Promoting Energy Efficient Driving Through a Form of Eco Score Master’s Thesis in Interaction Design and Technologies Diana Boskovic Linn Holmgren Department of Computer Science and Engineering CHALMERS UNIVERSITY OF TECHNOLOGY UNIVERSITY OF GOTHENBURG Gothenburg, Sweden 2025 Master’s thesis 2025 Promoting Energy Efficient Driving Through a Form of Eco Score Diana Boskovic Linn Holmgren Department of Computer Science and Engineering Chalmers University of Technology University of Gothenburg Gothenburg, Sweden 2025 Promoting Energy Efficient Driving Through a Form of Eco Score Diana Boskovic & Linn Holmgren © Diana Boskovic & Linn Holmgren, 2025. Supervisor: Mohammad Obaid, Department of Computer Science and Engineering Advisor: Micaela Nilsson, Volvo Cars Examiner: Staffan Björk, Department of Computer Science and Engineering Master’s Thesis Planning Report 2025 Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg SE-412 96 Gothenburg Telephone +46 31 772 1000 Cover: A visualization of the final design emerged from the results of the project, a Driver Information Monitor of a Battery Electric Vehicle, with an inserted interface depicting an Eco Score as well as ambient lighting surrounding the monitor. Typeset in LATEX Gothenburg, Sweden 2025 iv Abstract The increasing use of Battery Electric Vehicles (BEV) presents opportunities and challenges in promoting energy-efficient driving. This thesis explores how informa- tion about One Pedal Drive (OPD) and throttle usage can be visualized to help drivers better understand and manage their energy consumption. The study takes a user-centered design approach that involved conducting expert interviews and ques- tionnaire study to understand the users. Prototypes displaying eco-driving feedback integrated into the Drivers Information Monitor (DIM) were developed, tested, and refined. The initial design concepts developed according to a defined requirements list, were tested in two focus groups. A semi-functional prototype were developed based on the feedback from the first iteration and tested with 20 participants in a Think-Aloud Protocol study. The findings highlight that dynamic real-time visu- alizations combined with post-drive visualizations can help user gain a better un- derstanding of their energy consumption. Gamified elements such as an Eco Score, social comparisons, and ambient feedback were shown to motivate energy-efficient behaviour. The thesis presents a set of actionable design recommendations for in- car displays that aim to improve user experience, reduce cognitive load, and support sustainable driving habits. These insights contribute to the field of human-vehicle interaction and the development of intuitive interfaces for the next generation of BEVs. Keywords: battery electric vehicle, energy-efficient driving, human-vehicle inter- action, user experience, interaction design, user-centered design, gamification, infor- mation visualization v Acknowledgements We express our sincere gratitude to all who supported us throughout the course of this master’s thesis. First, we thank Dr. Mohammad Obaid, our supervisor at Chalmers University of Technology, for his invaluable guidance, encouragement, and thoughtful feedback throughout the process. Your support helped us stay focused and motivated during both the challenging and rewarding phases of the project. We would also like to extend our heartfelt thanks to Micaela Nilsson, our advisor at Volvo Cars, for her continuous support, coordination, and commitment. Your insights, encouragement, and belief in our work were instrumental in helping us move forward with the project. With your help, nothing was impossible. A special thanks also go to the Vehicle Energy Management team at Volvo Cars who welcomed us with open arms, and to the UX team at Volvo Cars for assistance with the simulation during usability testing. Finally, we are grateful to all the participants who contributed to our research journey by sharing their time, knowledge and feedback. Even if we cannot mention each and everyone of you, know that we cherish the interactions and insights you gave us. Your collaboration was fundamental to the outcome of this thesis. Diana Boskovic & Linn Holmgren, Gothenburg, May 2025 vi Contents List of Figures xi List of Tables xiii Abbreviations xiv 1 Introduction 1 1.1 Problem statement and Research Questions . . . . . . . . . . . . . . 1 1.1.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Delimitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.3 Expected Contributions . . . . . . . . . . . . . . . . . . . . . 3 1.2 Ethical Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Background 5 2.1 Stakeholders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Volvo Cars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2.1 Vehicle Subscriptions . . . . . . . . . . . . . . . . . . . . . . . 6 2.2.2 Working Towards Emission Free Vehicles . . . . . . . . . . . . 7 2.2.3 Design Principles . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.3 Battery Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3.1 Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3.2 Environmental Impact . . . . . . . . . . . . . . . . . . . . . . 9 2.3.3 Information Visualisation in Battery Electric Vehicles . . . . . 9 2.3.3.1 Driver Information Monitor and Center Stack Display 9 2.3.4 Range Anxiety . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.4 Regulations and Policies . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.5 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3 Related Work 15 3.1 Gamification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1.1 Social Networks and Collective Data Sharing . . . . . . . . . . 16 3.2 Energy efficient driving behaviours . . . . . . . . . . . . . . . . . . . 17 3.3 Eco Score . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.4 Cognitive Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4 Theory 21 vii Contents 4.1 Wicked Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.2 User Experience Design . . . . . . . . . . . . . . . . . . . . . . . . . . 21 4.3 Interaction Design Approaches . . . . . . . . . . . . . . . . . . . . . . 22 4.3.1 User-Centred Design . . . . . . . . . . . . . . . . . . . . . . . 23 4.3.2 Research Through Design . . . . . . . . . . . . . . . . . . . . 23 4.4 Human-Vehicle Interaction . . . . . . . . . . . . . . . . . . . . . . . . 24 4.4.1 Cognitive Overload . . . . . . . . . . . . . . . . . . . . . . . . 24 4.5 Gameful Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.6 Information Visualisation . . . . . . . . . . . . . . . . . . . . . . . . . 25 5 Methods 27 5.1 Interaction Design Process . . . . . . . . . . . . . . . . . . . . . . . . 27 5.2 Methods for Discover . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.2.1 Benchmarking . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.2.2 Expert Interview . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.2.3 Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 5.3 Methods for Define . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.3.1 Thematic Analysis . . . . . . . . . . . . . . . . . . . . . . . . 29 5.3.2 Affinity Diagram . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.3.3 Personas and Scenarios . . . . . . . . . . . . . . . . . . . . . . 30 5.3.4 Requirements List . . . . . . . . . . . . . . . . . . . . . . . . 30 5.4 Methods for Develop . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 5.4.1 Brainstorming . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5.4.2 Prototyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 5.4.2.1 Rapid Prototyping . . . . . . . . . . . . . . . . . . . 31 5.4.2.2 Low-Fidelity Prototype . . . . . . . . . . . . . . . . 31 5.4.2.3 High-Fidelity Prototype . . . . . . . . . . . . . . . . 32 5.5 Methods for Deliver . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 5.5.1 Focus Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 5.5.2 Think-Aloud Protocol . . . . . . . . . . . . . . . . . . . . . . 32 5.5.3 Interview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 6 Planning 35 6.1 Gantt Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 7 Execution and Process 37 7.1 Discover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 7.1.1 Benchmarking . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 7.1.1.1 Summary of Benchmarking Result . . . . . . . . . . 39 7.1.2 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . 40 7.1.2.1 Expert Interviews . . . . . . . . . . . . . . . . . . . 40 7.1.2.2 Questionnaire . . . . . . . . . . . . . . . . . . . . . . 40 7.2 Define . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 7.2.1 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 7.2.1.1 Analysis of Expert Interviews . . . . . . . . . . . . . 42 7.2.1.2 Summary of Expert Interview Result . . . . . . . . . 43 7.2.1.3 Analysis of Questionnaire . . . . . . . . . . . . . . . 44 viii Contents 7.2.1.4 Summary of Questionnaire Result . . . . . . . . . . . 44 7.2.2 Requirement Identification . . . . . . . . . . . . . . . . . . . . 46 7.2.2.1 Creating Personas . . . . . . . . . . . . . . . . . . . 46 7.2.2.2 Formulating Scenarios . . . . . . . . . . . . . . . . . 47 7.2.2.3 Establishing Requirements List . . . . . . . . . . . . 47 7.3 Develop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 7.3.1 Iteration 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 7.3.1.1 Development of Low-Fidelity Prototypes . . . . . . . 49 7.3.1.2 Focus Group to Evaluate Low-Fidelity Prototypes . . 50 7.3.1.3 Result Analysis of Iteration 1 . . . . . . . . . . . . . 54 7.3.1.4 Summary of Iteration 1 Result . . . . . . . . . . . . 55 7.3.2 Iteration 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 7.3.2.1 Development of Semi-Functional Prototype . . . . . 56 7.3.2.2 Think-Aloud Protocol to Evaluate Semi-Functional Prototype . . . . . . . . . . . . . . . . . . . . . . . . 58 7.3.2.3 Result Analysis of Iteration 2 . . . . . . . . . . . . . 59 7.3.2.4 Summary of Iteration 2 Result . . . . . . . . . . . . 59 7.4 Deliver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 7.4.1 Establishing Design Recommendations . . . . . . . . . . . . . 60 7.4.2 Development and Evaluation of Final Design: Eco Score . . . 61 8 Results 69 8.1 Establishing the Requirements List . . . . . . . . . . . . . . . . . . . 69 8.1.1 Benchmarking . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 8.1.2 Expert Interviews . . . . . . . . . . . . . . . . . . . . . . . . . 71 8.1.3 Questionnaire . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 8.1.4 Personas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 8.1.5 Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 8.1.6 Requirement List . . . . . . . . . . . . . . . . . . . . . . . . . 80 8.2 Establishing Design Recommendations . . . . . . . . . . . . . . . . . 81 8.2.1 Iteration 1: Focus Groups . . . . . . . . . . . . . . . . . . . . 82 8.2.1.1 Iteration 1 Concept A: Takeaways . . . . . . . . . . 82 8.2.1.2 Iteration 1 Concept B: Takeaways . . . . . . . . . . . 83 8.2.1.3 Iteration 1 Concept C: Takeaways . . . . . . . . . . . 84 8.2.1.4 Iteration 1 Concept D: Takeaways . . . . . . . . . . 85 8.2.1.5 Overarching Takeaways Considering all Concepts . . 86 8.2.2 Iteration 2: Protocol Study Usability Testing . . . . . . . . . . 87 8.2.2.1 U1: Colour as a Communication Tool . . . . . . . . 87 8.2.2.2 U2: Visual Usability . . . . . . . . . . . . . . . . . . 89 8.2.2.3 U3: Making Sense of Eco-Driving Feedback . . . . . 90 8.2.2.4 U4: Cognitive Load and Contextual Sensitivity In Feedback Delivery . . . . . . . . . . . . . . . . . . . 92 8.2.2.5 U5: Learning to Drive Efficiently . . . . . . . . . . . 93 8.2.2.6 U6: Understanding the Eco Score . . . . . . . . . . . 95 8.2.2.7 U7: Motivation through Comparison and Gamification 96 8.2.3 Design Recommendations . . . . . . . . . . . . . . . . . . . . 98 ix Contents 8.2.3.1 Visual and Spatial Presentation of Information . . . 100 8.2.3.2 Promoting the Acquisition of Eco-Driving Habits . . 102 8.2.3.3 Motivating Energy Efficient Behaviour With Game- ful Elements in Driver Information Monitors . . . . . 102 8.3 Final Design: Eco Score . . . . . . . . . . . . . . . . . . . . . . . . . 103 9 Discussion 109 9.1 Work Process and Connected Theories . . . . . . . . . . . . . . . . . 