Safety and Reliability Assessment of Systems in Autonomous and Non-Autonomous Vehicles Industry: Two Classical and Fuzzy Approaches of Fault Tree Analysis

In this research, we examine the challenges of ensuring the safety of self-driving car software by presenting two real examples using the classic fault tree (FTA) approach. Process integration, insufficient data, and system complexity in the automotive manufacturing sector are the main uncertainty factors that are used to predict the probability of failure (FP) and are very influential in achieving improved system design and a reliable maintenance program. To deal with such uncertainties, by presenting a case study, we pay to fault tree analysis with a fuzzy approach to evaluate system reliability in a situation where only qualitative data such as experts’ opinions or decisions are available and described in terms of language. This research proposes a preventive knowledge-based technique for FP estimation towards an optimal design with system optimization and appropriate maintenance program in the automotive industry.

کلیدواژه ها:

Autonomous Systems ، ، Safety Assurance of Artificial ، Intelligence ، Fault Tree Analysis ، Fuzzy Set Theory ، Fuzzy Fault Tree Analysis