Abstract
There are always submerged risks involved with advanced technology; therefore, it is necessary for policymakers, inventors and technology companies to scrutinise potential risks when they consider implementing new technology. This paper attempts to extract generic lessons from a failure relevant to autonomous transport systems. We use fault tree analysis (FTA), a reliability block diagram (RBD) approach and failure mode and effect analysis (FMEA), for analysing a fatal pedestrian accident caused by a level-3 self-driving car in 2018. The work highlights the importance of prematurity of test driving self-driving cars on public roads and the potential of an insightful analysis method that can capture human factors. In this work we theorise accident reporting systems, and provide a framework for triple loop learning.
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Labib, A., Nagase, Y., Hadleigh‐Dunn, S. (2020). Analysis of Human Factors Failures in an Incident of Self-driving Car Accident. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-030-50943-9_28
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DOI: https://doi.org/10.1007/978-3-030-50943-9_28
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