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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/25903
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DC FieldValueLanguage
dc.contributor.advisorWassyng, Alan-
dc.contributor.advisorLawford, Mark-
dc.contributor.authorBarkovic, Joshua-
dc.date.accessioned2020-10-11T01:19:36Z-
dc.date.available2020-10-11T01:19:36Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/11375/25903-
dc.description.abstractThere have been several accidents involving autonomous vehicles on public roadways under scenarios that are normally avoidable by competent human drivers. This thesis contains a review of these accidents and their causes as a result of inadequate hazard mitigation. As a solution to this problem, a novel design pattern is proposed. This design pattern was developed from a hazard analysis using Systems Theoretic Process Analysis ( STPA ) methodologies that analyzed the circumstances common to several of these accidents. To demonstrate the effectiveness of the novel design pattern, an example system is constructed and tested in simulation against several accident scenarios similar to the ones studied. The results are then explained to demonstrate the effectiveness of the proposed design pattern.en_US
dc.language.isoenen_US
dc.subjectAutonomousen_US
dc.subjectSafetyen_US
dc.subjectSensor Fusionen_US
dc.subjectSTPAen_US
dc.subjectAccidentsen_US
dc.subjectAutopiloten_US
dc.subjectDesignen_US
dc.subjectHazard Analysisen_US
dc.subjectTeslaen_US
dc.subjectUberen_US
dc.titleA Fault-aware Sensor Fusion System for Autonomous Vehiclesen_US
dc.typeThesisen_US
dc.contributor.departmentComputing and Softwareen_US
dc.description.degreetypeThesisen_US
dc.description.degreeMaster of Applied Science (MASc)en_US
Appears in Collections:Open Access Dissertations and Theses

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