Human Factors of Transitions in Automated Driving

Doctoral Thesis (2020)
Author(s)

Zhenji Lu (TU Delft - Mechanical Engineering)

Contributor(s)

Joost de Winter – Promotor (TU Delft - Mechanical Engineering)

Riender Happee – Promotor (TU Delft - Mechanical Engineering)

Research Group
Intelligent Vehicles
DOI related publication
https://doi.org/10.4233/uuid:88dcb158-5fc3-4222-a402-4e484fa84414 Final published version
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Publication Year
2020
Language
English
Research Group
Intelligent Vehicles
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Abstract

In the last decades, advanced driver-assistance systems have contributed to improved road safety. With the recent advance of technology, automotive automation is taking more and more tasks away from the driver. Although automation removes human imprecision and variability, it also introduces out-of-the-loop problems such as complacency, skill degradation, mental underload, mental overload, and loss of situation awareness. Additionally, the rising levels of automation have contributed to an increasingly complex interaction between the automation and the driver, where driver and automation may have to change roles while driving. The objective of this PhD thesis is to understand what types of ‘transitions’ occur between the automation and the driver, how drivers process visual information to rebuild situation awareness and make decisions during these transitions, and how to make the transitions from automation to human safer and more acceptable for the driver...

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