NASA Funding Opportunity in Data Mining for System-Wide Safety and Assurance Technologies
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Development of Data Mining Methods to Discover Human-Automation Issues
Due date for Notice of Intent to propose (NOI) 3/22/12
Due date for proposals 4/26/12
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Public benefits derived from continued growth in the transport of passengers and cargo are
dependent on the improvement of the intrinsic safety attributes of current and future air vehicles that will operate in the Next Generation Air Transportation System (NextGen). The System-Wide Safety
and Assurance Technologies Project (SSAT) project will identify risks and provide knowledge
required to safely manage increasing complexity in the design and operation of vehicles and the air
transportation systems, including advanced approaches to enable improved and cost-effective
verification and validation of flight-critical systems. SSAT is focused on methods to assess and
ensure system-wide safety of complex aviation systems. The project will emphasize proactive
methods and technologies, and utilize a systems analysis approach to identify key issues and
maintain a portfolio of research leading to potential solutions. A proactive approach to managing
system safety requires (1) the ability to monitor the system continuously and to extract and fuse
information from diverse data sources to identify emergent anomalous behaviors after new
technologies, procedures, and training are introduced; and (2) the ability to reliably predict
probabilities of the occurrence of hazardous events and of their safety risks.
This research will focus on the development of validated data mining and machine learning based
methods to detect human-automation interaction issues on simulated data that is representative of
the interactions between humans and automation found on flight systems and on data from realworld
aircraft. The objective of this topic is to provide NASA with (1) robust methods for detecting
precursors to aviation safety incidents that are due to human-automation interaction issues; (2)
validated studies on data from a simulation that exhibits the appropriate statistical and operational complexities that are found in real-world human automation interactions; (3) demonstration of these methods on a data set comprised of discrete and continuous data and potentially textual, network, and other data types. The total of the data set under study should be at least 10 TB in size. NASA will participate in the latter tests by executing the algorithms provided by the awardee on real-world data; (4) development of a concept of operation for the algorithms on real-world flight systems; (5) demonstration that the candidate methods perform better than existing methods developed by NASA and its partners with respect to relevant metrics and comprehensibility of the results. Numerous papers describing methods developed by NASA are available on the DASHlink website at (c3.nasa.gov/dashlink). Metrics will be defined by the awardee and confirmed by NASA. Comprehensibility will!
be determined by the use of subject matter experts from NASA and, if needed, an organization suggested by the awardee.
For more information please see the solicitation below.
The following solicitation has been posted in Open status on NSPIRES:
Solicitation Number: NNH11ZEA001N-SSAT1
Solicitation Title: B.2 System-Wide Safety Assurance Technologies (SSAT1)
Due date for Notice of Intent to propose (NOI) 3/22/12
Due date for proposals 4/26/12
Amendment 6 to the NASA ARMD Research Opportunities in Aeronautics (ROA) 2011 NRA has been posted on the NSPIRES web sitehttp://nspires.nasaprs.com
This release solicits research proposals in Appendix B.2 for Development of Data Mining Methods to Discover Human-Automation Issues in support of the Aviation Safety Program System-Wide Safety Assurance Technologies Project.
NOIs are due March 22, 2012 and proposals are due April 26, 2012.
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Ashok N. Srivastava, Ph.D.
Project Manager, System-Wide Safety and Assurance Technologies
Steve Jacklin
NRA Manager, System-Wide Safety and Assurance Technologies
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