Grant: Discovery Grants Program - Individual
Memorial University of Newfoundland
$24,000.00
Collision assessment for UAV
FY 2012-13
Summary
The inability to see (sense) and avoid (SAA) other air traffic has been recognized by Transport Canada, FAA and ICAO as a major impediment preventing the integration of unmanned aerial vehicles (UAVs) into non-segregated airspace. An initial requirement was for UAVs to have equivalent level of safety (ELOS) similar to a human pilot being able to ""see"" and avoid traffic. But ELOS is now replaced by a more quantifiable measure: targeted level of safety (TLS), the acceptable mean number of near collisions per flight hour which could result in fatalities. My research thrust is aimed at a novel analysis tool to determine TLS, based on an industry-accepted statistical (encounter) model used to develop and validate TCAS. The approach is to determine TLS statistically by fast simulation over a large number of probable encounters. A novelty is that the analyzer is ""technology agnostic'': it can evaluate early-stage SAA algorithms from the developers and standards from the regulators, without reference to and prior to the implementation of a particular technology or adaptation of a certain standard. An early outcome could be a scientific quantification of risk (TLS) for UAV patrol duties over sparsely populated areas and this could have an immediate impact on the Government of Canada's policy on Arctic sovereignty. In longer term, by collaborating with MIT Lincoln Lab, a contractor to FAA, we are positioned to contribute ""Canadian content"", at an early stage, in the drafting of an FAA SAA standard, which will likely be later adopted by ICAO and Transport Canada. Within the aerospace sector, SAA development is stifled by a circular dependence: regulators are looking to the industries for input, but many industries are waiting for an approved standard before investing in a technology. This research will foster sector growth by breaking this deadlock. It pioneers a methodology which enables industry to assess a technology before equipment is manufactured, and legislators to validate a standard before it becomes law. The resulting quantification of risk will also help the insurance industry to underwrite commercial UAV services: a necessity for growth of the unmanned aircraft sector.
Program
Discovery Grants Program - Individual
Recipient
Location
Newfoundland and Labrador, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
157916-2010
Name nom
OYoung, Siu
Department département
Engineering and Applied Science, Faculty of
Organization id
89
Institution établissement
Memorial University of Newfoundland
Province en
Newfoundland and Labrador
Province fr
Terre-Neuve-et-Labrador
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2010
Award amount
24000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1512
Committee name en
Mechanical Engineering
Committee name fr
Génie mécanique
Area of application code
703
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Aerospace
Area of application fr
Aérospatial
Research subject code
2108
Research subject group en
Mechanical engineering
Research subject group fr
Génie mécanique
Research subject en
Aerospace, aeronautical and automotive engineering
Research subject fr
Génie aérospatial, aéronautique et automobile
Partie
3
Nb partie
5
Application title
Collision assessment for UAV
Keyword
NSERC
Application summary
The inability to see (sense) and avoid (SAA) other air traffic has been recognized by Transport Canada, FAA and ICAO as a major impediment preventing the integration of unmanned aerial vehicles (UAVs) into non-segregated airspace. An initial requirement was for UAVs to have equivalent level of safety (ELOS) similar to a human pilot being able to ""see"" and avoid traffic. But ELOS is now replaced by a more quantifiable measure: targeted level of safety (TLS), the acceptable mean number of near collisions per flight hour which could result in fatalities. My research thrust is aimed at a novel analysis tool to determine TLS, based on an industry-accepted statistical (encounter) model used to develop and validate TCAS. The approach is to determine TLS statistically by fast simulation over a large number of probable encounters. A novelty is that the analyzer is ""technology agnostic'': it can evaluate early-stage SAA algorithms from the developers and standards from the regulators, without reference to and prior to the implementation of a particular technology or adaptation of a certain standard. An early outcome could be a scientific quantification of risk (TLS) for UAV patrol duties over sparsely populated areas and this could have an immediate impact on the Government of Canada's policy on Arctic sovereignty. In longer term, by collaborating with MIT Lincoln Lab, a contractor to FAA, we are positioned to contribute ""Canadian content"", at an early stage, in the drafting of an FAA SAA standard, which will likely be later adopted by ICAO and Transport Canada. Within the aerospace sector, SAA development is stifled by a circular dependence: regulators are looking to the industries for input, but many industries are waiting for an approved standard before investing in a technology. This research will foster sector growth by breaking this deadlock. It pioneers a methodology which enables industry to assess a technology before equipment is manufactured, and legislators to validate a standard before it becomes law. The resulting quantification of risk will also help the insurance industry to underwrite commercial UAV services: a necessity for growth of the unmanned aircraft sector.