Establishment of Accident Analysis Method for Sociotechnical System by System Theory

2022 Fiscal Year Final Research Report

• Project/Area Number: 21K21301
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 1001:Information science, computer engineering, and related fields
• Research Institution: Tohoku University of Community Service and Science (2022); National Institute of Informatics (2021)
• Principal Investigator: KANEKO TOMOKO 東北公益文科大学, 公私立大学の部局等, 研究員 (60906345)
• Project Period (FY): 2021-08-30 – 2023-03-31
• Keywords: 事故分析手法 / AIシステム / 社会技術システム / CAST / 自動運転 / セキュリティ・レジリエンス / FRAM / 意思決定インテリジェンス

Outline of Final Research Achievements

This project aims to tackle the issue that the accuracy of conventional single models alone is not enough to evaluate the entire system in a system that includes AI, and based on system theory, to measure risk from a global perspective, to find points to be improved based on hazard factors, to determine leading indicators based on hazard factors and external conditions, and to develop optimal countermeasures and problemーーーsolving. The project is also aimed at creating a system that can be used in a wide range of fields, such as information science and engineering, and in developing a system that can be used in a wide range of areas, such as information technology and information engineering.

Free Research Field

情報科学、情報工学およびその関連分野

Academic Significance and Societal Importance of the Research Achievements

事故は社会インフラに多大な影響を社会に与え，同じような事故は繰り返し起きている．一方、現状のAIは，特に安全性や信頼性に対して大きな懸念がある．AIの動作は安全保証しがたく，AIシステムである自動運転は実証段階において，複数の人身事故が発生している．この状態の解決のために本研究では，事故分析手法CASTの拡張分析手順の研究やAIシステムの事故分析を行った．