Impact of control authority on the drivers' perceived responsibility: a haptic shared control driving study

Master thesis (2021)

Authors

C.H. Kok Mechanical Engineering

Contributors

N.W.M. Beckers Human-Robot Interaction - Mechanical, Maritime and Materials Engineering (mentor)
David Abbink Human-Robot Interaction - Mechanical, Maritime and Materials Engineering (graduation committee member)
L. Cavalcante Siebert Interactive Intelligence - EEMCS (graduation committee member)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2021 Cedric Kok
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Published Date

08-04-2021

Language

English

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Faculty

Mechanical Engineering

Abstract

More and more vehicles have multiple advanced driver-assistance systems (ADAS), that take over tasks from the human driver, thereby taking the driver out of the loop of control. This might create a discrepancy between the responsibility that the human driver feels and the responsibility that is attributed to them when something goes wrong. Previous studies into perceived responsibility were mostly conducted in traded control systems, in which either the vehicle or the driver was performing the task, and tasks were shifted between them. In haptic shared control systems the automation and human driver cooperate continuously. The Level of Haptic Authority (LoHA) determines how strong the controller enforces its guidance. We examine how this LoHA impacts the driver's own perceived outcome responsibility, as well as that attributed to the automation when the automation makes a mistake. We found that when authority is shifted towards the car, the human driver feels less responsible, and attributes more responsibility to the automation, but only to a certain degree. Our findings correspond with previous research and with our own hypothesis. They add a new perspective to the current literature, as this is the first research-paper to examine responsibility perception in haptic shared driving from the drivers perspective. More research in the human driver's experience is needed to better understand human behaviour whilst driving with driving automation systems.