| QUANTITATIVE ASIL ESTIMATION USING FUZZY SET THEORY |
| Sung min Kim1, Gyeong-hun Do2, Junkeon Ahn3, Juneyoung Kim4 |
1Yonsei University
2Dongguk University
3Institute for Advanced Engineering
4Korea Testing Laboratory |
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| ABSTRACT |
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The 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 |
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Corresponding Author.
Juneyoung Kim , Email. 
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