109 9.2 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 9.3 Limitations and Challenges . . . . . . . . . . . . . . . . . . . . . . . 112 9.4 Ethical Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . 113 9.5 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 10 Conclusion 115 Bibliography 117 A Appendix: Expert Interview 1 B Appendix: Questionnaire 5 C Appendix: Focus Group Protocol 13 D Appendix: Think-Aloud Protocol 17 1. x List of Figures 2.1 DIM during driving of a Volvo EX90 . . . . . . . . . . . . . . . . . . 10 2.2 DIM displaying regeneration through the power meter in a Volvo EX90 11 2.3 Range assistant application in the Center Stack Display (CSD) of a Volvo EX90 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 4.1 User Experience (UX) designs overlapping areas of concern [51]. . . . 23 5.1 Double Diamond design process [59] . . . . . . . . . . . . . . . . . . . 27 6.1 Gantt chart illustrating the planned time plan of the project colour coded and divided into phases with tasks from January to March . . 36 6.2 A print screen of a Gantt chart illustrating the time plan process of the project from March to May . . . . . . . . . . . . . . . . . . . . . 36 7.1 visualisation of the Double Diamond Design Framework with all in- cluded processes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 7.2 Key insights from expert interviews displayed in an Affinity Diagram. 42 7.3 Affinity Diagram of overarching themes from expert interviews. . . . . 43 7.4 Affinity diagram of free-text answers from the questionnaire. . . . . . 45 7.5 Prototype of Concept A. . . . . . . . . . . . . . . . . . . . . . . . . . 50 7.6 Prototype of Concept B. . . . . . . . . . . . . . . . . . . . . . . . . . 51 7.7 Prototype of Concept C. . . . . . . . . . . . . . . . . . . . . . . . . . 51 7.8 Prototype of Concept D. . . . . . . . . . . . . . . . . . . . . . . . . . 52 7.9 Examples of locations of poster and brochures distributed. . . . . . . 53 7.10 Focus group setup with participants. . . . . . . . . . . . . . . . . . . 54 7.11 Arduino controller setup with LED strip. . . . . . . . . . . . . . . . . 57 7.12 Example of the ambient light feedback incorporated with the digital prototype. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 7.13 Prototype of welcome screen with previous score. . . . . . . . . . . . 63 7.14 DIM prototype for energy-efficient driving . . . . . . . . . . . . . . . 63 7.15 DIM prototype for energy-efficient driving showing fast acceleration. . 63 7.16 DIM prototype for energy-efficient driving showing harsh braking. . . 63 7.17 Example of pop-up when the driver has gained a leaf to the score. . . 64 7.18 Example of pop-up providing suggestions of improvements to the driver. 64 7.19 Goodbye screen displayed after drive where driver has gained or main- tained their score. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 7.20 Goodbye screen displayed after drive where driver has lost a leaf. . . 64 xi List of Figures 7.21 Two examples from a user test in the UX buck, showing how the ambient lighting behind the DIM changes colour based on driving efficiency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 7.22 Setup of tools used positioned behind the buck. . . . . . . . . . . . . 65 7.23 Facilitator and participant during a user test. . . . . . . . . . . . . . 66 7.24 Affinity diagram of the usability testing for Iteration 2. . . . . . . . . 67 8.1 Persona 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 8.2 Persona 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 8.3 View of the welcoming screen of the DIM, greeting the driver and showing the Eco Score of their latest drive. . . . . . . . . . . . . . . . 104 8.4 View of the DIM during an active drive, showing a message prompt of the driver gaining a leaf when driving energy efficiently. . . . . . . 104 8.5 View of the DIM during an active drive, with an power meter ef- ficiency indicator indicating high acceleration as well as an Eco-tip prompt suggesting the driver to keep even speed. . . . . . . . . . . . 105 8.6 View of the DIM when parked post-drive, an Eco Score summary of the drive is visible with individual scoring, a scoring board featuring other drivers and metrics connected to the efficiency of the recent drive indicating that the drive was efficient. . . . . . . . . . . . . . . 106 8.7 View of the DIM when parked post-drive, an Eco Score summary of the drive is visible with individual scoring, a scoring board featuring other drivers and metrics connected to the efficiency of the recent drive indicating that the drive was inefficient. . . . . . . . . . . . . . 107 B.1 The images demonstrate the different types of screens available in the vehicles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 C.1 Warm-up session presented to participants in focus groups. . . . . . . 13 C.2 Presentation of the two personas in focus groups. . . . . . . . . . . . 14 C.3 Presentation of calm screen, surrounding traffic, and navigation sce- narios in Focus groups. . . . . . . . . . . . . . . . . . . . . . . . . . . 14 C.4 The four presented low-fidelity prototypes in the focus groups . . . . 16 D.1 Setup of the buck and simulation room . . . . . . . . . . . . . . . . . 18 xii List of Tables 7.1 Summary of Requirements . . . . . . . . . . . . . . . . . . . . . . . . 48 7.2 Participants Focus Group 1 . . . . . . . . . . . . . . . . . . . . . . . 53 7.3 Participants Focus Group 2 . . . . . . . . . . . . . . . . . . . . . . . 54 8.1 Requirement List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 8.2 Design Recommendations . . . . . . . . . . . . . . . . . . . . . . . . 98 xiii List of Tables Abbreviations BEV Battery Electric Vehicles. v, xiv, 1–6, 8–10, 12, 13, 15, 18, 20, 21, 28, 38, 40–42, 44, 46, 47, 52, 59, 60, 69–75, 77, 78, 81, 85, 86, 90, 92–94, 96, 98, 101–103, 109–116 CoDev Co Development. xiv, 6, 41, 42 CSD Center Stack Display. xi, xiv, 3, 10, 11, 17, 38, 39, 46, 50, 58, 70, 71, 73, 75, 76, 91, 114 DIM Drivers Information Monitor. v, xiv, 1, 3, 7, 10, 14, 17, 20, 38, 39, 46, 49, 50, 56–58, 61, 70, 71, 73, 75, 76, 80, 82, 84, 87–89, 92, 95, 96, 98–104, 106, 111, 113, 114 DVI Driver-Vehicle Interface. xiv, 10 EDTE Estimated Distance to Empty. xiv, 9, 10 EV Electric Vehicle. xiv, 1, 3, 6–10, 12, 15, 17, 60, 71, 74, 92, 94, 102, 111 GDPR General Data Protection Regulations. xiv, 1, 4, 113 HCI Human-Computer Interaction. xiv, 19, 22, 23 HMI Human-Machine Interaction. xiv, 24 HVI Human-Vehicle Interaction. xiv, 24 ICEV Internal Combustion Engine Vehicles. xiv, 1, 9, 12, 17, 94, 102, 115 MaaS Mobility as a Service. xiv, 6 xiv List of Tables OPD One Pedal Drive. v, xiv, 1, 2, 8, 38, 39, 44, 46, 47, 71, 73, 75, 77, 78, 81, 98–103, 110–112, 115, 116 RtD Research through Design. xiv, 23, 24, 109, 115 SoE State of Energy. xiv, 1, 9, 10, 39 UCD User-Centred Design. xiv, 23, 109 UI User Interface. xiv, 7 UX User Experience. xi, xiv, 7, 21–23, 102, 109 xv List of Tables xvi 1 Introduction Battery Electric Vehicles (BEV) have become increasingly popular and are no longer considered an exclusive luxury but can be an affordable option since production has increased and the market of Electric Vehicle (EV)s has become diverse enough to cater to the general public. Hence, an increasing number of drivers switch from Internal Combustion Engine Vehicles (ICEV)s to EVs and there is a need of inform- ing drivers en masse of how their previously favourable driving behaviour might not benefit their energy consumption. Energy efficient driving patterns could improve consumption patterns, and by that the range of the vehicle. Consumption has be- come increasingly important since the range of EVs, especially BEVs, is smaller than that of ICEVs, and the charging time of vehicles takes longer than filling a fuel tank of petrol. The infrastructure for charging EVs is another challenge, though it is prioritized by several countries and developments are ongoing, EV drivers depend on reliable and accessible charging infrastructure. The importance of driving styles is due to its effects on consumption and its consequences to the State of Energy (SoE) of the vehicle, deterioration of the battery and loss of range which could all result in otherwise avoidable emissions. EVs are considered an innovative solution to moving the transportation industry in a sustainable direction. Because of the global energy crisis and the concern of the impact of the emissions generated by the automotive industry, the development of EVs has rapidly become a global trend as the industry shifts to become electrified. With this, the cars status as a means of transportation has not changed, but the mental model of the cars attributes and affordances has evolved as the EV demands a change of behaviour by the driver. This poses the question if the knowledge of EVs and how to drive them energy efficiently has had a corresponding increase as the use of the vehicles themselves. To communicate how the driving task has changed with the EV, effective interfaces are required to successfully help drivers adapt to the new standard of vehicles. 1.1 Problem statement and Research Questions The transition to BEVs presents a shift toward sustainable transportation, driven by the need to reduce environmental impact. As BEVs become more common, efficient energy management has emerged as a critical factor in enhancing their performance, range, and user satisfaction. However, many drivers need to be made aware of how their driving behaviour, specifically the use of features like One Pedal Drive OPD and the throttle, directly impacts energy consumption. While the awareness of vehicle 1 1. Introduction energy consumption becomes more important, how to behave and manoeuvrer the vehicle in a manner that minimises energy usage might not be as easy to comprehend. This limits the potential efficiency gains of BEVs and the broader adoption of Eco- friendly driving practices. Understanding how to provide actionable feedback to drivers in a way that promotes energy-efficient behaviour while ensuring safety and an engaging user experience requires a multidisciplinary approach. The problem could be addressed by combining insights from behavioural research, user-centred design, and gamification techniques. The research questions that will be investigated in the thesis are: 1. What information about One Pedal Drive (OPD) and throttle usage helps Battery Electric Vehicle (BEV) drivers understand their energy consumption? 2. What are the design recommendations for displaying information to promote energy-efficient driving? 1.1.1 Purpose The purpose of the thesis is to investigate what information of energy consumption should and could be displayed to drivers whilst driving to provide either actionable or educational information. To gain understanding of this, the focus will lie on first understanding the user and their perspective, since usability and user experience is a central part of the research. Another focus is to understand the role that gamified feedback might play in information visualisation of energy consumption and if this could enhance the user’s understanding of their driving behaviour affecting their energy consumption. To concretise the findings of the research, the aim is to develop several design recommendations for displaying actionable feedback to drivers about their BEV energy usage intuitively to reduce cognitive overload. With these intentions, the purpose is to develop low-fidelity and semi-functional prototypes with which the usefulness, usability and actionability of the proposed solutions can be tested with BEV users. 