As Autonomous Driving Systems (ADS) technologies become a more prevalent and sophisticated component of modern vehicle fleets, the automotive industry faces significant challenges to ensuring and proving the safety of these technologies to the public. Under the remit of the International Standards Office (ISO), for the past few years the global industry has been hard at work developing a standard to define global concepts, methods and processes for ensuring the safety of autonomous vehicles. This global effort has come to a fruition in the recent publication of the draft international standard of ISO 21448 “Safety of the Intended Functionality” (SOTIF).
Sensmetry’s recent research paper “Self-driving car safety quantification via component-level analysis” (preprint available to download from arXiv) has been peer-reviewed, accepted, and is soon to be published by the SAE in a special safety-focused issue of its Journal on Automated and Connected Vehicles. In the paper Sensmetry presents a rigorous modular statistical methodology for quantitatively arguing safety or its insufficiency of an Automated Driving Systems (ADS).