A formal method for including the probability of erroneous human task behavior in system analyses
Matthew L. Bolton,
Xi Zheng and
Eunsuk Kang
Reliability Engineering and System Safety, 2021, vol. 213, issue C
Abstract:
Formal methods have been making inroads into the engineering of human–automation interaction (HAI) by allowing engineers to use mathematical proofs to determine whether normative or unanticipated erroneous human behavior can ever cause problems. However, these approaches are limited because they do not give engineers a way to assess the relative likelihood of different outcomes. In this work, we address this shortcoming by defining a new approach that combines formal approaches with human reliability analysis and probabilistic and statistical model checking. This approach ultimately allows analysts to compute the probability of different outcomes occurring in reactive HAI systems. We describe how this method was realized, assess its scalability, and demonstrate its capabilities with an automated teller machine example. We ultimately discuss our results and describe directions of future research.
Keywords: Human error; Formal methods; Model checking; Probabilistic modeling; Human reliability (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832021002921
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002921
DOI: 10.1016/j.ress.2021.107764
Access Statistics for this article
Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares
More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().