1.1.2 Delimitations The information visualisation of in-car displays for BEVs is a relatively new area of research, because of this there is a limited amount of research on the subject. Because of the ongoing rapid development in the field, with new models of cars being brought out every year, the standard for interfaces in BEVs is evolving together with the market. This offers an opportunity for this research to bring fresh insights into the field. The goal is to understand what information should be displayed to users driving BEVs for them to understand the correlation between their own driving behaviours and the energy usage of the vehicle. Because of this and the limited previous research on the topic, the research will have a user-centred approach. Another aspect of the research is to investigate what gamified feedback could be used in in-car displays to display energy usage and how these could potentially effect energy usage. The field of gameful interfaces in cars is new and the information 2 1. Introduction available is limited, adding an exploratory approach to understanding the value of gamified feedback in vehicles. The research is limited to in-car displays, specifically the Drivers Information Moni- tor DIM. Other displays, such as the CSD or mobile applications will not be a part of the scope of this thesis. This is to narrow the scope and the interest of using information visualisation techniques in a limited amount of actionable space, such as in the DIM, which is regulated by law and corporate design language. The scope of the thesis will only include BEVs, an no other EVs will be taken into considera- tions even though they might share the same challenges and might benefit from the results of this research. The participants in the studies will be BEV drivers employed by Volvo Cars. Adding consistency to our methodology, the participants are assured to be stakeholders. However, the findings of the study can not be guaranteed to apply to a broader range of BEV drivers without further investigation beyond the scope of this project. The participants will be recruited to represent a wide range of education, age, gen- der and area of work. This will offer insights from different perspectives. Because of their shared attribute of having the same employer, the findings might not re- flect the general public. The study is conducted in Gothenburg, Sweden, with the participants living in the same area. This makes the findings based on a limited demographic, which might not be representative for the global populations because of cultural differences, climate and social factors. 1.1.3 Expected Contributions The research is expected to contribute to the field of research of BEVs, as well as information visualization in in-car displays and of gameful design in cars. The findings of the research will be represented in several design recommendations according to the scope of the project. These are expected to answer the research questions and guide future iterations of in-car displays in design challenges. 1.2 Ethical Considerations The nature of the environment which will be investigated immediately offers eth- ical concerns which need to be taken into account. Because of the focus on user experience whilst actively driving, and the scope including actionable feedback, the safety of the user is a priority. When addressing information visualisation in in-car displays, the designs need to be made to avoid information overload and potentially distracting the user. Since the research has a user-centred approach, decisions of the design will me made so to not overwhelm or distract the user, as well as not demanding their attention whilst driving. Whilst aiming to understand the user and the impact of energy consumption dis- played to them, knowledge of the correlation between driving behaviour and energy consumption should not lead to stress or anxiety. The research is meant to empower 3 1. Introduction users driving BEVs by informing them of how they can actively have an impact on energy consumption by their daily choices. The proposed solutions will be developed to include aspects of accessibility, and the designs will be constructed as to not exclude colour-blind individuals. All research will be conducted according to the General Data Protection Regulations (GDPR), implying that data privacy and security is prioritised. All data will be handled to assure privacy, no sensitive information will be asked of the participants of the questionnaires, interviews, focus groups or think aloud protocol studies and all data will be made anonymous after processing. 4 2 Background The context needed to understand the research questions and the problem statement introduced in Chapter 1 will be presented in this chapter. The stakeholders will be introduced, together with the topics of BEVs and their vehicle specific attributes, as well as data visualisation in the context of BEVs. Sustainability, energy-efficient driving, and gameful design will be addressed to shed light on the context specific areas of interest for the thesis. Regulations regarding in-car displays will be put into context to provide information necessary to understand the scope of development for the design recommendations proposed. 2.1 Stakeholders The expected outcomes of this research is of relevance to three main groups of stake- holders. Volvo Cars, which are expected to benefit from the design recommendations which might be further implemented in future developments of information visual- isation of energy consumption, will provide vital input, expertise and resources to aid the process of the project. The drivers play a central role in the discovery and development phase of the project, and user insights gathered during the evaluations will further drive the development of the final prototype and the design recommen- dations. 1. Drivers: drivers of BEV will participate in the different stages of the process. The final proposed design solutions will aim to help drivers drive more energy- efficient, which they can benefit from economically whilst positively impacting the environment. 2. Environment: the global transport industry has had a negative impact on the environment, not only by adding to rising CO2 levels. By electrifying vehicles and choosing a future sustainable way of transportation that could minimise those emissions. 3. Automotive industry: the industry has drastically shifted into prioritising the development of BEVs to face current and foreseeable challenges, imple- mentation of new innovative technology is happening continuously and having informative interfaces to guide drivers into changing their driving habits would help setting a new standard of driving energy efficient vehicles. This would affect manufacturers, designers and the industry as a whole. 5 2. Background 4. Bystanders: if the design recommendations were to be implemented and influence future versions of BEV interfaces, there might be a long-term impact on bystanders perspective of BEVs and perhaps their future driving style and demands on BEVs. 2.2 Volvo Cars Volvo Cars is a multinational company based in their hometown of Gothenburg, Sweden. Their core values are safety, quality and care for the environment. With this, they aim to be leading in the automotive industry in safety technology, electri- fication and autonomous driving [1]. Their long-term plan for the production of cars align with their values, as Volvo Cars’ goal is to become a fully electrified company, with the aim of reaching 65-70% CO2 reduction per vehicle by 2030 [2]. To add to this expansion into the manufacturing of fully electrified vehicles, they aim to release an EV annually. Due the substantial international recognition of the brand Volvo Cars, their commitment to adapt sustainability policies and their open concern for the future of the environment, their progress in developing BEVs is noticed and has already had an impact on vehicles in use by cross-national customers. 2.2.1 Vehicle Subscriptions With the rising awareness of negative social, environmental and economical factors of private vehicle travel and ownership, the demand for alternative solutions has been identified [3]. In countries with poorly developed public transportation systems, res- idents depend on having access to a private vehicle. The dependency contributes to climate changes and environmental damage, it affects infrastructure and pollution. An alternative ownership is Mobility as a Service (MaaS). The automotive industry has managed to shift the way consumers view mobility by introducing user-ship instead of ownership, in line with the concept of MaaS which includes alternatives such as car subscriptions and sharing [4]. These solutions offer flexibility, adaptabil- ity, and convenience to the consumer, compared with leasing or private ownership. As for environmental impacts, car subscription solutions could increase resource effi- ciency since the car is with the customer for a shorter period of time, and is returned at the end of the contract. The owner can then keep the car on the market if the cus- tomer chooses to end their subscription or change models, resulting in a decrease in the need to manufacture or acquire new vehicles [5]. Consequently, the rising trend of car subscriptions has lead to encouragement of responsible resource utilization. Volvo Cars has their own car subscription services, one of which is an exclusive offer to employees. A part of the service is to offer participation in their Co Development (CoDev) fleet, which means choosing a car with test equipment and commitments made by the driver. This offer is beneficial both for the employee and the company, as the contract is an opportunity for Volvo to gain valuable insights of their products, which can be used for improvements. The commitments includes active participation by the drivers in surveys and interviews, making CoDev BEV drivers ideal candidates for the research conducted in this project. CoDev drivers will be asked to participate 6 2. Background in the different evaluative methods used in the research. By offering the use of their own resources within the company, Volvo Cars have been of great help in finding participants of relevance for our user studies. 2.2.2 Working Towards Emission Free Vehicles Volvo Cars has adopted a sustainability plan meant to have their sales consist of 90-100% EVs, with a reservation of a limited number of hybrid vehicles. With five fully electric cars already on the market, and another five in development, the car company has already established their presence on the EV market. The company had an increase in sales of EV of 70% in 2023, equivalent to 16% of their global sales [6]. Of the five fully electric models EX40, EC40, EX30, EM90 and EX90, the EX30 was during the last quarter of 2024 ranked third of the best selling EV in Europe [7]. Whilst still producing hybrid vehicles, the whole electrification of the company stands as the long-term goal, the current EVs on the market and those in develop- ment being meant to pave the way for the future of the company’s manufacturing and investment plan. Together with their own fleet of EV, Volvo Cars collaborates with Polestar, a Swedish EV brand founded by Volvo which now operates separately. The two companies are partners across manufacturing, research and development [8], collaborating intimately because of their history. This partnership acts as a valuable asset for the development of future EVs. 2.2.3 Design Principles Volvo Cars has internal design guidelines used by User Experience (UX) and User Interface (UI) designers to ensure that all interfaces share the same design language. To further anchor this vision into all vehicles and updates in Volvo Cars’ systems, design values are set to guide the designers. As thesis workers, we have been given access to these principles together with wireframes and modules used in the interfaces of cars today compiled in Figma files [9]. Files containing up-to date DIM interfaces were used to create low and high-fidelity prototypes, to create realistic artefacts to use in the process of the project. The intention with adopting the already used design language of the corporation is to utilise recognisable as well as established standards of orientation with which proposed design solutions will blend into, within the restraints of existing regulatory frameworks. Summary of principles relevant to our design process: • Information should be displayed in a safe way which does not distract users from their immediate surroundings whilst driving • Access to information should be predictable, users should not experience con- fusion • The design should be accessible and inclusive • Incentives to resort into phone usage should be eliminated • Layouts should be simple and glanceable 7 2. Background • Colour is a mean used to communicate, and should be discrete unless the value of the information demands otherwise • Affordances should be indicated clearly, size and colour contrasting should be utilised accordingly 2.3 Battery Electric Vehicles A BEV is an EV with an electric engine and system solely consuming energy from rechargeable battery packs for propulsion BEV which need to be plugged into an energy outlet to charge [10]. Compared to the more general term EV, which also includes hybrid electric vehicles utilising fossil fuels such as gasoline or diesel, BEV have power as their exclusive source of energy. The idea of the BEV has long been around, and has become an increasingly popular alternative in the midst of the global climate crisis together with expanding fuel costs. Advancements in battery technology to battle battery degradation and infrastructure for charging are mak- ing BEV a viable option for drivers worldwide. Lithium-ion batteries have further opened up opportunities for development because of their force capacity generat- ing longer range, advancements in the field are essential for making BEVs more sustainable [11]. 