The level of autonomous functions in vehicular control systems has been on a steady rise. This rise makes it more challenging for control system engineers to ensure a high level of safety, especially against unexpected failures such as stochastic hardware failures. A generic Backtracking Process Algorithm (BPA) based on a deductive implementation of the Markov/Cell-to-Cell Mapping technique is proposed for the identification of critical scenarios leading to the violation of safety goals. A discretized state-space representation of the system allows tracing of fault propagation throughout the system, and the quantification of probabilistic system evolution in time. A case study of a Hybrid State Control System for an autonomous vehicle prone to a brake-by-wire failure is constructed. The hazard of interest is collision with a stationary vehicle. The BPA is implemented to identify the risk significant scenarios leading to the hazard of interest.
@article{arxiv.1804.04348,
title = {Identification of Risk Significant Automotive Scenarios Under Hardware Failures},
author = {Mohammad Hejase and Arda Kurt and Tunc Aldemir and Umit Ozguner},
journal= {arXiv preprint arXiv:1804.04348},
year = {2018}
}