Quantitative ASIL Estimation Using Fuzzy Set Theory
- PDF / 341,734 Bytes
- 8 Pages / 595 x 842 pts (A4) Page_size
- 38 Downloads / 321 Views
ght © 2020 KSAE/ 11711 pISSN 12299138/ eISSN 19763832
QUANTITATIVE ASIL ESTIMATION USING FUZZY SET THEORY Sung min Kim1), Gyeong-hun Do2), Junkeon Ahn3) and Juneyoung Kim4)* Department of Information and Industrial Engineering, Yonsei University, Seoul 03722, Korea 2) Department of Convergence Standard, Dongguk University, Seoul 04620, Korea 3) Plant Engineering Center, Institute for Advanced Engineering (IAE), Goan-ro 51, Baegam-myeon, Gyeonggi-do, Yongin 17180, Korea 4) Industrial Convergence Technology Center, Korea Testing Laboratory, Digital-ro 26-gil, Guro-gu, Seoul 08389, Korea
1)
(Received 22 January 2019; Revised 25 October 2019; Accepted 9 December 2019) ABSTRACTThe present study proposes a method that numerically quantifies automotive safety integrity level (ASIL). Additionally, the method reduces the uncertainty in the risk estimation step by subdividing the ASIL step by applying fuzzy theory to reduce the ambiguity of ASIL with an extremely wide step. The conventional risk-based design concept is adopted to quantify ASIL, and fuzzy modeling is used to express the vehicle safety integrity ratings of uncertain automotive electrical equipment. To overcome the uncertainty, we fuzzify the variable using the mean expected value method and select the trapezoidal fuzzy number. The final fuzzy output is generated using Mamdani’s method with 25 fuzzy rules combined with variables to obtain risk. This theory provides a useful approach for overcoming the inherent uncertainty in ASIL. We attempt to establish the effectiveness of the proposed method by utilizing it to quantify the automatic emergency-braking device scenario, which is a typical target system. KEY WORDS : Autonomous vehicle, Automotive safety integrity level (ASIL), Vehicle control, Driver assistance, Intervehicle communications, Automated highway systems, Autonomous emergency-braking system (AEB), Safety and human factors, Driver performance, Driver error, Crash causation, Crash countermeasures, Fuzzy theory
NOMENCLATURE
the functionality of electronic control units (ECUs) and enables operating environments to be more pleasant and safe via ECU modules. It amplifies the function of ECUs. Accordingly, the importance of embedded software, which regulate electronic units, is also increasing. Even though electronic devices provide the abovementioned advantages, they experience several errors (Fagnant and Kockelman, 2015; Fagnant and Kockelman, 2014; Wadud et al., 2016). ISO 26262 has been officially established as the importance of safety has increased with the rapid development of automotive electronic control systems. ISO 26262 is a functional safety standard for preventing the accidents caused by errors in embedded software in automobiles. ISO 26262 is designed to overcome the limitations of the IEC 61508 standard—the quality management standard for existing automotive SWs—as a comprehensive standard for the safety of general electrical and electronic equipment (Young and Walker, 2017; International Organization for Standardization, 2018). ISO 2
Data Loading...