2.3.1 Features A feature unique to BEVs is the ability to harness energy by charging the battery whilst the brakes are applied, resulting in regenerative breaking. This is integrated in most BEVs and works by converting energy during deceleration manoeuvres. Energy that would otherwise have gone to waste can by this be renewed and saved in the battery, making BEVs energy efficient. With this attribute, drivers have significant influence over the vehicles use of energy, as inefficient use of generative breaking can result in a loss of 30% in the energy efficiency of the vehicle [12]. Although this feature is of importance to increase the energy efficiency and by that the range of the vehicle, recuperated energy could be limited by additional friction braking whilst already decelerating. To counter this and offer a comfortable solution to drivers, OPD has been implemented and is now a feature found in most BEVs. Applying the feature allows for acceleration and deceleration with the throttle alone, reserving the brake pedal for emergency breaking. OPD could lead to more energy efficient driving since the algorithm is designed to utilise regenerative breaking to a certain level [13]. However, with easier access to control the acceleration and braking of the vehicle with one pedal, this mechanism could result in easier practice of non-efficient driving because of the easy access to implementing non-smooth driving behaviour because of the use of a single pedal. Releasing the pedal will instantly result in braking, which might not always be beneficial. Most drivers quickly adapt to using OPD, increasing trust into regenerative breaking systems [14]. The affordance diminishes the need to frequently shift between pedals, resulting in increased speed control flexibility. 8 2. Background 2.3.2 Environmental Impact Increasing climate challenges has notified the public of the emissions generated by the global transportation sector, as the industry accounted for 24% of global green- house gas emissions stemming from fuel combustion in 2017, of these emissions 74% are due to road transport [15]. To manage this, numerous cities and countries are committing to eliminating ICEVs in favour of BEVs. With increasing global sales, 14 million cars being 18% of all cars sold in 2023, it is projected that one in two cars sold in 2035 will be an EV [16]. This is in part due to increased support for energy, climate and industrial policies. Another incitement for scaling up produc- tion of EVs are zero-emission zones implemented in many European cities, where restricted or no access is granted for ICEVs [17]. Along with decreasing green house gas emissions, EVs could have an impact on air and noise pollution. In the pursuits of pivoting the global transportation system into a more sustainable counterpart, electrification of passenger vehicles is regarded as a key strategy. 2.3.3 Information Visualisation in Battery Electric Vehicles Even though sales of EVs have been significantly increasing for years, the concepts displayed through in-car displays may not be considered familiar to the general popu- lation. In a study conducted by Chalmers University [18], participants were deemed to have problems understanding information specific to EVs whilst expecting the vehicle they were operating to behave like an ICEV when faced with a traditional interface and experienced insecurities handling innovative interfaces. The results indicated that drivers were unsure of what information is relevant to them as EV drivers, they also did not show full understanding of aspects of importance, indicat- ing a need for better information display. The reason for the confusion might be lack of knowledge concerning electricity and batteries, having useful mental models of these was deemed of critical importance to understand the vehicle and its be- haviour. BEVs introduce new and sometimes unfamiliar technologies to users, such as regenerative breaking, one pedal driving, limited range, charging optimisation, battery degradation and driving style consequences to range. Other research of BEV drivers has revealed the user need of improved information display, stressing the importance of additional information particularly for energy consumption and efficiency [19] [20]. 2.3.3.1 Driver Information Monitor and Center Stack Display Since they rely solely on power, the information visualization of BEV in-car displays needs to contain the SoE, the amount of energy stored, as well as the Estimated Distance to Empty (EDTE), the approximate calculation of possible mileage you can drive until charging is required, in the vehicles. A study conducted by Volvo Cars found that the participants, employees leasing EVs, did not actively feel concern of the SoE or caring for it [21]. Despite the relaxed attitude to the meaning of SoE, the participants stated an interest of having more information of possible battery protection and preventative actions to preserve SoE. Another finding of the study was the preference of having the State of Health displayed together with other car 9 2. Background status notifications. An example of SoE and EDTE status and their location in the DIM of a BEV can be seen in figure 2.1. BEVs, like other automotive vehicles, are built with indicators and instruments in the instrument cluster behind the steering wheel, referenced to as the DIM in this thesis, as well as in the console centred in the build, referenced to as the CSD. Examples of these are portrayed in figure 2.1 and figure 2.3 respectively. These are the Driver-Vehicle Interface (DVI) available to the driver during the activity of driving, whilst it is becoming increasingly usual to have mobile apps available on separate personal appliances to access real-time updated information of the vehicle. Figure 2.1: DIM during driving of a Volvo EX90 Although the cluster of information displayed in the DVI is not limited to what amount of information is allowed to be displayed, a cluttered display filled with unnecessary information or non-beneficial visualisations could lead to confusion in finding and categorising information and might cause a strain on attention, causing the driver to cast long glances on the DIM or CSD [22]. Distractions from the driving task could cause errors in reading comprehension. Hence, specific indicators or instruments should not be too complex in their construction for the user to grasp the content, the visualisations should not be changing too fast and size and contrast need to be considered [23]. The time needed of the driver to divert their attention from their task of driving to read and comprehend the information should be minimal. In figure 2.2, part of the DIM is visible. The image depicts the SoE of the battery in the vehicle at 29%, the EDTE at 120 km and the power meter, a vertical bar showing an orange limitation of the BEV’s power capacity at the instant, in this case possibly because of climate conditions, and a green bar in the lower halve, notifying the driver of an ongoing regeneration of energy. The power meter is associated with EVs, and can be visualized in different ways, often being in the form of a bar or in the more recognizable classic speedometer aesthetic. The power meter gives real-time feedback of power used and occurring regeneration whilst accelerating or practising deceleration or harsh breaking manoeuvres. Some interfaces display the limit of recouperation. Seen in Figure 2.3 is an image of the Range and Trip information in a CSD. The con- tent of the information regarding energy consumption differs between manufacturers 10 2. Background Figure 2.2: DIM displaying regeneration through the power meter in a Volvo EX90 Figure 2.3: Range assistant application in the CSD of a Volvo EX90 and generations of vehicles, some of which only have the general trip information such as in the trip computer, where information of fuel or energy usage and total distances are displayed. The range and trip information acts as a complement to this information. In this example, the driver sees their energy consumption visu- alised with visual elements indicating energy usage to see what activity affected their consumption most, with the opportunity of comparing the specific drive to historic data. 2.3.4 Range Anxiety Estimations of limitations to energy or battery capacity is something encountered by most individuals daily in phones or computers, and our following actions are dependent on the information displayed. Estimations of battery life is indicated by miles or kilometres in cars, often higher than it should be, this creates unrealistic user expectations [19]. As it is difficult to display power accurately, especially for 11 2. Background a remaining drive which is a dynamic activity where the power used is not entirely predictable, users being signalled accuracy of those metrics has consequences. Un- certainty of the state of charge during a drive can bring an element of surprise when the user comes to the realisation that the range of the vehicles current battery power might not be enough for them, either because of time or accessibility of charging infrastructure. This can cause distress, which could lead to increased risk taking and careless driving behaviour. This phenomenon relating to limited range is called range anxiety. Drivers have been shown to create strategies to handle range anxiety, adapting to the behaviour of their EV and by this decrease the amount of incidents with critical range [24]. To give perspective a sense of awareness of the situation, estimation of range, state of charge, the power meter and informing of charging opportunities are useful tools that might give the driver knowledge on how to act in relation to the range, and could have a positive effect on range anxiety. A field study made with EV drivers about interaction with limited mobility resources showed that drivers comfortably used up to 80% of available range of energy without issues of anxiousness [25]. Traits such as low impulsivity and beliefs of control correlated positively to range values and utilisation, suggesting that drivers utilise range preserving strategies and personal traits and competence have a role in specific user-cases of range utilisation. 