Human Factors of Transitions in Automated Driving

Doctoral thesis (2020)

Authors

Z. Lu Intelligent Vehicles - Mechanical, Maritime and Materials Engineering
Research Group
Intelligent Vehicles (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2020 Z. Lu
DOI: https://doi.org/10.4233/uuid:88dcb158-5fc3-4222-a402-4e484fa84414
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Published Date

2020

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Intelligent Vehicles

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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- Embargo expired in 22-10-2020