Tricycle
Smart parking solutions for urban cyclists to find and secure their ride
DURATION
March 2024 - June 2024
ROLE
Product Designer / Solo Project
Tools
Figma, Protopie
OVERVIEW
Tricycle is a mobile application designed to solve one of the most pressing issues for unban cyclists by helping them find safe, reliable, and personalised parking recommendations to ensure a seamless and stress-free cycling experience.
PROBLEMS
Cyclist need parking they can trust and rely on
In London, high bicycle theft rates make cyclists feel anxious when parking their bikes, particularly in unfamiliar or busy areas. This anxiety is intensified by uncertainty around parking availability, as cyclists often cannot tell whether a parking location will have enough space upon arrival. The lack of clear, reliable information about both parking safety and availability forces cyclists to make rushed decisions, increasing stress and the risk of unsafe parking choices.
SURVEY
insight
• Uncertainty around parking availability causes stress
• Weather changes affect parking decisions
• Security concerns impact trust and behavior
RESEARCH SYNTHESIS
User Journey
The user journey outlines the key steps cyclists take when using the Tricycle app. It highlights their goals and challenges, helping to create a better and more seamless experience.
Competitive Analysis
This analysis highlights why existing navigation and cycling apps fail to reduce anxiety at the moment of parking decision.
insight
Existing solutions provide navigation or cycling support, but none are designed to reduce anxiety at the moment of parking decision.
DESIGN SOLUTIONS
How might we help cyclists feel confident when deciding where to park?
Reduce anxiety, not just provide information: Focus on reducing uncertainty at the moment of parking decision.
Support fast decisions in high-pressure moments: Enable quick, clear decisions in busy and unfamiliar environments.
Build trust through clear and visible signals: Use simple visual cues to communicate safety and availability.
Core User Flow
This simplified flow highlights how cyclists move through the app at the moment of parking decision. Each step prioritises clarity, trust, and speed in busy urban environments.
DESIGN
Design System
Establishing a unified design system for a consistent and intuitive user experience.
Scenario 01
This simplified flow highlights how cyclists move through the app at the moment of parking decision. Each step prioritises clarity, trust, and speed in busy urban environments.
Task 1
Assess the safety of the facility and make a confident decision
Key Feature
Integrated Destination Search & Contextual Widgets
Justification
Eliminating Double-Search: Traditional navigation apps force users to search twice (destination → parking). By integrating parking options directly into the destination search, this design proactively suggests the best spots near the final goal, streamlining the route planning process.
Reducing Cognitive Load: Surfacing contextual widgets (e.g., weather-based suggestions, recently visited spots) immediately upon opening the app allows users to make quick, zero-tap decisions based on their current situation.
Scenario 02
A rider evaluates a potential parking spot and needs immediate reassurance about its security to alleviate theft anxiety.
Task 2
Assess the safety of the facility and make a confident decision
Key Feature
Scannable Facility Icons & Visualised Safety Reviews
Justification
Building Data-Driven Trust: For urban cyclists, 'safety' is the primary concern. Instead of forcing users to read through lengthy text reviews, the design aggregates feedback into visual tags. This provides immediate, data-backed reassurance, replacing subjective anxiety with verified trust.
Frictionless Decision Making: Standardised facility icons (CCTV, Repair) allow for instant scannability. Once the user is convinced, the prominent, sticky 'Get directions' CTA ensures an effortless transition from the decision phase to active navigation.
Scenario 03
The rider has successfully parked. The app now asks for a quick update on the spot's status to help the next cyclist.
Task 3
Contribute accurate real-time data about the parking spot without friction.
Key Feature
Frictionless Crowdsourcing & Tap-based Feedback
Justification
Minimising Input Friction: Tired riders are unlikely to type out long reviews. To encourage participation, I replaced keyboard inputs with simple 'Yes/No' questions and tap-based chips (e.g., Available, Moderate, Full). This allows users to submit valuable feedback in seconds.
Scenario 04
The user is away from their parked bike. A potential theft is reported nearby, and the user needs to quickly understand the threat and take action.
Task 4
Assess the exact risk area and decide whether to relocate the bike.
Key Feature
Actionable Smart Notification & Visualised Risk Zone
Justification
From Panic to Action: The initial icon-based alert (AS-IS) provided a generic warning without location context, causing unnecessary anxiety. I shifted this to a map-based UI (TO-BE) that visualises the specific theft radius (Red Zone).
Scenario 05
The user finishes their daily activity and opens the app to pick up their bike. The app predicts their next move and prepares the route back.
Task 5
Start the navigation for the return trip with minimal interaction.
Key Feature
Predictive Routing & Zero-Search Navigation Card
Justification
Seamless Ride Preparation: By analysing the time elapsed since parking and the user's routine, the app proactively anticipates the next logical destination ("Home"). This eliminates the repetitive, high-friction task of manually typing an address, offering a true zero-search experience right upon launching the app.
FEATURE HIGHLIGHT
Context-Aware Smart Alerts
Notifications are tailored to exact real-world situations, such as sudden rain or local market days.
Each notification is hyper-relevant to the rider's current context. Instead of just sending generic updates, the smart alerts provide actionable suggestions, allowing users to make quick decisions on the go without unlocking their phones.
@ Jio Park, 2026