NASA SBIR 2017 Solicitation


PROPOSAL NUMBER: 171 A3.02-8684
SUBTOPIC TITLE: Autonomy of the National Airspace Systems (NAS)
PROPOSAL TITLE: Airport Movement Area Closure Planner

SMALL BUSINESS CONCERN (Firm Name, Mail Address, City/State/Zip, Phone)
2770 De La Cruz Boulevard
Santa Clara, CA 95050 - 2624
(408) 736-2822

PRINCIPAL INVESTIGATOR/PROJECT MANAGER (Name, E-mail, Mail Address, City/State/Zip, Phone)
Mr. William Keller
2770 De La Cruz Boulevard
Santa Clara, CA 95050 - 2624
(408) 736-2822

CORPORATE/BUSINESS OFFICIAL (Name, E-mail, Mail Address, City/State/Zip, Phone)
Mr. Charles Winkleman
2770 De La Cruz Boulevard
Santa Clara, CA 95050 - 2624
(408) 736-2822

Estimated Technology Readiness Level (TRL) at beginning and end of contract:
Begin: 2
End: 4

Technology Available (TAV) Subtopics
Autonomy of the National Airspace Systems (NAS) is a Technology Available (TAV) subtopic that includes NASA Intellectual Property (IP). Do you plan to use the NASA IP under the award?

TECHNICAL ABSTRACT (Limit 2000 characters, approximately 200 words)
This SBIR research develops an automation tool improving temporary and permanent runway closure management. The Movement Area Closure Planner (MACP) provides airport stakeholder capability to improve decision processes and decision outcomes during surface closure events by developing a what-if simulation functionality to explore multiple operational decision choices during surface closure events. MACP ensures realistic simulation of airport traffic operations by relying on a high-fidelity airport simulator which has been used in multiple high-fidelity airport operations analyses for FAA and airport operational improvement evaluation projects. The key innovation added to a high-fidelity simulator is a machine learning based predictive engine which realistically projects multiple probable future evolution trajectories for key factors influencing the airport operations under surface closure events (e.g., predicted gate pushback rates, predicted runway arrival and departure demands, predicted departure queue lengths, predicted de-ice pad queue lengths). Reliable what-if analysis is enabled by taking each of these probable evolution trajectories of key variables and kicking off multiple airport traffic simulations, each simulating airport traffic under one of these probable scenarios. Another variable input for the simulations is surface closure operational decision parameters, e.g., start and end times for runway closure. Multiple probable futures are simulated for each choice of surface closure operational decision parameter, thereby enabling us to predict not just one value for key airport performance metrics, but multiple probable values each associated with its probability of occurrence.

POTENTIAL NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
MACP is relevant to NASA's AORG that supports R&D airline focused work, including the airline operations center (AOC) & flight deck. AORG seeks to integrate industry ideas with NASA solutions to develop innovative and automated solutions for increasing airline operations efficiency and safety. The AORG is gaining a better understanding of the effects of winter storms on NAS operations (especially airports) and developing knowledge and tools needed to improve efficiency (reduce cancelations and delays). AORG developed a tool called FACT. FACT is a web-based application that would improve winter weather operations within the AOC and at airports.
Accessing the MACP would represent a significant shift in airport runway closure decision making processes. The ability to create a reliable data driven CDM process automates the decision process during irregular (non-emergency) operational situations, namely prediction. By having predictive data at hand when multiple decision making processes are active, airport staff have a greater flexibility to focus on safety related aspects - thereby enhancing safety. A quick and easy tool that can provide efficiency and safety benefits, reduce staff workload, and drive data into the multiple management decision making layers would be highly desirable for commercial application. Deploying this tool across a wide variety of airport sizes and types could have a significant positive efficiency impact on the NAS.

POTENTIAL NON-NASA COMMERCIAL APPLICATIONS (Limit 1500 characters, approximately 150 words)
What-if scenario analysis decision support tool supports runway closure decision making at the FAA ATCSCC, FAA ARTCCs and AOCs supporting NAS-wide what-if analyses while planning and negotiating potential TMI actions under a CDM operational paradigm. MACP input portals can also be installed at busy TRACONs and Towers so controllers or Traffic Management Coordinators (TMCs) at those facilities can provide real-time inputs on current or forecast local conditions. Airport operations staff is the most reliable local runway closure forecast source and MACP portals provide an expedient approach for generating the most reliable forecasts. Deploying MACP as a web based tool enables airlines and ATCT to share data with central airport tools to improve CDM. Airlines providing expected gate pushback times, high-value flight preferences, ATCT can share data on the expected arrival landing rates, airspace configuration (e.g., what departure-fixes are open for use), expected runway configuration changes, etc. Enhanced non-NASA application includes predicting and managing the closure of any movement area during any selected airfield irregular operational condition. Movement areas may include any surface between the gate and the departure runway surface or may be limited to portions between those points. Movement area closures can be more disruptive to airlines than a runway closure due to extended taxi times, fuel burn, and overall delay.

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.)
Air Transportation & Safety
Simulation & Modeling

Form Generated on 04-19-17 12:59