runway rate and the accuracy of the schedules.

Description: NASA's Airspace Technology Demonstration-2 (ATD-2) integrates arrival, departure, and surface operations to extend integrated traffic sequencing all the way from the gate to the overhead stream and back again for multi-airport, metroplex environments. A key concept of ATD-2 centers on surface scheduling that allows aircraft to taxi, climb, and insert within the overhead stream with minimal interruptions. A core principle is to allow aircraft to absorb delay at the gate prior to engine start in order to reduce overall fuel burn and emissions. To achieve these goals, it is necessary for the scheduler to properly balance the demand at the runway with the available capacity while also predicting accurate takeoff times. This paper provides a data-driven analysis of the runway demand capacity balancing and measures the accuracy of schedules that are generated while running in a live operational environment at the Charlotte Douglas International Airport. We found that using minimum-time wake vortex separation constraints to define runway capacity resulted in scheduling departure operations at a slightly higher rate than the runway was operating and we discovered a surprising relationship between the runway rate and the accuracy of the schedules.

Description: Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Description: NASA has initiated a new five year program this year, the Quiet Aircraft Technology (QAT) Program, a program which will investigate airframe and engine system noise reduction. QAT will also address community noise impact. As part of this community noise impact component, NASA will investigate air traffic management (ATM) challenges in reducing noise. In particular, controller advisory automation aids will be developed to aid the air traffic controller in addressing noise concerns as he/she manages traffic in busy terminal areas. NASA has developed controller automation tools to address capacity concerns and the QAT strategy for ATM Low Noise Operations is to build upon this tool set to create added advisories for noise mitigation. The tools developed for capacity will be briefly reviewed, followed by the QAT plans to address ATM noise concerns. A major NASA goal in global civil aviation is to triple the aviation system throughput in all-weather conditions while maintaining safety. A centerpiece of this activity is the Center/TRACON Automation System (CTAS), an evolving suite of air traffic controller decision support tools (DSTs) to enhance capacity of arrivals and departures in both the enroute center and the TRACON. Two of these DSTs, the Traffic Management Advisor (TMA) and the passive Final approach Spacing Tool (pFAST), are in daily use at the Fort Worth Center and the Dallas/Fort Worth (DFW) TRACON, respectively, where capacity gains of 5-13% have been reported in recent NASA evaluations. Under the Federal Aviation Administration's (FAA) Free Flight Phase One Program, TMA and pFAST are each being implemented at six to eight additional sites. In addition, other DSTs are being developed by NASA under the umbrella of CTAS. This means that new software will be built upon CTAS, and the paradigm of real-time simulation evaluation followed by field site development and evaluation will be the pathway for the new tools. Additional information is included in the original extended abstract.

Description: Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.