Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/25903
Title: | A Fault-aware Sensor Fusion System for Autonomous Vehicles |
Authors: | Barkovic, Joshua |
Advisor: | Wassyng, Alan Lawford, Mark |
Department: | Computing and Software |
Keywords: | Autonomous;Safety;Sensor Fusion;STPA;Accidents;Autopilot;Design;Hazard Analysis;Tesla;Uber |
Publication Date: | 2020 |
Abstract: | There 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. |
URI: | http://hdl.handle.net/11375/25903 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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barkovic_joshua_j_202009_masc.pdf | Thesis | 10.64 MB | Adobe PDF | View/Open |
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