NASA SBIR 2015 Solicitation

FORM B - PROPOSAL SUMMARY


PROPOSAL NUMBER: 15-1 A3.02-9593
SUBTOPIC TITLE: Autonomy of the National Airspace System (NAS)
PROPOSAL TITLE: Probabilistic Trajectory Constraint Modeler

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
Mosaic ATM, Inc.
540 Fort Evans Road, Suite 300
Leesburg, VA 20176 - 4098
(800) 405-8576

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
George Hunter
ghunter@mosaicatm.com
540 Fort Evans Road
Leesburg, VA 20176 - 4098
(530) 677-2046

CORPORATE/BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Chris Stevenson
stevenson@mosaicatm.com
540 Fort Evans Road, Suite 300
Leesburg, VA 20176 - 4098
(540) 454-7458

Estimated Technology Readiness Level (TRL) at beginning and end of contract:
Begin: 2
End: 3

Technology Available (TAV) Subtopics
Autonomy of the National Airspace System (NAS) is a Technology Available (TAV) subtopic that includes NASA Intellectual Property (IP). Do you plan to use the NASA IP under the award?
No

TECHNICAL ABSTRACT (Limit 2000 characters, approximately 200 words)
Air traffic control research, air traffic control operations and user operations rely on simulators that predict the future time history of three-dimensional aircraft trajectories. Such predicted trajectories are fundamental inputs to a wide variety of planning, monitoring and control tasks, including airline seasonal fleet planning, pre-departure flight planning, real-time airspace and airport load forecasting, traffic sequencing and spacing, separation assurance, weather routing, runway assignment, etc. Clearly trajectory simulators are core components of many air traffic applications; it is important that they be as accurate, as efficient and as manageable as possible. We propose an innovative trajectory constraint modeling utility that leads to improvements in all three areas. Regarding trajectory simulator accuracy, there are several categories of error sources that contribute to trajectory prediction uncertainty. One key, and overlooked, source is flight plan nonconformance. Flights often fail to follow their flight plan due to various constraints that are encountered, such as altitude holding, speed control, path stretching and reroutes. It is important to model these constraints both for flight time forecasting as well as load forecasting. Such constraints are not deterministic and their variance is a major contributor to trajectory prediction error. Therefore our constraint modeler produces probabilistic constraint forecasts which, in turn, support probabilistic trajectory prediction. Advanced air traffic applications not only require trajectory predictions that (i) are as accurate as possible, but also that (ii) provide an indication of their error as well, which can vary substantially. Traditionally, predictors have produced deterministic trajectories and their uncertainty is often ignored. We also discuss in our proposal how our trajectory constraint modeler supports significant improvements in efficiency and manageability of trajectory predictors.

POTENTIAL NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
Our 4D Probabilistic Trajectory Constraint Modeler has several valuable applications for NASA. First, it will be an important addition to existing trajectory predictors. No modifications are required as our Probabilistic Trajectory Constraint Modeler will be used to enhance the accuracy of the input flight plan data. The result will be more accurate trajectory forecasting which will improve the efficiency, benefits and acceptance of NASA air traffic control and air traffic management tools. Also, because our modeler provides the probabilistic information about the constraints, it support probabilistic trajectory prediction which will be important in the next generation decision support tools. Finally, our Probabilistic Trajectory Constraint Modeler supports extremely fast trajectory prediction. Such a trajectory predictor will enable entirely new optimization approaches for traffic planning tools.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
Beyond NASA, potential applications for this work lie with operators ranging from major airlines to charters and air taxi services, the Federal Aviation Administration and international Air Navigation Service Providers (ANSPs). In fact we already have provided an initial version of an empirical trajectory predictor to an operator with great success. This product is useful for operators both for seasonal fleet planning, predeparture flight planning and real-time flight following. With more accurate flight times, operators can make more efficient use of their fleet and provide more accurate arrival times to their customers. More accurate flight times also improves the operator flight planning process. For instance, operators can compute more accurately the required fuel loading for their flights. This can reduce their takeoff weight, thus reducing their overall fuel burn and environmental impact. For their dispatch and flight following tasks, operators will have more accurate predictions of the future progress of a flight as it progresses along its route. In addition to operators, our Probabilistic Trajectory Constraint Modeler will be a valuable component for the Federal Aviation Administration and international Air Navigation Service Providers (ANSPs) for improved traffic flow planning.

TECHNOLOGY TAXONOMY MAPPING (NASA's technology taxonomy has been developed by the SBIR-STTR program to disseminate awareness of proposed and awarded R/R&D in the agency. It is a listing of over 100 technologies, sorted into broad categories, of interest to NASA.)
Algorithms/Control Software & Systems (see also Autonomous Systems)
Quality/Reliability
Simulation & Modeling

Form Generated on 04-23-15 15:37