2.4 Regulations and Policies This section will touch on regulations concerning EVs, however they share the same demands on uniformity and clarity as ICEVs on identification of indicators, hand- controls and tell-tale signs [26] as well as for devices allowing indirect vision, such as mirrors and cameras, and their installation [27]. The European Union are aiming to decrease emission caused by the transportation sector by 90% by the year 2050 compared to 1990 [28]. They declare that it is essential for this change that trans- portation vehicles makes a shift towards using low-carbon fuels, including electricity as the most efficient power source. To enable this dramatic change of fuel use, in- frastructure for charging needs to be improved and made accessible to EV drivers, the objective of the policy is to have EV charging be as accessible, quick and simple as that of a fuel tank. 2.5 Recommendations Battery Electric Vehicles (BEV) introduce new information demands that differ from those of conventional Internal Combustion Engine Vehicles (ICEV) . Neumann and Krems [29] examined how specific BEV displays affect driver understanding and vehicle interaction. The study showed that although drivers initially found dis- plays moderately helpful for estimating energy-related metrics, their perceived use- fulness declined over time. One issue was the difficulty in interpreting electrical units such as kWh, range, and consumption rates, which are unfamiliar to many drivers. These findings suggest that traditional approaches to in-vehicle information design 12 2. Background are insufficient for BEVs. To effectively support energy-efficient driving, interfaces should both present accurate data and translate complex electrical information into intuitive, understandable formats. The recommendations includes adopting clear, user-centered design principles and introducing additional assistive cues that help drivers relate their actions such as acceleration or regenerative braking to real-time energy consequences. Improving display clarity and relevance is therefore crucial for promoting energy efficient driving behaviour in BEVs. 13 2. Background 14 3 Related Work This chapter will introduce and assess works related to this project. Since the scope concern driving behaviour and its effects on energy consumption, how information should be displayed and visualised to drivers for them to fully comprehend their effect on their BEV and how gamified elements could be used enhance understanding, several fields of science and design will be introduced. In line with the second research question of this project, developing design recom- mendations for display of information with the purpose of promoting energy-efficient driving is the goal. Pongchancha et al. [30] similarly did a user-centred study on user needs regarding information display in BEV to enhance understanding of battery State of Energy, with recommendations of efficiently communicating BEV-specific energy to drivers. This study adds to the scarce research on user-perspectives of Sate of Health and other BEV topics which are now becoming increasingly important due to global initiatives, thereby expanding the market, prominence and private use of EVs. 3.1 Gamification Gameful design, commonly known as gamification, is applied in the automotive in- dustry. Diewald et al. [31] reviewed existing and future use of game design, and discussed challenges with integration of game mechanics into automotive contexts. There is a distinction between external and in-vehicle applications of gameful de- sign. Externally, gamification is used in marketing strategies to enhance brand engagement and customer loyalty. Automotive companies have utilised game me- chanics in campaigns, mobile apps, and reward systems to motivate customer in- teraction [31]. Within vehicles, gameful design is primarily focused on promoting safer and more efficient driving behaviours. However, one main application is Eco- driving where drivers receive real-time feedback, points, or rewards for maintaining fuel-efficient and environmentally friendly driving styles. Navigation systems and driver-assistance technologies also integrate game elements, such as challenge-based route optimisation or rewards for maintaining good driving patterns. There are still significant challenges in applying gamification to driving. The main concern is driver distraction since poorly designed game elements could compromise safety by drawing attention away from the road. Additionally, the effectiveness of gameful interventions varies depending on user motivation, cultural differences, and driving 15 3. Related Work habits. It is important to design balanced and non-intrusive game mechanics that enhance driving experiences without introducing new risks [31]. Wee and Choong [32]further explored how different gamification elements could mo- tivate drivers to engage in energy efficient behaviours. Their research was grounded in Self-Determination Theory, which suggests that motivation is driven by three psychological needs namely autonomy, competence, relatedness, and intrinsic mo- tivation. Nine core game design elements were identified as effective in satisfying psychological needs and fostering engagement. The suggested elements for gamified energy-saving were as follow: • Personal Profile • Non-fixed Structure • Challenge • Feedback • Theme • Short Cycle Time • Competition • Cooperation • Chat-based Social Networking These elements provided users with a sense of control, opportunities to develop skills and track progress, and social connections through challenges and shared goals [32]. Implementation of gamified elements into in-car displays need to not distract the driver by attention-seeking visualisations and too dynamic visual changes of the interface. Interfaces should be simple and promote natural interactions to avoid distraction. In an attempt to achieve this, Rodríguez et al. [33] proposed a gamified ambient in-car display solution, where drivers are challenged to drive safely by com- peting with their social network. The proposed technology would provide ambient feedback to drivers when following or breaking traffic laws, with a connected mobile application where scores can be compared to others and rewards can be collected in an attempt to motivate and modify driving behaviours. 3.1.1 Social Networks and Collective Data Sharing Driving in traffic is an inherently social activity, Riener and Reder [34] explored how collaborative data sharing can improve driving efficiency and road safety. Ex- perienced drivers can support less experienced drivers by sharing driving data and creating a collective intelligence network that benefits all drivers. They developed a social driving application that provides drivers with real-time recommendations for navigating a specific route. This system uses data from multiple vehicles for analysing driving patterns, traffic conditions, and environmental factors to gener- ate personalised suggestions that promote safer driving. The application aimed to 16 3. Related Work reduce traffic congestion, optimise fuel consumption, and minimise accident risks through collaboration. Data-driven feedback systems could be used to change indi- vidual driving habits while contributing to broader traffic improvements. However, there are challenges regarding data privacy and user acceptance to support data sharing at scale [34]. Meeco [35] is another digital platform that was designed to promote environmen- tally friendly behaviours through gamification and social networking. According to Macias et al. [35], sustainable habits can be more effective when integrated into an engaging and interactive digital environment. The platform used location-based services and web technologies to allow users to log their ecological actions and share them within a social network. It motivated users to adopt greener behaviours while fostering a sense of community by incorporating game mechanics such as rewards, challenges, and leader boards. The social aspect reinforces participation as users can track each others progress and compete in sustainability challenges. Gamification can therefore act as a tool to drive behavioural change by making sustainability an enjoyable and socially rewarding experience. Still, the implementation proposed challenges such as maintaining user engagement, ensuring the credibility of logged activities, and addressing privacy concerns in location-based tracking [35]. In our research, we aim to explore collective data sharing as a way to motivate users as a form of feedback to change their driving style based how well they drive compared to other drivers of the same vehicle. 3.2 Energy efficient driving behaviours What effects environmentally friendly behaviours is complex factors that conflict with each other and influence our daily decision making, which also applies to en- vironmentally friendly behaviours [36]. What could be considered contributing to environmentally friendly behaviour is environmental knowledge, attitudes, and val- ues. These are shaped by internal and external elements, where social and cultural factors can be included. A contributor to not embracing environmentally friendly behaviour in daily life is old habits, which can act as a barrier to adopting new behavioural patterns. Sympathy and a sense of personal control has ben shown to correlate with environmentally friendly behaviour patterns, where individuals feel- ing personal control in solving environmental issues could improve environmental ethics [37]. This implies that a focus on the individual and internal factors might affect their sense of environmental responsibilities. The driving styles of ICEVs and EVs are not interchangeable, studying the first months of driving EVs compared with ICEVs show that drivers new to the tech- nology have stronger acceleration and deceleration patterns, possibly due to EVs allowing high acceleration indifferent to the engines revolution per minute [38]. The distinct technological features of an EV make for a unique experience which is likely reflected in driving behaviour. Aggressive driving styles such as harsh brakage, fre- quent acceleration and high speeds could result in 30% higher energy consumption [39]. Nudging tactics used in car interfaces to improve driving behaviour is becoming more prevalent, settings labelled with the words Eco, green, sustainable, or efficient 17 3. Related Work modify driver settings such as climate control and power usage. Whilst these tactics prove useful for a while, that effect fades over time, failing in creating lasting driving habits. Additionally, in a study by Günther et al. [40], Eco-driving behaviours in the context of BEVs were examined to identify strategies that optimise energy consumption and range while maintaining safe and efficient driving practices. Both objective driving performance metrics and subjective driver perceptions were analysed by integrating multiple data sources. Eco-driving behaviours such as acceleration and braking, anticipation of traffic flow, and efficient use of regenerative braking were central. The findings were that drivers can influence the energy efficiency of BEVs through their driving style. However, individual differences in user behaviour, motivation, and experience affect the adoption of Eco-driving strategies [40]. 3.3 Eco Score There are several studies of Eco Score implementation aiming to explore ways to change driving behaviours to be more energy efficient. Stillwater and Kurani [41] explores how in-vehicle feedback influences drivers to adopt more energy-efficient driving behaviours and investigates whether goal setting, framing, and anchoring within feedback systems could motivate do so. Findings from their study indicated that roughly 75% of drivers modified their driving behaviour in response to the feed- back. The study also found that different types of feedback influenced behaviour in different ways. Real-time feedback was especially useful for experimentation since it allow drivers to test and refine new driving strategies while historical performance feedback was more effective for setting goals and maintaining motivation. Partici- pants were more likely to adopt new Eco-driving techniques when they had a clear efficiency goal, and framing the feedback in a game-like manner made it more en- gaging. When drivers were provided with a baseline comparison or anchoring, such as the average fuel efficiency of other drivers, they gained a better understanding of their performance and adjusted their behaviour to align with that standard [41]. Franke et al. [42] further explored the possibilities of improving energy efficiency and driver experience in BEV. Effective energy interfaces need to integrate technical and psychological perspectives to support drivers in optimising energy consumption while reduce concerns such as range anxiety [42] [24]. Factors influencing energy interface design include the dynamics of vehicle energy use, driver cognition, and behavioural strategies. Current energy feedback systems in electric vehicles often fail to provide intuitive, actionable feedback that could lead to inefficient driving behaviours and increased range anxiety. To address these challenges, Franke et al. [42] propose a conceptual framework that considers three main aspects technical energy dynamics, driver perception and decision-making, and system usability. They suggest that energy interfaces should offer predictive, and context aware information that helps drivers anticipate and manage energy use effectively. Another study conducted by Hibberd et al. [43] also investigated the effectiveness of in-vehicle interfaces to promote environmentally friendly driving. It was conducted 18 3. Related Work using a high-fidelity driving simulator to evaluate potential Eco-driving interfaces, including visual dashboard displays, multimodal combinations of visual and auditory feedback, and haptic feedback through the accelerator pedal. The goal was to deter- mine which of the interface modalities most effectively guided drivers toward optimal accelerator pedal use and consequently improve fuel efficiency. Interfaces providing real-time and intuitive feedback can significantly improve Eco-driving performance. The feedback combining visual and auditory cues were particularly effective. Haptic feedback through the accelerator pedal also showed potential through subjective im- pressions [43]. These insights are valuable for the development of in-vehicle systems and interfaces aiming to support environmentally friendly driving. 