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Understanding Take-Over in Automated Driving: A Human Error Analysis

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HCI in Mobility, Transport, and Automotive Systems (HCII 2021)

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Abstract

Automation offers a new way of driving, but often the human error (HE) in the process of take-over results in adverse effects of unrecognized risks. Hence, the impact of HE in safety of automated driving remains a major problem. This paper proposed a Human error analysis method based on analysis of the root cause of HEs events to understand the process of take-over and identify root cause of take-over failure in automated driving. Simulated driving practice with videos and questionnaire were conducted to identify the main factors leading to HEs in take-over. Human factors events diagram was used to better understand take-over as a human factor event and to provide information for root cause of take-over failure recognition. The results reveal that the most common failure mode in take-over is cognition error caused by driver poor mental state such as driver fatigue and reaction ability, followed by control error caused by inappropriate take-over request (TOR). Determination of these failure modes provide evidence for increasing or repairing barriers in the process of take-over. The suggested cognition-corresponding model of take-over showed that take-over is a complex human-machine interaction process, thus the causes of HEs should be discussed from a multi-dimensional perspective, and explored through empirical research.

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Authors and Affiliations

  1. College of Design and Innovation, Tongji University, Fuxin Road 281, Shanghai, 200092, China

    Jue Li, Long Liu & Liwen Gu

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  1. Jue Li
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  2. Long Liu
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  3. Liwen Gu
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Correspondence to Long Liu .

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Editors and Affiliations

  1. Technische Universität Ilmenau, Ilmenau, Germany

    Heidi Krömker

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Li, J., Liu, L., Gu, L. (2021). Understanding Take-Over in Automated Driving: A Human Error Analysis. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2021. Lecture Notes in Computer Science(), vol 12791. Springer, Cham. https://doi.org/10.1007/978-3-030-78358-7_20

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  • DOI: https://doi.org/10.1007/978-3-030-78358-7_20

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  • Online ISBN: 978-3-030-78358-7

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