{"title":"Comparison of the HAZOP, FMEA, FRAM and STPA Methods for the Hazard Analysis of Automatic Emergency Brake Systems","authors":"Liangliang Sun, Yanfu Li, E. Zio","doi":"10.1115/1.4051940","DOIUrl":null,"url":null,"abstract":"\n As autonomous vehicle (AV) intelligence for controllability continues to develop, involving increasingly complex and interconnected systems, the maturity level of AV technology increasingly depends on the systems reliability level, also considering the interactions among them. Hazard analysis is typically used to identify potential system risks and avoid loss of AV system functionality. Conventional hazard analysis methods are commonly used for traditional standalone systems. New hazard analysis methods have been developed that may be more suitable for AV system-of-systems complexity. However, a comprehensive comparison of hazard analysis methods for AV systems is lacking. In this study, the traditional hazard analysis methods, hazard and operability (HAZOP) and failure mode and effects analysis (FMEA), as well as the most recent methods, like functional resonance analysis method (FRAM; Hollnagel, 2004, 2012) and system-theoretic process analysis (STPA; Leveson, 2011), are considered for implementation in the automatic emergency braking system. This system is designed to avoid collisions by utilizing the surrounding sensors to detect objects on the road, warning drivers with alerts about any collision risk, and actuating automatic partial/full braking through calculated adaptive braking deceleration. The objective of this work is to evaluate the methods in terms of their applicability to AV technologies. The advantages of HAZOP, FMEA, FRAM, and STPA, as well as the possibility of combining them to achieve systematic risk identification in practice, are discussed.","PeriodicalId":44694,"journal":{"name":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","volume":"5 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2021-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4051940","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 17
Abstract
As autonomous vehicle (AV) intelligence for controllability continues to develop, involving increasingly complex and interconnected systems, the maturity level of AV technology increasingly depends on the systems reliability level, also considering the interactions among them. Hazard analysis is typically used to identify potential system risks and avoid loss of AV system functionality. Conventional hazard analysis methods are commonly used for traditional standalone systems. New hazard analysis methods have been developed that may be more suitable for AV system-of-systems complexity. However, a comprehensive comparison of hazard analysis methods for AV systems is lacking. In this study, the traditional hazard analysis methods, hazard and operability (HAZOP) and failure mode and effects analysis (FMEA), as well as the most recent methods, like functional resonance analysis method (FRAM; Hollnagel, 2004, 2012) and system-theoretic process analysis (STPA; Leveson, 2011), are considered for implementation in the automatic emergency braking system. This system is designed to avoid collisions by utilizing the surrounding sensors to detect objects on the road, warning drivers with alerts about any collision risk, and actuating automatic partial/full braking through calculated adaptive braking deceleration. The objective of this work is to evaluate the methods in terms of their applicability to AV technologies. The advantages of HAZOP, FMEA, FRAM, and STPA, as well as the possibility of combining them to achieve systematic risk identification in practice, are discussed.