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dc.contributor.advisorJohn P. Thomas.
dc.contributor.authorCabosky, Rachel (Rachel Lynn)en_US
dc.contributor.otherMassachusetts Institute of Technology. Engineering and Management Program.en_US
dc.contributor.otherSystem Design and Management Program.en_US
dc.date.accessioned2021-10-08T16:48:16Z
dc.date.available2021-10-08T16:48:16Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/132809
dc.descriptionThesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020en_US
dc.descriptionCataloged from the official version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 127-129).en_US
dc.description.abstractIn 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.en_US
dc.description.statementofresponsibilityby Rachel Cabosky.en_US
dc.format.extent129 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectEngineering and Management Program.en_US
dc.subjectSystem Design and Management Program.en_US
dc.titleApplication of hierarchy to STPA : a human factors study on vehicle automationen_US
dc.title.alternativeApplication of hierarchy to System-Theoretic Process Analysisen_US
dc.title.alternativeHuman factors study on vehicle automationen_US
dc.typeThesisen_US
dc.description.degreeS.M. in Engineering and Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering and Management Programen_US
dc.identifier.oclc1262990537en_US
dc.description.collectionS.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Programen_US
dspace.imported2021-10-08T16:48:16Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSysDesen_US


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