The Backtracking Process Algorithm : A Dynamic Probabilistic Risk Assessment Method for Autonomous Vehicle Control Systems

There is an increasing demand for quantitative risk assessment tools capable of providing safety assurances for autonomous vehicle control systems. This demand is due to the recent rise of autonomous functions that are being incorporated into aerospace and automotive domains. A deductive implementation of Markov Cell-to-Cell Mapping Technique is proposed for the identification of risk significant scenarios that may lead to violations of safety goals. Challenges of the methodology are identified, and a breadth-first implementation of the Backtracking Process Algorithm (BPA) is proposed to meet these challenges. Three autonomous vehicle case studies on which BPA was successfully implemented are summarized.