Thesis Topic:
Motion as Communication: Using Micro-Interactions to Help Drivers Understand Automation Mode Changes
| Aims | Objectives | Methods | Outcomes | Outputs |
|---|---|---|---|---|
| Understand how drivers currently get confused about automation modes and handovers. | Clarify the problem space of mode confusion and existing HMI strategies for communicating mode and takeover. | Targeted literature review on mode confusion, takeover studies, and automation HMI guidelines. | Clear picture of where current interfaces fail (e.g., unclear state, weak anticipation, bad timing of alerts). | Short problem framing section with diagrams of current HMI patterns and failure modes. |
| Find out what existing research already says about effective feedback and motion in high‑load, time‑critical interfaces. | Collect and organize evidence on which feedback types and motion patterns improve comprehension and reaction time. | Systematic search, screening, and evidence mapping across automotive, aviation, medical, and UI/motion research. | Evidence maps showing which strategies (static, motion, multimodal) work, where, and how strongly they’re supported. | Evidence tables and visual maps you can include in the thesis (and reuse in slides). |
| Translate that evidence into concrete motion patterns and parameters for automation mode changes. | Define a compact motion framework for entering automation, exiting automation, and escalating takeover requests. | Research‑through‑design: sketching, storyboard flows, prototyping micro‑interactions (e.g., in Figma) guided by the evidence. | A small, coherent set of motion patterns with rationale tied back to specific studies and theories. | Motion specs (timing, easing, behavior) plus prototype screens showing mode transitions and alerts. |
| Turn those patterns into reusable motion tokens and a design guide that teams could plug into a design system. | Define motion tokens (durations, easing curves, escalation patterns) and describe how to use them in an automotive HMI. | Synthesis + systems thinking: abstracting patterns into tokens, writing guidelines, and mapping them into a component library structure. | A motion “layer” that can sit inside a design system for vehicle HMIs (or similar products). | Motion token set, usage guidelines, and an example component library (e.g., Figma pages or documented components). |
| Reflect on how this changes the way we think about motion in safety‑critical interaction design. | Position motion as a functional communication tool (not just delight) and highlight gaps for future empirical work. | Critical discussion that connects your framework back to theory (cognitive load, attention, mode confusion) and identifies missing research. | Clear articulation of what we know, what we can recommend with confidence, and what still needs live testing. | Discussion + conclusion chapters that wrap up the framework, its limits, and next steps (including ideas for future simulator studies). |
