Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 127-129). / In a world where vehicle automation designed to remove "human error" is increasingly present on our roadways, are we actually safer? As we replace human tasks and decision making, the machines and the software used to substitute these actions become more complex. This increased complexity drives the need to thoroughly understand changes to the associated risk as well as the impacts to, and changing relationships with, the human driver. System-Theoretic Process Analysis (STPA) has been proven as an effective tool to evaluate risk by analyzing the system as a whole rather than at the component level. Notably, STPA includes, and evaluates, the operator as a part of the system. Additionally, STPA methodology provides the means to simply depict and communicate intricate system controls. Though it is clear that STPA can be performed with a range of system specificity, it has yet to be documented what types of recommendations can be provided as more complexity and detail is included in the system description. This thesis is used to demonstrate that STPA can be performed iteratively, and that significant insights to the system design can be obtained at each iteration or level. This method of evaluation includes the human factors extension and basic scenario generation to supplement the refinement process. To perform this analysis, an SAE Level 2 feature intended for highway traffic assist, proposed by Zenuity, is evaluated at three levels of detail--focusing on the driver-feature interface. Iteration and refinement are possible at all steps of STPA, but special attention is given here to the control structures, unsafe control actions, and scenarios. This work benefits risk management and hazard analysis by offering a methodology for managing complexity through hierarchical iteration, such that insights can be derived early and be refined throughout the analysis process. / by Rachel Cabosky. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/132809 |
| Date | January 2020 |
| Creators | Cabosky, Rachel (Rachel Lynn) |
| Contributors | Massachusetts Institute of Technology. Engineering and Management Program., System Design and Management Program., Massachusetts Institute of Technology. Engineering and Management Program |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 129 pages, application/pdf |
| Rights | MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided., http://dspace.mit.edu/handle/1721.1/7582 |
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