Design for Perception - A human-centric approach to the design of driving automation systems based on the driver’s perception
Doctoral thesis, 2023

The automotive industry is rapidly developing driving automation systems (DAS) with the aim of supporting drivers by means of the automation of longitudinal and lateral vehicle control. As vehicle complexity increases and update-over-the-air features are enabling continuous development of vehicle software and functionality, the driver’s understanding of their responsibility and their vehicle’s capabilities and limitations is becoming significantly more important. In order to motivate manufacturers to adopt a human-centric perspective for the development of driving automation systems, the factors influencing the driver’s perception of these systems during their usage needs to be understood. Therefore, the aim of this thesis is to contribute towards the systematic development of DAS from a human-centric perspective.

The core research for this thesis is organised into four empirical studies, embedding a mixed methods research design. Study I aimed to investigate the usage of DAS in different driving contexts by facilitating an online survey to drivers in Germany, Spain, China, and the US.
Study II aimed to explore the driver’s contextual usage of DAS and which factors affect their understanding and employed an explanatory sequential mixed methods approach consisting of a Naturalistic Driving Study (NDS) in the greater Gothenburg area over a 7-month period. This was followed up by in-depth interviews to elicit knowledge about how drivers understand the DAS, and which factors influence their usage.
Study III and Study IV aimed to gain further insights into which factors in the driver’s perception of the DAS affect their understanding and consequent usage of DAS. Thus, Study III applied a Wizard-of-Oz on-road driving study, simulating a vehicle offering a Level 2 and a Level 4 DAS in the San Francisco Bay Area paired with pre- and post-driving in-depth interviews. Finally, Study IV applied a Wizard-of-Oz on-road driving study, simulating a vehicle offering a Level 2 and a Level 3 DAS, and contrasting two different human machine interfaces in Gothenburg, paired with post-driving in-depth interviews.

The results from these studies allowed a contribution to the body of research in a theoretical and practical form. The theoretical contribution is the unification of aspects that shape a driver’s understanding of a DAS into a conceptual model. The unified model describes the process of how this understanding is shaped through the driver’s perception of the DAS. The developed model further facilitated the development of a design toolkit by applying a participatory design approach (Study V) that facilitated co-creation sessions with domain experts (designers of DAS) in an industrial setting, which is considered a practical contribution to the field. The toolkit serves as a common foundation for aligning the motivations and goals of developers, designers, and strategists with regulators.
Consequently, it can support practitioners to: 1. explore possible solutions driven by a systematic approach; 2. identify areas of improvement by applying the lens of the user; and 3. ideate and evaluate design decisions through a structured process. Thus, it facilitates the identification of design, evaluation, and training approaches that promote appropriate usage strategies for drivers and the building of a sufficient understanding of a DAS.

design method

human-centric design

human factors.

mental model

driving automation

cognitive engineering


empirical research

design tool


levels of automation

mixed-methods research

Virtual Development Laboratory (VDL), Campus Johanneberg: Chalmers Tvärgata 4C
Opponent: Greg A. Jamieson, PhD, P.Eng., Professor and Clarice Chalmers Chair of Engineering Design in the Department of Mechanical & Industrial Engineering at the University of Toronto.


Fjolle Novakazi

Chalmers, Industrial and Materials Science, Design & Human Factors

Stepping over the Threshold - Linking Understanding and Usage of Automated Driver Assistance Systems (ADAS)

Transportation Research Interdisciplinary Perspectives,; Vol. 8(2020)

Journal article

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

Journal article

Johansson, M., Novakazi, F., Strömberg, H. and Karlsson, I.C.M. (2023, accepted with revision). Piecing together the puzzle – exploring how different information sources influence users’ understanding of automated vehicles. Behaviour & Information Technology.

Kim, S., Novakazi, F. & I.C.M. Karlsson (2023, in submission). Interaction Challenges in Automated Vehicles with Multiple Levels of Driving Automation - An On-Road Study. Applied Ergonomics.

Novakazi, F. & Bligård, L.-O. (2023, in submission). Design for Perception – Co-Creation and Evaluation of a Design Tool for Driving Automation Systems. Conference of Intelligent User Interfaces 2024.

Driving automation systems (DAS) are being rapidly developed by the automotive industry in order to improve driver safety and comfort. To realise the promised benefits, manufacturers must develop design solutions from a human-centric perspective. This thesis seeks to contribute to the systematic development of DAS from a human-centric perspective by shedding light on the driver’s perception and consequent understanding of DAS.

The aspects constituting drivers’ understanding of DAS and the factors influencing their perception of such systems were identified through a series of four empirical studies utilising online surveys, interviews, a naturalistic driving study, and on-road driving observations employing a Wizard-of-Oz approach. As a result, a conceptual model describing how a driver’s perception shapes their understanding of driving automation systems was developed.
Building on this theoretical model, a co-creation study with practitioners in an industrial setting was conducted, aiming to develop the knowledge into an applicable design tool. During the co-creation study, the "Design for perception"-toolkit was developed and evaluated.

The results show that the tool supports practitioners when designing driving automation systems in three ways: 1. exploring viable design solutions using a systematic approach, 2. identifying areas for improvement using the driver’s lens, and 3. generating and evaluating design decisions using a structured process.

Semi-autonomous driving and its effect on mode-awareness and user experience

VINNOVA (2017-01946), 2017-10-02 -- 2021-12-31.

Subject Categories

Production Engineering, Human Work Science and Ergonomics


Human Computer Interaction

Areas of Advance




Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5413



Virtual Development Laboratory (VDL), Campus Johanneberg: Chalmers Tvärgata 4C


Opponent: Greg A. Jamieson, PhD, P.Eng., Professor and Clarice Chalmers Chair of Engineering Design in the Department of Mechanical & Industrial Engineering at the University of Toronto.

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