Referenced Items are not available for this document.
A machine learning technique for automating the traditional controller tests process that evaluates autonomous-vehicle software controllers is discussed. In the proposed technique, a controller is subjected to an adaptively chosen set of fault scenarios in a vehicle simulator, and then a genetic algorithm is used to search for fault combinations that produce noteworthy actions in the controller. This approach has been applied to find a minimal set of faults that produces degraded vehicle performance and a maximal set of faults that can be tolerated without significant performance loss.<
Published in:
IEEE Expert
(Volume:8
,
Issue:
5
)
Date of Publication: Oct. 1993
- Page(s):
- 9 - 14
- ISSN :
- 0885-9000
- INSPEC Accession Number:
- 4562660
- Digital Object Identifier :
- 10.1109/64.236476
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Oct. 1993
- Sponsored by :
- IEEE Computer Society
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