Perception Creates Reality - Factors influencing the driver’s perception and consequent understanding of Driving Automation Systems
Licentiate thesis, 2020
The research for this thesis is organised into three empirical studies, embedding a mixed-methods research design. Study 1 aimed at investigating usage of DAS during different driving situations by facilitating an online survey. Studies 2 and 3 aimed to explore how drivers motivate their usage of driving automation systems, and which factors affect their understanding. Study 2 adopted an Explanatory Sequential Mixed Methods approach, consisting of a Naturalistic Driving Study and in-depth interviews to elicit knowledge about how users understand the DAS, and which factors influence usage. In Study 3 observations and interviews during an on-road driving session with a Wizard-of-Oz vehicle were conducted to gain insights into how users build an understanding of a vehicle with multiple levels of automation.
The results show that the users of such systems, independent of the level of automation, talked about the systems by referring to different elements: the Context, the Vehicle, and the Driver. In addition, eleven recurring aspects describing the drivers’ understanding of an automated system were discerned. Furthermore, six factors were identified that influence how drivers perceive driving automation during usage. The six factors are Preconceptions, Perceived Usefulness, Previous Experiences, Trust, System Performance, and Driving Behaviour of the Vehicle. Collectively, the identified aspects and factors constitute the building blocks of a process describing how drivers perceive driving automation systems and how this shapes their consequent understanding. The process is presented as a descriptive unified model.
The main contribution of this thesis is twofold: unification of aspects found to shape a driver’s understanding of a driving automation system, and the presentation of a unified descriptive model of the process showing how this understanding is shaped through what the driver perceives at the moment of use.
levels of automation
mixed methods research
Chalmers, Industrial and Materials Science
Karlsson, I.C.M and Novakazi, F. (2020). Drivers’ usage of Advanced Driver Assistance Systems – An International Survey. Manuscript submitted to the Journal Transportation Research Part F: Traffic Psychology and Behaviour.
Effects of the driving context on the usage of Automated Driver Assistance Systems (ADAS) -Naturalistic Driving Study for ADAS evaluation
Transportation Research Interdisciplinary Perspectives,; Vol. 4(2020)
Stepping over the Threshold - Linking Understanding and Usage of Automated Driver Assistance Systems (ADAS)
Transportation Research Interdisciplinary Perspectives,; Vol. 8(2020)
Levels of what? Investigating drivers' understanding of different levels of automation in vehicles
Journal of Cognitive Engineering and Decision Making,; Vol. 15(2021)p. 116-132
Johansson, M. and Novakazi, F. (2020). To Drive or not to Drive – When Users Prefer to Use Automated Driving Systems. [Submitted to 7th Humanist Conference but conference postponed until 2021].
Who's in charge?: The influence of perceived control on responsibility and mode awareness in driving automation
IT - Information Technology,; Vol. 62(2021)
Semi-autonomous driving and its effect on mode-awareness and user experience
VINNOVA (2017-01946), 2017-10-02 -- 2021-12-31.
Production Engineering, Human Work Science and Ergonomics
Other Engineering and Technologies not elsewhere specified
Areas of Advance
Chalmers University of Technology
The licentiate seminar will be broadcast online via ZOOM
Opponent: Andrew Morris, Professor of Human Factors in Transport Safety, Loughborough University, UK