Toyota, In-Car Software Experience

Information Architecture | Systems Design | Cross-Functional Leadership

Client: Toyota North America—embedded with the infotainment team to redesign the Settings experience for the next-generation in-car system.

Problem: The Settings domain had grown to 100+ features across safety, comfort, and connectivity. Users struggled to navigate the complexity, especially while driving—where speed and clarity are critical.

Goal: Create an intuitive, scalable Settings architecture for Western markets while coordinating with global teams developing the system in Japan.

Role: Lead Designer over a two-year engagement. I directed a senior designer and partnered with product, human factors, research, and Japanese design counterparts. Because Settings touches navigation, entertainment, and home, we also cross-collaborated with design leaders across those domains.

Approach: System audits, competitive analysis, regionally adaptive information architecture, and in-car usability testing. We also championed clearer presentation of safety features—adding full names, descriptions, and animations to replace obscure acronyms.

Outcome: The redesigned experience shipped in Toyota's next-generation infotainment system, debuting in the 2026 Rav4. Professional reviewers have praised the clarity of the safety feature presentation—validating an approach we advocated for throughout the engagement.

Toyota's infotainment settings had grown unwieldy—more than 100 features. A next-generation system was being developed globally, and early reviews raised questions about whether one architecture could work across different markets.

I was embedded with Toyota North America to lead the redesign of the Settings domain. The core challenge wasn't just UI—it was information architecture at scale, with real constraints: usable while driving, learnable without a manual, coherent across regions.

What made this hard

Deep nesting and inconsistent categories made common tasks hard to find. Terminology didn't match how drivers actually thought about their cars. And a single global architecture wouldn't serve all global markets.

Key decisions

Rather than forcing a single global solution, we designed regional variants that shared underlying logic but adapted navigation patterns to fit local expectations—list-based, text-forward navigation for Western markets; grid-based layouts for Japan. Categories were restructured around driver mental models, not system logic. We added subtext to clarify naming, designed an overview page for orientation, and used AI to stress-test the architecture against different driver profiles before usability testing.

Making safety features understandable

With ADAS controls moving to the center console, we had room to improve clarity. Rather than relying on obscure acronyms (BSM, LDA) with no explanation, we introduced:

Full feature names alongside acronyms

Plain-language descriptions explaining what each feature does

Animations showing the feature in action

We started by building a complete picture of the problem. The audit covered the existing settings experience, competitor infotainment systems, and early global designs. We mapped every feature, documented hierarchy issues, and identified patterns in where users struggled.

Key findings:

Poor discoverability and inconsistent categorization

Layouts that increased cognitive load—especially problematic at speed

Western users gravitated toward list-based, text-first navigation

Designing for Clarity at Scale

With 100+ features, the goal wasn't to simplify by removing—it was to create structure that made complexity navigable.

We reorganized top-level and sub-level categories around user mental models rather than system logic. Added subtext to clarify ambiguous labels. Reduced visual noise in list views. Introduced quick-action modals for frequent adjustments.

Using AI as a Thinking Partner

Given the scale and diversity of driver profiles, we used AI to explore how different users might navigate the system—new owners vs. longtime users, safety-focused vs. customization-focused, different age groups. This helped identify edge cases and pressure-test category decisions before usability testing.

Final decisions remained grounded in research.

Testing & Validation

In partnership with Toyota's research team, we built a detailed Figma prototype for in-car testing. Twelve sessions—with participants both parked and driving—validated the new structure and surfaced minor terminology refinements.

The redesigned Settings experience shipped in Toyota's next-generation infotainment system, debuting in the 2026 Rav4. The ADAS approach we championed has been recognized in professional reviews.

Challenges

Balancing global consistency with regional usability—one architecture wouldn't fit all markets, but too much fragmentation would create maintenance and coherence problems

Designing for an in-motion context where cognitive load and glance time are real safety constraints

Aligning stakeholders across global teams with different priorities and assumptions

Learnings

Information architecture decisions are often cultural, not just logical—what feels intuitive depends on learned patterns

AI was most useful as a stress-testing tool, not a replacement for research or judgment

In-car testing surfaced issues that desktop prototyping couldn't—context changes everything

Wins

Shipped a validated architecture in the 2026 Rav4

Built alignment across global teams through clear reasoning and shared artifacts

Championed the ADAS clarity approach that earned external recognition

Established a scalable foundation that can absorb future features without structural rework