CarPlay
Date Range
2021 - 2022
Operating System
iOS (CarPlay)
Role
Rotational Product Designer
Introduction
Opportunity
Reducing Friction in Driving Scenarios through Voice
While CarPlay, Siri was becoming more widely available across vehicles, we noticed consistent breakdowns in common voice tasks. Switching between audio sources, adjusting language settings, or navigating dictation styles often triggered errors, particularly when users needed to repeat themselves or wait through stacked confirmation prompts.
Designing for HandsFree
Driving introduces unique UX constraints. Visual feedback is limited, and user attention is partial at best. The team saw an opportunity to streamline voice interaction flows: reducing redundant confirmations and increasing the success rate of task completions without visual input. This required rethinking how Siri confirmed, canceled, or requested clarification from users, while staying aligned with HMI and safety standards.
Solution
Exploration of Lightweight Confirmation Models
I supported an internal sprint focused on reducing friction in Siri’s voice interaction flows, particularly around messaging and dictation. We explored alternate paths that minimized confirmations while preserving task clarity.
Rapid Prototyping Across Multilingual Scenarios
Using flow mapping and light prototyping, I contributed to early design explorations across English and Spanish configurations. The goal was to evaluate task success and voice clarity in driving conditions where visual feedback is limited.
Discovery
Field Research
Validating Voice Interactions Through Usability Research
To evaluate proposed updates to Siri’s dictation behavior, I supported a set of moderated usability tests using internal CarPlay builds on iOS. Over a three-week sprint, we ran sessions with 20 participants in both English and Spanish. These sessions helped us surface key behavioral patterns — from how users responded to confirmation prompts, to how speech pacing varied by age and cultural background. We used these insights to explore new flow structures and edge cases before they reached full production.
“It’s not just about what users say — it’s how they say it, and when they give up.”
Design Considerations
Voice First, Touch Aware
We treated CarPlay as a mainly voice, sometimes touch platform. Our assumptions and early flows prioritized voice task success while documenting fallback behaviors when users instinctively reached for the screen.
Timing and Feedback Rhythm
User trust dropped when Siri responses came too fast or too slow. We noted how even subtle delays or overly quick prompts made users interrupt or abandon the flow. These moments shaped how we thought about pacing and confirmation placement.
System Expectations by Age and Locale
Younger drivers expected Siri to behave more like a messaging assistant. Older participants leaned toward imperative dictation commands. Spanish-speaking users often included politeness phrasing or pauses, which impacted recognition fidelity and recovery logic.
Glanceability and Recovery
Visual prompts were rarely seen but often relied upon. When a message or error did flash onscreen, it needed to be recognizable at a glance and predictable enough that users could recover without needing to retry the task completely.
InCar Edge Cases
We explored edge scenarios such as tunnels, music interruptions, or loud passenger cabins where secondary voices could confuse Siri. These informed how we approached affordances around “intent certainty” and fallback strategies.
Wireframes
Mapping Out Response Templates
To support design direction, I worked on early wireframe explorations tied to Siri voice tasks in CarPlay. These sketches were shaped by insights from usability testing and aimed to simplify how users completed actions without needing to look at or touch the screen. The goal was to create tangible artifacts that helped the team evaluate interaction timing, voice clarity, and fallback patterns in driving conditions.
To translate our user insights into practical solutions, we prototyped a series of lightweight interaction patterns addressing common Siri breakdowns within the CarPlay experience. These focused on: disambiguating saved locations for contacts, verifying voice recognition across multilingual contexts, and recovering gracefully from ambient noise interference. Each wireframe targets a distinct voice UX edge case while remaining aligned with Siri’s systemic constraints and CarPlay’s safety model.
Listening State Indicator
The UI introduces a new visual motif to reinforce Siri’s active listening state within the CarPlay environment.
Intent Disambiguation Flow
Issues a clarifying question when a voice command references a contact with more than one saved address.
Input Modal Flexibility
System prioritizes voice interaction but supports fallback touch selection for safety and accessibility.
