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Human Factor Risks in Driving Automation Crashes

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HCI in Mobility, Transport, and Automotive Systems (HCII 2023)

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Driving automation systems are capable of continuously performing part or all of the dynamic driving task. Driving automation is intended to reduce the probability and severity of traffic crashes by minimizing manual operation. However, inadequate automation systems (including advanced driver assistance systems mounted on Level 2 vehicles and automated driving systems mounted on Level 3 or higher levels vehicles) and inappropriate human-automation interaction will threaten road safety. This study analyzed the factors of crashes related to driving automation from the perspective of human factor risks. We summarized the crashes and categorized the probable causes mentioned in six accident reports from National Transportation Safety Board. We extracted common causal factors related to human drivers, including inappropriate using ways of driving automation, human distraction or disengagement, and complacency (overreliance) on vehicle automation. Finally, we discussed the relationship between the extracted common causes and previous insights in the driving automation domain, such as the rationality of complacency as a causal factor, and provided potential countermeasures.

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This research was supported by the National Natural Science Foundation of China (Grant No. 72071143 and T2192933).

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Correspondence to Peng Liu .

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Chu, Y., Liu, P. (2023). Human Factor Risks in Driving Automation Crashes. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2023. Lecture Notes in Computer Science, vol 14048. Springer, Cham.

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  • Print ISBN: 978-3-031-35677-3

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