Methods to ensure software safety for safety-critical autonomous systems : a systematic literature review
Shrestha, Bikash (2021)
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Many companies are working on autonomous systems, such as autonomous vehicles and autonomous vessels, as the solution to reduce human errors that can result in huge losses. Over the past decade, various machine learning techniques were implemented for controlling autonomous systems. Due to the safety-critical nature of autonomous systems, it is important to ensure software safety along with the safety of the physical system of an autonomous system. In this paper, a systematic literature review method is used to analyse the various aspects of software safety in an autonomous system. Specifically, this paper assesses the existing techniques, such as software development guidelines, system design and architecture, machine learning techniques, and formal verification methods, to ensure software safety in autonomous systems and summarizes the challenges referred to in the literature concerning software safety of autonomous systems. The results presented in this paper are relevant to the researchers seeking better methods to ensure software safety in autonomous systems.