3.4 Cognitive Aspects The concept of nudging suggest that it is possible to leverage the knowledge about cognitive biases to influence behaviour in a positive way. Researchers have adopted the idea of nudging to promote healthy behaviours in the field of Human-Computer Interaction (HCI). Caraban et al. [44] created "The Nudge Deck" to assist designers in creating effective technology-mediated nudging. They develop the cards as a tool to navigate the unstructured theoretical knowledge about nudging and make the information more actionable during the design process. The deck of cards consisted of 32 cards categorized into three types: Trigger Cards, Mechanism Cards, and Category Cards. Trigger Cards help identifying the ap- propriate moments to implement a nudge, Mechanism Cards feature 23 different nudging mechanisms that provide insights into strategies that can influence user behaviour, Category Cards assist in organising and selecting nudges based on spe- cific behavioural objectives. Examples of nudging mechanisms for social influences includes leveraging social commitment, raising the visibility of users’ actions, and en- abling social comparison. The mechanisms for reinforcement includes just-in-time prompts, ambient feedback, and subliminal priming. Mechanisms to facilitate in- cludes default options and opt-out policies while mechanisms to confront includes throttling mindless activity and providing multiple view points. The findings of the evaluation indicated that the Nudge Deck significantly enhances designersťefficiency. It help to bridge the gap between complex theoretical concepts and practical appli- cations [44]. A second cognitive phenomenon, flow, has been researched in a variety of fields, such as gaming, productivity, and creativity. It is defined as the ideal psychological state of profound immersion and enjoyment in an activity. Blanchard et al. [45] presented the "Flow Engine Framework" that describes the dynamic relationships between flow-related elements and cognitive processes. The Input-Process-Output model is the foundation of the framework and is similar to an engine in which flow is produced and maintained by key components. The terms inputs refer to the prerequisites for flow, which include objectives, immediate feedback, and a balance between skill level and challenge. Processes describe the cognitive mechanisms that regulate and sustain flow, including attentional focus, motivation, and the combi- nation of action and awareness. Outputs represent the outcomes of flow, such as 19 3. Related Work enjoyment, improved performance, and productivity. The framework are suggested to be applied in various fields, including game design where fostering engagement and productivity is essential [45]. To the best of our knowledge, previous research on BEVs did not addressed how gameful and real-time feedback systems, designed with a user-centred and cognitive aware approach, can be integrated into the DIM to support energy-efficient driving. While studies have explored Eco-driving behaviours, energy interfaces, and gamifi- cation individually, few have combined these domains in the context of in-vehicle feedback related to BEV-specific characteristics such as regenerative braking and throttle sensitivity. Moreover, most existing solutions overlook the interactions be- tween behavioural motivation and long-term habits related to interface design. This gap has motivated us to investigate how gamified feedback grounded in cognitive principles and supported by real user input can be used to enhance driver under- standing and promote sustainable driving practices in BEVs. 20 4 Theory This chapter provides the theoretical foundation for the research by presenting sig- nificant frameworks and concepts relevant to the study. It covers topics such as Wicked Problems, User Experience Design, Interaction Design Approaches, Human- Vehicle Interaction, and Information Visualisation, as well as gameful design and cognitive theories. These perspectives inform the planning and design strategies used to address the challenges in this project. 4.1 Wicked Problems Complex problems in social settings are often referred to as picked problems. These issues are recognised because they evolve and change as attempts are made to solve them, resulting in no clear initial definition. The understanding of these problems shifts as solutions are suggested and tested. This makes addressing wicked problems a non-linear process as problem-solving and understanding occurs simultaneously [46]. Rittel & Webber also state that solutions to wicked problems are not right or wrong. Instead, they are evaluated as better or worse, or sufficient or insufficient [46]. Richard Buchanan further highlights that design thinking plays a crucial role in structuring and framing wicked problems allowing innovative approaches that integrate multiple perspectives and evolving conditions [47]. In this research, our goal is to provide a set of recommendations for a new design concept of an interface solution in BEVs to promote energy-efficient driving through a form of Eco Score. Due to its complexity, this challenge is considered a wicked problem with no straightforward solution. Various factors can influence the issue such as user behaviour, location, environmental responsibility and evolving technol- ogy of interfaces and computer models. The problem may have multiple solutions, and the aim of the research is to identify a feasible and optimal solution. Addition- ally, the iterative nature of wicked problems is particularly relevant as each stage of the process maybe leads to new insights. The solution will be assessed based on the clarity and usability it provides to the user. 4.2 User Experience Design UX entail all aspects of the end-userťs interaction with a company, services, and products. It is a dynamic and context-dependent subjective account of human- 21 4. Theory technology interaction. The field of Human-Computer Interaction HCI has evolved to include an experiential perspective that focuses on the emotional and affective aspects of technology use [48]. Mirnig et al. [49] provides a formal analysis of the International Organization for Standardization (ISO) 9241-210 definition of UX. The official ISO 9241-210 standard defines UX as "A persons perceptions and responses that result from the use and/or anticipated use of a product, system, or service". The Interaction Design Foundation [50] outlines seven factors that influence UX design to help designers understand what shapes a user’s perception and interaction with a product or system. According to the Interaction Design Foundation [50], the factors that influence UX and what it should facilitate are: • Useful: The product or system must meet user needs and provide value. Users will not engage with a product if it does not solve a problem or improve a situation. • Usable: The the product or system should be easy to learn, efficient to use, and be error-resistant. A usable product reduces frustration and increases satisfaction. • Findable: Users should be able to easily locate information or navigate the interface without confusion. • Credible: Users must trust the product. Credibility is built through reliabil- ity and transparency. • Desirable: A product should create emotional engagement through appealing visuals and interactions. • Accessible: The design should be inclusive and usable by people with differ- ent abilities. This includes considerations like contrast and alternative input methods. • Valuable: The product must provide value to both users and businesses. It should align with user goals while meeting business objectives. These seven factors interact to create a holistic UX. Designers should aim for a balance among these elements to optimise user satisfaction [50]. UX is a broad term for several design disciplines that is used to create useful, usable, and desirable designs. Cooper et al. [51] emphasises the interconnection of three overlapping areas of concern in UX form, behaviour, and content as seen in figure 4.1. 4.3 Interaction Design Approaches Interaction design is an area that focus on discovering requirements for the product, designing to meet requirements, and producing prototypes to evaluate. The field refers to designing interactive products to support the way humans communicate in their everyday life, and the users and their goals should be consistently considered. It is about creating user experiences that enhance the way people work, communicate, 22 4. Theory Figure 4.1: UX designs overlapping areas of concern [51]. and interact. Typically, interaction design refers to the field that includes a variety of different theories, frameworks, approaches, methods, and guidelines that designers can apply to deliver appropriate UX [48]. 4.3.1 User-Centred Design One fundamental approach in interaction design is User-Centred Design (UCD) that prioritise the needs, expectations, and limitation of the user during the design pro- cess [48]. It is an iterative methodology that relies on user involvement to ensure that the final product is both functional and user-friendly. Active participation of users in the design and development stages is essential. This mean that designers engage with users through methods such as interviews and usability testing to un- derstand their behaviours, preferences, and challenges. It ensures that the design is informed by users actual needs rather than assumptions. In addition, UCD fol- lows an iterative design cycle where prototypes are developed, tested, and refined multiple times based on user feedback. This helps to identify and address usability issues early in the process. The design process begins with in-depth user research to explore their goals. UCD also considers the emotional and experiential aspects of interaction ensuring that products are engaging and satisfying to use. Usability testing and evaluations are conducted at various stages to assess how well the de- sign supports user tasks and whether it meets accessibility and efficiency standards. Compared to traditional functionality driven design approaches, UCD reduce the risk of creating products that are too difficult to use [48]. 4.3.2 Research Through Design Research through Design (RtD) is a method for interaction design research within HCI [52]. The design itself can serve as a probe to generate new knowledge by creating and evaluating interactive products. This method differs from traditional scientific and engineering approaches that rely on controlled environments and hy- pothesis testing. Instead, RtD focus on exploring possibilities and producing insights throughout the design process. Researchers can uncover new theoretical perspectives 23 4. Theory and frameworks that might not emerge through conventional methods by produc- ing and iterating on design artifacts. The value of RtD lies in addressing complex, open-ended problems where traditional approaches might not be applicable [52]. 