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Routly

Connecting people,
routes, and interactions.

Routly is an AI-powered ride-sharing platform that blends efficient travel with meaningful social connection, built with a focus on safety, control, and accessibility.

UI/UX DesignerVisual DesignerRide-sharing
Routly project overview with branding, designer roles, and four app screens
Routly / Connecting people, routes, and interactions

01 / overview

Connecting people, routes, and interactions

Routly is an AI-powered ride-sharing concept that brings efficient travel and meaningful social connection together. My roles span UI/UX design and visual design, with safety, accessibility, and rider control guiding the experience.

Routly · Project overview

02 / problem

A journey can be more than a destination

Transportation typically prioritizes speed, cost, and individual convenience. Routly explores a different question: how can a shared ride create opportunities for connection without making social interaction feel compulsory?

The opportunity

Daily commutes are a frequent, underused setting for human connection. Riders need the freedom to move between solitude, quiet coexistence, and active engagement.

How might we

How might we design a shared mobility system that enables meaningful, low-friction social interaction while preserving user autonomy, safety, and comfort?

03 / research

From mobility systems to social behavior

The research moved from structural changes in transportation to the conditions that make people comfortable interacting during a ride.

Phase 1 · Systems-level research

32 academic and industry sources; PESTEL analysis across 100+ sources; a survey with 216 respondents; 11 expert interviews; 28 user interviews; and synthesis of 1,300+ data points.

Phase 2 · Social behavior

4 expert interviews, 5 Gen Z user interviews, a mobility preference survey with 14 respondents, and a social preference survey with 15 respondents.

Context shaping the opportunity

The original research explored declining interest in private car ownership, sustainable mobility, social connection, and safety and affordability barriers.

04 / insights

Connection works best when it stays optional

The research points toward adaptable social environments rather than one fixed way to share a ride.

Let riders choose their level of engagement

Social preferences change with context. Quiet, passive coexistence, and active conversation all need to be valid choices.

Start with common ground

Shared interests, destinations, events, and neighborhoods provide natural entry points for conversation.

Make interaction organic

Subtle prompts and optional engagement are preferable to scripted experiences or intrusive nudges.

Build comfort before connection

Trust, physical safety, and protection from social pressure are foundational. Fluid, interest-based communities also support the research theme of “modular belonging.”

05 / solution

A shared ride, shaped around its riders

The proposed robotaxi platform uses contextual AI matching to consider social compatibility alongside route efficiency.

User-controlled sociality

Engagement is adjustable and reversible. Riders can choose to connect or stay quiet.

Context-aware matching

Routes, interests, social preferences, and rider intent inform compatible ride groups.

Digital support for real interaction

Digital touchpoints facilitate conversation while leaving room for the physical experience.

Trust and safety

Rider autonomy and psychological comfort guide the matching and interaction design.

Design solution · A connected ecosystem of rides, people, and places
Design solution · A connected ecosystem of rides, people, and placesView full size ↗

06 / journey

Before, during, and beyond the ride

The experience connects a personal mobile app with a shared in-vehicle interface.

01 · Build a social profile

Onboarding captures interests, expertise, topics of curiosity, conversation style, and social intent, including networking, casual conversation, or quiet travel.

Building a social profile · Interests, preferences, and social intent
Building a social profile · Interests, preferences, and social intentView full size ↗

02 · Match and book

Recurring, scheduled, and on-demand rides combine route efficiency with social compatibility and network proximity. Riders choose social mode and a preference for familiar or new connections.

Adaptive ride formation · Planning and booking
Adaptive ride formation · Planning and bookingView full size ↗
Adaptive ride formation · Matching and rider preferences
Adaptive ride formation · Matching and rider preferencesView full size ↗

03 · Prepare for the ride

Lightweight co-rider profiles, shared context, optional conversation starters, and destination highlights reduce uncertainty before meeting.

Pre-ride experience · Reducing social friction
Pre-ride experience · Reducing social frictionView full size ↗

04 · Connect in transit

The shared interface offers common interests, contextual topics, location insights, and optional music, media, or games. Riders can adjust ambiance, express interest in topics, and save destinations.

Shared in-vehicle interface · Building connection in transit
Shared in-vehicle interface · Building connection in transitView full size ↗
In-ride mobile experience · Rider controls and shared context
In-ride mobile experience · Rider controls and shared contextView full size ↗

05 · Continue after arrival

Save connections, join communities, and bookmark places. Interest-based groups, shared planning, and event discovery extend the value of a ride.

Post-ride experience · Extending social value
Post-ride experience · Extending social valueView full size ↗
Social infrastructure · Communities and shared planning
Social infrastructure · Communities and shared planningView full size ↗
Discovery layer · Places and recommendations
Discovery layer · Places and recommendationsView full size ↗

Visual identity

The brand system brings the mobile and in-vehicle experience together.

Routly visual identity · Logo, typography, color, and graphic elements
Routly visual identity · Logo, typography, color, and graphic elementsView full size ↗

Intelligent matching

The matching flow connects rider preferences with a compatible shared journey.

Intelligent matching · System flow
Intelligent matching · System flowView full size ↗

07 / strategy

Designing an ecosystem that can grow

The business strategy considers repeat usage, fleet integration, and context-specific communities.

Pricing and retention

Demand- and context-based pricing, commuter subscriptions, and loyalty incentives.

Service integration

A consistent experience across vehicles and providers, supported by an integration framework for mobility partners and standardized hardware modules.

Partnership opportunities

Entertainment services, universities, employers, local businesses, and residential communities are proposed partners—not confirmed partnerships.

Community-led growth

Events, temporary communities, and seasonal campaigns create relevant reasons to share a ride.

08 / validation

Testing the concept with Gen Z

16 participants aged 19–25 across multiple cities evaluated scenario-based prototypes. The project recorded SUS, NPS, and qualitative feedback.

83.44 · System Usability Scale

Reported score from the prototype evaluation.

75 · Net Promoter Score

Reported score from the same concept validation.

Participant feedback

“Low risk, high chance of meeting great people.” — Student, 23. “Digital and physical blend seamlessly.” — Student, 24. “Highly appealing for younger users.” — UX Designer, 25.

What these results tell me

The prototype feedback is encouraging. These results describe a small concept evaluation, rather than production adoption or long-term behavior.

09 / reflection

Designing relationships, not only interfaces

Routly reframed the project around how people relate to one another during everyday travel.

Transportation as a social setting

The experience of a journey matters alongside the efficiency of reaching a destination.

Technology as a facilitator

Digital tools should support real-world interaction without taking over the moment.

Responsible matching

User control, safety, and transparency need to guide AI matching decisions.

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