From Nobel Prize(s) to Safety Risk Management: Lessons Learnt from 2018 Uber collision for their Application to Autonomous Train Systems

The research and development of autonomous driving systems in the automotive sector is driving the trend towards autonomous train systems as well. However, railway safety risk management has been facing a crisis since the promulgation of the 2004 EU Safety Directive. This directive demands a cultural shift away from current engineering safety management practices despite the good statistical record of railways as a safe transport mode. Using techniques such as Failure Mode, Effects, (and Criticality) Analysis and Bowtie analysis do not support identification of systematic errors at the higher levels of socio-technical system that is involved in monitoring and certifying the autonomous train systems. Further, the traditional risk assessment process used in the rail sector does not address decision mistakes noted in the decision making under uncertainty literature. Past research on accident case studies indicates that organizational and management factors that contribute to fallible decisions are not included in the risk assessment process. Thus, the hypothesis of underestimation of significant hazards and risks such as autonomous train system collision hazard and over-estimation of failure of human safety supervisor of autonomous train system is proposed.
One benefit of the paper is to contribute to reflection on the part of systems engineers to help them plan, design, develop and operate safe autonomous train systems and related signaling systems as well.

Keywords: Complex socio-technical systems, Decision making under Uncertainty, Heuristics & Biases, Safety risk management, Safety culture, Autonomous train systems.