Language Confidence Cue
A subtle icon communicates when Siri detects a language change in voice input, helping users verify parsing accuracy in multilingual contexts.
The UI adapts to confirm in the detected language, enabling fast correction or approval based on previous utterance patterns
Name Disambiguation Repair
Siri responds to uncertain voice recognition with a spoken follow up and bold onscreen name for visual verification. This prevents misdirected messages caused by ambient noise or contact list overlap.
Users can resolve the prompt by either speaking or tapping. Voice input is prioritized for Siri HandsFree, while large touch targets offer safe, glanceable fallback.Peripheral Recognition Design
Minimal text and layout hierarchy allow users to resolve ambiguity without needing to fully engage visually, supporting safer use in driving conditions.
Solution
01
New Siri Listening Indicator
Reduced Mental Load
To improve clarity and user trust during voice interactions, we explored alternative visual affordances for Siri’s listening state. The resulting indicator was optimized for peripheral awareness, helping drivers confirm Siri is engaged without losing focus on the road.
Visual Hierarchy
The animation was tuned for both brightness and contrast across driving environments. This was informed by our ambient light testing and helped us balance visual feedback with minimal distraction.
02
ETA Sharing with Voice
Context Aware Prompts
Siri now proactively offers to share your estimated arrival time during active navigation sessions. This feature reduces manual steps, particularly when users are running late or entering known geofences like “Home” or “Work.”
Passive Safety Enhancement
By converting a manual task into a single voice command — or an automatic suggestion — this update significantly reduces driver distraction while reinforcing helpful, timely behavior.
03
Dictation + Audio Messaging in CarPlay
HandsFree Messaging
In response to high demand for safer communication, Siri now supports both text and audio messaging in CarPlay. Users can dictate messages or opt to send short voice memos all while keeping eyes on the road.
Multilingual Support
Testing was conducted across English and Spanish locales to ensure accurate transcription and intent matching, particularly in bilingual households and code switching environments.
04
Siri + Smart Home Integration
Ambient Task Handling
With HomeKit support, users can issue voice commands to control lights, garage doors, or thermostats before pulling into the driveway. This helps bridge the home–vehicle interaction gap and reflects Apple’s expanding ecosystem thinking.
Confidence Feedback
CarPlay now provides stronger confirmation for smart home commands, either through visual reinforcement or spoken confirmation, to avoid misfires in shared environments.
05
Siri Suggestions for Driving Context
Proactive Navigation & Music Cues
Siri has become more anticipatory within CarPlay, surfacing common destinations, calendar events, or playlist suggestions based on usage patterns. These contextual nudges help reduce cognitive load and keep interactions fluid.
Driver Focused Timing
Suggestions are delivered during natural lulls, like near rest stops, to avoid cluttering attention during critical navigation or turns.
Outcome
US Enterprise Launch
We conducted a 7-week pilot of the app with 52 internal Apple account managers in the enterprise workspace. This pilot allowed us to gather valuable insights and inform the future development of Coach.
Instant Answers
High User Engagement
49 out of 52 users continued to use the app daily.
Users asked an average of over one question per day.
Positive User Feedback
75% of respondents gave a thumbs up rating.
25% of respondents gave a thumbs down rating.
Key Insights
High Utility: The Instant Answers feature is valuable for finding information, getting answers, and crafting solutions.
Improvement Opportunity: We needed to enhance response quality for specific templates, which can be achieved by analyzing user expectations and refining the model.
Interactive Practice
High User Engagement
Users practiced on average 1 session per day.
Positive User Feedback
64% of respondents gave a thumbs up rating.
36% of respondents gave a thumbs down rating.
Key Insights
High Utility: The Interactive Practice feature proved invaluable for testing various approaches to client solutions within specific industries. The ability to explore multiple approaches in a low-risk environment, coupled with real-time feedback and tips, significantly enhanced user learning.
Improvement Opportunity: To further enhance realism, we will need to consider incorporating more industry-specific problems and ideas into the customer needs scenarios. Additionally, exploring the integration of tone of voice and facial expression detection could provide even more comprehensive assessments.
