Accident Case Study Analysis of Developmental Automated Driving System Collison

EasyChair Preprint 13900, version 1

Abstract

The aim of the Case study is to produce a list of accident causal factors using the Cybernetic risk management model with the hybrid Swiss Cheese Model (SCM) and Management Oversight & Risk Tree (MORT) Methodology. The hybrid SCM/MORT methodology incorporates Jens Rasmussen’s risk management framework (RMF) and is augmented by including the Heuristics & Biases approach to make the methodology capable of identifying latent failures conditions at all levels of the socio-technical system that control the system of interest (SOI). The desk top study included collection of information and data that is publicly available to represent all relevant viewpoints to ensure completeness. The results raise awareness of latent causal factors in the form of biases that have impact on Risk management, Decision making, Assurance and wider Human factors concerns that are relevant and applicable to Artificial Intelligence/ Machine Learning (AI/ML) domain. It is hoped the Case Study will contribute to reflection on the part of systems engineers to help them plan, design, develop and operate safer automated vehicle systems.

Keyphrases: AI/AV Safety, Heuristics and Biases in Risk Management, The Socio-technical Risk Management Framework, accident analysis

@booklet{EasyChair:13900,
  author    = {Sanjeev Appicharla},
  title     = {Accident Case Study Analysis of Developmental Automated Driving System Collison},
  howpublished = {EasyChair Preprint 13900},
  year      = {EasyChair, 2024}}