4.4 Human-Vehicle Interaction Human-Vehicle Interaction (HVI) is an important field of modern transportation since vehicles become increasingly automated and intelligent. It refers to the way drivers and passengers interact with a vehicles systems, interfaces, and features. Ad- vancements in automotive technology continue to evolve and the role of HVI start to extend beyond traditional Human-Machine Interaction (HMI) where intelligent systems and automation play a more active role in driving and decision-making processes [53]. However, designing effective human-vehicle interactions requires ad- dressing challenges such as cognitive workload, system transparency, and user trust. Intelligent in-vehicle interaction technologies is changing the way of transportation where user-centred design aim for automation to assists rather than replace human decision-making. Haptic feedback and adaptive displays provide drivers with in- formation to focus on minimising distractions and enhancing situational awareness. These technologies are important to ensure that human-vehicle interactions remain safe, efficient, and user-friendly [54]. The design of human-vehicle interaction must balance technological advancements with human cognitive and perceptual capabili- ties. 4.4.1 Cognitive Overload Mental Workload refers to how humans process information and manage cognitive workload in complex environments such as driving and multitasking scenarios. Ac- cording to Wickens [55], cognitive resources are divided across four different dimen- sions. The first dimension relates to the stages of processing that include perception, cognition, and response. Tasks that rely on the same processing stage, such as two demanding activities, are more likely to interfere with each other than those that en- gage different stages of processing. The second dimension is the modalities of input and output. Since humans process information primarily through visual and audi- tory channels, tasks that depend on the same modality can create interference and increase cognitive load. The third dimension focuses on processing codes where there is a difference between spatial and verbal tasks. Spatial tasks, such as interpreting a map, and verbal tasks, like reading written instructions, rely on different cognitive systems. Interference is more likely to occur when two tasks are processed in the same code. Finally, the fourth dimension involves response mechanisms. They can can be manual or verbal, such as steering a car or speaking to a co-driver. Perform- ing two tasks that require the same response mechanism leads to greater cognitive load and diminished performance [55]. Wickens model has significant implications for human-vehicle interaction and driv- ing safety [55]. Multitasking while driving becomes particularly problematic when two visual tasks compete for attention. Keeping eyes on the road while reading 24 4. Theory instructions about the energy consumption on a display is one example of com- peting tasks. However, presenting some information audibly rather than visually distributes the cognitive load across different modalities resulting in reduced inter- ference. This principle supports the effectiveness of heads-up displays in vehicles, as they allow drivers to keep their eyes on the road while accessing critical information. Understanding how drivers distribute attention and cognitive resources is essential to prevent overload or disengagement from the driving task. Furthermore, Young and Stanton [56] argue that automation in vehicles does not lead to a linear reduction in mental workload. Instead, it redistributes cognitive demands. Highly automated systems may reduce the need for continuous manual control but increase the demand for monitoring and decision-making in complex situations. This shift can lead to cognitive underload which is a state in where drivers become disengaged and less prepared to take over control when necessary. However, if automation is poorly designed or requires frequent interventions, it can create overload that increase cognitive strain rather than reducing it. Drivers may lose the ability to perform certain tasks effectively, particularly in emergency situations where manual control is suddenly required as automation takeover more driving functions. System design must consider ways to keep drivers engaged and ensure that they retain essential driving skills. Automation can create confusion where drivers misunderstand the current level of automation or overestimate the systems capabilities. This can lead to delayed reactions in critical moments. Young and Stanton [56] highlights the need for intuitive and transparent automation interfaces that clearly communicate the systems status and limitations. Automation should enhance safety without diminishing driver engagement or essential skills. 4.5 Gameful Design Gamification is not only about adding points, badges, or leaderboards but also about crafting meaningful, engaging experiences by incorporating game design elements into non-game contexts. There is a difference between gameful and playful expe- riences, where gameful design is structured and goal-oriented, while playful design allows for exploration and creativity [57]. It is important for designers to consider user motivation and the context of use as well as the psychological mechanisms that drive engagement. Effective gamification requires an understanding of motivation relating to that systems should be designed to promote competence, autonomy, and relatedness rather than relying rewards [57]. 4.6 Information Visualisation Information visualisation is an aspect of interaction design that helps users interpret and engage with complex data effectively [51]. By transforming raw data into mean- ingful graphical representations, information visualisation reduces cognitive load and enables users to recognise patterns and make informed decisions quickly. Clar- ity should always take priority over decoration. Effective visualisations use hierarchy, 25 4. Theory contrast, and grouping to guide users toward the most important insights without overwhelming them. The choice of visualisation should align with user needs and the specific tasks they aim to accomplish. Interactivity is also important to consider, allowing users to filter, zoom, and manipulate data enhance their ability to explore information and understand the data [51]. Furthermore, Tufte [58] highlights the importance of presenting complex data in a way that is both precise and efficient. The primary goal of any visualisation should be to convey data clearly without unnecessary distractions. The data-ink ratio is concept that encourages minimising non-essential elements in a graph. Every element should directly contribute to the representation of the data, and irrelevant features, such as unnecessary 3D effects or decorations, should be eliminated to focus on the data itself. Tufte critiques "chartjunk" which is the use of redundant design elements in visualisations that can distort the data. A Good visualisation should be straightforward and unambiguous. The integrity of the data must always be preserved, and any distortion risks reducing the credibility of the visualisation [58]. 26 5 Methods This chapter introduce the applied process of interaction design used in the thesis and present the chosen methods for each phase of the Double Diamond framework. 5.1 Interaction Design Process There are multiple design processes in the field of interaction design, but the pro- cesses have aspects in common that typically cover multiple stages taken in design along with the methods and tools used. One established interaction design process is the Design Councils design methodology, the Double Diamond, which consists of four phases represented by two diamonds [59]. The first half of a diamond repre- sents the process of investigating a problem in a comprehensive way (divergence), while the second half of the diamond describes the process of deciding and acting, (convergence). The Double Diamond consists of four key phases : Discover, Define, Develop, and Deliver [59] [48]. The design process is presented in figure 5.1. Discover is the first phase that focuses on researching the issues and gathering insights from the stakeholders who are affected by the problems. The Define phase is for understanding the insights and shaping the problems in different areas to focus on. The result of this phase is a clear problem definition. After the challenges have been identified, the development phase is to brainstorm possible solutions to design and develop potential designs including testing and iterating on the generated ideas. Lastly, the Deliver phase involves testing the potential solutions and choosing one for further refinement and delivering the most promising solution [59] [48] Figure 5.1: Double Diamond design process [59] 27 5. Methods 5.2 Methods for Discover In this section, methods considered suitable for the Discover phase are presented. This includes benchmarking, expert interviews, and questionnaires, aimed at gath- ering insights from users and identifying and addressing challenges. 5.2.1 Benchmarking Benchmarking is a structured methodology used to evaluate and improve business processes, performance, and best practices by comparing them against industry standards or leading organisations. According to Stapenhurst [60], benchmarking serves as a tool for organisations wanting to enhance efficiency, competitiveness, and innovation. The method of benchmarking involves identifying performance gaps and best practices by studying organisations within the same industry [60]. Benchmarking was used in our research as a method to identify best practices and performance standards within the automotive domain. According to Stapenhurst [60], benchmarking is a effective tool for improving processes and innovation by evaluating your approach against industry competitors. Comparison of existing solutions and user interface strategies used by leading automotive manufacturers enables identification of areas for improvement regarding the display of energy con- sumption and ensures that the developed solutions are in accordance with current industry standards. 5.2.2 Expert Interview Expert interviews are a form of qualitative interviews in which the subjects have specialised knowledge or expertise in a particular field, professional or academic [61]. This method can be applied when researchers need to understand specific phenomena that are difficult to investigate using other data sources or when the knowledge required is highly specialized. These types interviews are used to gain insights into complex topics or to gather informed opinions and analysis from individuals who are experts on specific issues [61]. The primary purpose of expert interviews is to gather insights from experts with significant experience and knowledge in driver behaviour and BEVs that are both technically complex and rapidly evolving areas. Conducting expert interviews directly with professionals who have experience and contextual understanding of the challenges in this domain provide in-depth information not available from public sources. 5.2.3 Questionnaire User research refers to the data collection and analysis needed to understand the users and the context of use before the product development begins [48]. Question- naires are a technique used to collect users opinions using closed or open questions, where open questions allow participants to give free-form text answers and closed questions restrict participants to one of a limited set of possible answers. They can 28 5. Methods be distributed to a large number of participants and therefore more data can be collected than with an interview study [48]. Questionnaires is a method to gather input from a broad group of drivers to under- stand the users aimed to design for. This is particularly valuable in the early stages of the research when gaining an overview of user needs and behaviours was essential for guiding design decisions. The scalability of questionnaires make possible to reach diverse participants which strengthened the reliability and relevance of the findings. 