DrivAR
Exploratory research project on how augmented reality systems can deliver helpful information in heads-up displays (HUDs) without diverting driver attention.​
Context & Background
As vehicles adopt increasingly complex digital systems, drivers face growing challenges with distraction and information overload. While AR head-up displays (HUDs) promise to bring information closer to the driver’s line of sight, poorly designed overlays risk cluttering the visual field and undermining safety. ​
Role
User Experience Researcher and Project Manager
​
Timeline
11 Weeks
​
Domain
Automotive UX Research / Augmented Reality / Cognitive Ergonomics
Methodology
​
Literature Review
To establish a theoretical foundation on cognitive workload, attention, and AR HUD usability, ensuring design decisions were grounded in prior research.
-
Reviewed academic papers and industry reports on visual perception, multimodal cues, and interface clutter. Synthesized findings to guide hypotheses and safety-focused design principles.
-
Identified key factors affecting driver attention, including information density, visual placement, and multimodal signaling. Highlighted safety concerns related to HUD complexity.
-
Informed initial design principles emphasizing clarity, simplicity, and minimal cognitive load, which guided prototype development.
​
Competitive Analysis
To understand existing AR/HUD solutions, identify usability gaps, and uncover opportunities for a more driver-centric, low-cost design.
-
Conducted a detailed review of luxury vehicle HUDs (BMW, Mercedes, XPeng), aftermarket apps (Hudway, Sygic AR), and Car Play. Evaluated features, accessibility, and potential distractions.
-
Found most systems are either expensive, feature-heavy, or distract drivers with smartphone-based overlays. ​
​
Contextual Inquiry
To observe drivers’ natural behavior and capture authentic pain points, ensuring designs reflect real-world usage.
-
Conducted ride-alongs and interviews. Participants demonstrated their navigation habits, attention strategies, and interactions with current tools
-
Reinforced the need for low-distraction, trustworthy AR overlays that complement driver attention rather than compete with it.
So now we must ask:
How can augmented reality heads-up displays deliver essential driving information in a way that supports driver attention and decision-making without increasing cognitive workload or visual distraction?
​
User Interviews
To explore perceptions of safety, trust, and cognitive load in AR navigation.
-
Conducted 8 semi-structured remote interviews. Asked participants to describe “too much information” and how they assess reliability. Transcripts were coded to extract recurring themes.
-
Participants valued simplicity, reliability, and minimal visual clutter. Distrust arose when overlays were intrusive or poorly timed.
-
Directly informed early design principles, emphasizing context-aware and low-clutter AR interfaces.
​
Surveys
To gather quantitative context about drivers’ behaviors, tool usage, and attitudes toward AR technology.
-
Administered an online exploratory survey via Qualtrics to 15 participants. Measured driving frequency, navigation habits, perceived stress, and openness to AR.
-
High reliance on smartphone navigation; participants reported frustration with frequent glances away from the road.
-
Identified variables critical for participant selection for interviews and guided the design focus toward minimizing visual distractions.​
We arranged our user feedback into an Affinity Diagram...
...then designed a testing environment for observing user behavior with augmented reality displays in a safe driving environment.
Wizard-of-Oz Simulation Testing
To validate AR HUD concepts before building functional hardware, ensuring design decisions are tested under realistic conditions.
-
Created a simulated driving environment in BeamNG.drive using Logitech steering wheel, gas pedal, and gear system. I manually triggered AR-style overlays while participants navigated routes. Tasks included:
-
Baseline: standard map navigation
-
Assisted: navigation with AR overlays
Collected performance metrics (task completion time, detours, map-check frequency) and think-aloud verbalizations.
-
-
AR overlays reduced map-check frequency, improved route confidence, and were perceived as helpful when minimally intrusive. Overloaded or fast animations caused stress.
-
Validated low-clutter, context-sensitive overlays and guided refinements for visual timing, placement, and content density.
Our user research was synthesized to extract themes:
& create three user personas:
​
A/B Testing of Concepts
To gather sentiment on mid-fidelity HUD designs.
-
10 participants compared Concept A (not pictured) and Concept B (minimalist) remotely. Collected preference rankings and qualitative reasoning.
-
Majority preferred the minimalist HUD, citing clarity, reduced distraction, and greater sense of control. Immersive overlays were engaging but cognitively demanding.
-
Confirmed that simplified, context-aware visuals improve perceived safety and driver focus, guiding the final design direction.​
​​
Analysis & Outcomes
The analysis revealed that drivers valued minimal visual distraction, preferring auditory or peripheral cues. Simplifying the interface and limiting data points increased comfort and trust.
Impact
The project emphasized the importance of human-centered principles in emerging technology spaces. Cognitive processing was something I studied heavily in undergrad, and I was excited to apply that knowledge so directly to this project. It influenced my perspective on designing for attention on how to guide it responsibly rather than compete for it.
Reflection
DrivAR encapsulated my journey as a hybrid researcher and designer. It challenged me to ideate testing methods to tackle automotive user experience, and I was exposed to working with subjects in an untraditional research setting. Although the research strategy and employment was the focus of this project, it was cool to create designs for a unique interface.