5.3 Methods for Define The Define phase centres on analysing insights gathered during the Discover stage. The methods presented for the Discover phase in this section are thematic analysis, affinity diagramming, personas, scenarios, and requirement list. 5.3.1 Thematic Analysis Thematic analysis is a qualitative research method to identify, analyse, and interpret patterns of meaning within the data. Braun and Clarke [62] define it as a flexible and accessible approach that allows researchers to make sense of complex qualitative datasets. The method of analysis consists of six phases. Researchers must first familiarised themselves with the data through repeated reading to begin recognizing potential patterns and gain an in-depth understanding of the dataset. Once familiar with the data, the next phase is coding involving systematically identification of relevant features in the data and assigning codes to meaningful segments [62]. The process of coding can be data driven (inductive) or guided by existing theories (deductive). It can be at a semantic level, focusing on explicit meanings in the data, or a latent level which explores underlying concepts, assumptions, or ideologies. The third phase focus on searching for themes where codes are grouped into patterns that capture significant aspects of the research questions. These themes serve as the foundation for the analysis and should reflect the insights emerging from the data [62]. Following, the fourth phase involves reviewing, refining, and combining themes to ensure they accurately represent the data. The fifth phase is defining and labelling the themes to articulate the essence of each theme. Lastly, the sixth phase is produc- ing the result by weaving together the identified themes into a coherent narrative. The final analysis should offer meaningful interpretations of the themes and their implications within the research context [62]. 5.3.2 Affinity Diagram The method of affinity diagramming is used for organising large amounts of qual- itative data into meaningful patterns or themes. This technique is useful during research analysis to help designers synthesise information from user studies [63]. The researchers write individual pieces of data or insights on sticky notes and then collaboratively group them based on similarities. Overarching themes or categories 29 5. Methods emerge through this grouping process and reveal insights. By engaging multiple team members it fosters diverse perspectives that lead to a more comprehensive understanding of the data [63]. This method is used to transform complex and unstructured information into clear, actionable insights that can guide the design process effectively [63]. 5.3.3 Personas and Scenarios Personas are fictional but realistic representations of users based on research data [64]. These representations help designers understand the needs, goals, and be- haviours of their target users. Creating personas can ensure that user needs are taken into account throughout the design process. The purpose of personas is to create a shared understanding of user needs and to keep the user perspective central during ideation and decision making. It can help to make decisions about the fea- tures of the product and the overall user experience. They should be based on real user research since data from these sources is synthesised to create a representative character. Scenarios are narratives that describe how personas will interact with a product or service in specific contexts. They help contextualise the persona’s needs and behaviours to gain a deeper understanding about user goals and expectations. Personas represents who we design for and scenarios provide a narrative for how and why they use the product [64]. The design team can create targeted and user-centred solutions that align with real-world needs with this method. 5.3.4 Requirements List A requirements list is a structured document that captures all necessary features, functionalities, and constraints for a product [65]. It serves as a foundational refer- ence to ensure that the final product meets user needs. The purpose is to systemati- cally document user and system needs to serve as a reference for design, development, and testing[65]. User stories is one approach to capture requirements that represents the functionality of value for the user. It is presented in the following format: As a , I want , so that [48]. This also propose a solution to capture the user experience and usability goal of the designed product [48]. In this research, a requirements list is used to translate insights gathered from user research and expert input into actionable design goals to the Development phase. 5.4 Methods for Develop The third phase of the Double Diamond aim bring ideas to life by transforming them into a tangible format. This involves creating prototypes with different resolutions with the purpose of evaluating the outcomes. The methods applied in this phase are brainstorming, low-fidelity prototyping, and high-fidelity prototyping described in this section. 30 5. Methods 5.4.1 Brainstorming Brainstorming is a structured but free-flowing process designed to generate creative ideas by group collaboration. Effective brainstorming follows a disciplined approach to maximise creativity and innovation. According to Kelly [66], no idea should be immediately criticised or dismissed and unconventional ideas are welcomed. The ideas should be expanded and combined. There should also be a clear problem statement to keep the discussion productive. Sketches and prototypes are used as tools for expressing ideas. The goal is to generate as many ideas as possible before filtering [66]. In the context of this research, brainstorming at in the beginning of the Development phase can explore new design spaces and generate new ideas to be adapted into prototyping. 5.4.2 Prototyping A prototype is one manifestation of a design that allows stakeholders to interact and explore its usability. Prototyping provides a concrete demonstration of an idea and acts as a tool for the designer to communicate their ideas to users [48]. This method will also help to support design choices, act as a communication device among the team members and a tool for evaluation. In the design process, prototypes act as filters by helping designers focus on spe- cific aspects of a product while disregarding others [67]. This allow designers to test core functionalities, user interactions, or aesthetic qualities without committing to a fully developed product. The filtering process ensures that critical design el- ements receive attention while unnecessary complexities are ignored during early development. They also serve as manifestations of design ideas by making abstract concepts concrete. Designers give form to an idea to evaluate feasibility, usability, and desirability while iterating toward a final product [67]. Prototypes vary in fidelity, ranging from low-fidelity sketches and wire frames to high-fidelity models. Each type of prototype provides different insights and guide design decisions at various stages of the process [48][67]. In this project, prototypes are used as tools for extrapolation to improve user experience through iterative development and testing 5.4.2.1 Rapid Prototyping Rapid prototyping is an iterative design approach that enables designers to effec- tively create, test, and refine concepts before committing to a final product. This allows for early-stage feedback that informs design improvements and bridge the gap between conceptual design and real-world applications by allowing iterative adjust- ments based on user insights [68]. 5.4.2.2 Low-Fidelity Prototype Low-fidelity prototypes are easy and cost effective early prototypes. They require little time to create which allows designers to develop ideas rapidly and iterate 31 5. Methods through multiple versions in a short time frame with little resources. At this stage, it is possible to use low-fidelity prototypes to identify problems with the proposed solution, evaluate and determine whether it meets the requirements and user needs [69]. 5.4.2.3 High-Fidelity Prototype High-fidelity prototypes are more detailed and interactive representations that re- semble the final product. These prototypes include actual user interface elements, colours, typography, and animations. This makes it suitable for advanced usability testing in the later stages of development [69]. 5.5 Methods for Deliver Deliver is the final phase of the Double Diamond framework where usability testing is conducted to evaluate the solutions and choose the most promising for delivery. This process can use several combined techniques, such as interviews, focus groups, and think-aloud methods. Combination of methods can provide valuable feedback from the participants. 5.5.1 Focus Group Focus groups are a qualitative research method used to gather information on user ex- periences, opinions, and preferences about games and products. Lankoski and Björk [70] highlight focus groups as an effective way to collect subjective data through group discussions. The benefit of using focus groups is that it allows diverse issues to be raised that might otherwise have been missed and is a method to investigate shared issues. The size of the focus group ranges from three to twelve participants [48]. A focus group typically consists of a small number of participants who share common characteristics, such as being belonging to a target audience for a specific product. A moderator facilitates the discussion to guide participants through planned topics while allowing organic conversation to emerge. Participants build on each others responses that lead to deeper insights than individual interviews might provide. Re- searchers can identify patterns in opinions and attitudes. However, participants may conform to dominant opinions, reducing the diversity of responses, and the way questions are framed can shape responses. Participants should be selected accord- ing to relevant criteria, the moderator should use open-ended questions and avoid leading questions that could bias responses [70]. The objectives with with method is to gather users’ opinions and attitudes on early stage prototypes to uncover ex- pectations to bring into the second iteration. 5.5.2 Think-Aloud Protocol The think-aloud protocol is a methodology used in psychology and interaction design to study cognitive processes. It involves asking participants to verbally describe their 32 5. Methods thoughts and actions while performing tasks, providing insight into their thought patterns and strategies [71]. This method provides an understanding of how work- ing memory is utilised during a given task. The method encourage participants to verbalise their thinking process during the experiment, such as repeating informa- tion or using visualisation techniques, offering insight into how thought patterns and strategies relate to the task. It can also be used to identify errors and mis- understandings during the task. The usual procedure for the think-aloud protocol starts with warm-up interview, instructions on how to vocalise thoughts, wrap-up interview, and analysis of the answers [71]. In this research, we conducted an ex- periment using a think-aloud protocol to evaluate the prototype, as it allows us to observe the cognitive processes of participants while completing predefined tasks in the simulation. 5.5.3 Interview Methodological triangulation means employing different data gathering techniques to validate the result of one inquiry referring to a similar result obtained through different perspectives [48]. Interviews can be used to compensate for limitations in the other methods. Using semi-structured interviews allows to combine features of both structured and unstructured interviews. There is a basic script with preplanned questions, but the nature of semi-structured interviews allow for follow-up questions such as why and how to gather a deeper understanding of the answers given by the interviewee [48]. Interviews could be used after the think-aloud protocol to ensure that we gathered information that the participant might not have shared during the test. 33 5. Methods 34 6 Planning This chapter outlines the initial