SlotSpot is a design-driven entrepreneurial project created in collaboration with design engineer Beny Hafkamp, focused on building a safety-first parking tool from scratch through user-centered research, iterative prototyping, and high-fidelity UI design.
From defining the problem to testing solutions, I guided the full UX processâbuilding SlotSpot from the ground up. I led user research, designed flows and wireframes, and continuously iterated based on feedback. Working closely with brilliant engineer Beny Hafkamp, I focused on creating a solution that was not only functional, but human-centered and ready to build.
Two-person UX and dev team. 8-month remote project covering research, prototyping, and testing. Still in funding phase.
Figma, Illustrator, Photoshop, Zoom, Google Docs, Caffeine.
People are frustrated searching for parking.
During interviews with drivers of varying backgrounds and demographics, including working people, parents, women, and college students, one issue kept surfacing: trying to find a safe, convenient, and preferably free place to park in crowded areas was often stressful and unpredictable.
Some users avoided entire neighborhoods or even going places they otherwise would go simply because parking felt like a gamble, especially at night or when time was tight. Furthermore, users indicated that the amount of waste that goes into finding parkingâsuch as money in gas and vehicle wear and tear, as well as frustration and the danger associated with road rageâmade the parking dilemma a very tangible but necessary evil. This all raised an important question:
How might we help people find parking that's fast, safe, and stress-freeâeven in high-demand areas?
Average annual cost per driver spent searching for parking
Drivers who have avoided trips due to parking difficulties
Time the average driver spends annually searching for a spot
Drivers report feeling stress or anxiety while parking
A simplified, AI-driven parking tool finding both free and paid spaces.
As the driver nears the destination, SlotSpot highlights available parking zones using a real-time color system. With no taps required, the app visualizes legal optionsâgreen for high-trust areas, yellow for caution, and red for restrictionsâso drivers act instantly and safely.
When the driver changes their route or updates filters mid-trip, SlotSpot instantly recalculates. The zone overlay updates in real time, offering new legal options with minimal disruptionâkeeping parking simple, even when life isnât.
When the driver changes their route or updates filters mid-trip, SlotSpot instantly recalculates. The zone overlay updates in real time, offering new legal options with minimal disruptionâkeeping parking simple, even when life isnât.
Framing the Challenge
Before diving into solutions, we anchored our approach in the Design Thinking frameworkâensuring that every step, from research to refinement, would be shaped by real user needs and clear problem definition.
Refining the parking experience starts with understanding whatâs already out there. Initial audit showed a consistent gap in locating free spots and the nearest available parking based on personal needs.
We explored six popular parking apps to uncover their strengths, weaknesses, and untapped opportunities. This competitive snapshot helped shape SlotSpotâs core features around real-time availability, security, and free + paid parking options.
⢠Popular with travelers/commuters
⢠Integrates with lots and garages
⢠Often cheaper than paying onsite
⢠Mostly paid-only
⢠No real-time spot availability
⢠Not ideal for quick/last-minute needs
⢠Expand to more non-garage, casual, free parking alternatives
⢠Add live availability filters
â
4.5/5.0
⢠Huge user base (millions of city users)
⢠Easy mobile pay/extend features
⢠Great for metered parking
⢠Paid-only⢠App can be glitchy or slow
⢠No built-in free parking discovery
⢠Add map view of free/unregulated areas
⢠Improve time estimation or ânext open spotâ predictor
4.0/5.0
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⢠Best for free parking discovery
⢠Crowd-sourced updates
⢠Includes street sweeping info + alertssum...
⢠Smaller user base = less data
⢠Not always accurate
⢠Limited partnerships with garages or cities
⢠Integrate garage search
⢠Incentivize more user input for accuracy
3.8/5.0
⢠Trusted for reserving paid parking
⢠UI is clean and polished
⢠Works in many major cities
⢠Limited real-time updates
⢠Complaints about lot overbooking
⢠Doesnât always save time when lots are full
⢠Integrate free parking or off-street filters
⢠Display accurate walk time + security info
3.5/5.0
⢠Nice price comparison across lots
⢠Decent historical availability data
⢠Maps nearby lots
⢠Not super accurate in real-time
⢠Not well maintained
⢠UI feels dated
⢠Modernize experience
⢠Integrate user data for better predictions
3.0/5.0
⢠Works in hundreds of U.S. cities
⢠Easy pay-by-phone for city-managed spots
⢠Trusted by municipalities
⢠Only supports paid spots
⢠Doesnât help users find spaces
⢠No map of availability or predictions
⢠Add GPS guidance to open spots
⢠Show free street zones
â
3.0/5.0
The audit showed that these products compete on featuresâand users still feel lost. What would it take to actually help them feel in control?
We asked 8 drivers what they thought about the parking situation, divulging their situations and pain points.
The goal was to validate or strike down our initial assumptions and gain insight into the parking struggleâif one existsâfor potential users of different backgrounds.
Zoom-based and in-person interviews (both formal and informal) revealed that time, money, and stress were significant themes into the parking dilemma.
Time pressure, cost uncertainty/price, and mental load remain the biggest challenges when searching for parking, even in familiar areas.
We extracted pain points and other factors through affinity mapping sessions. Although being able to pay in advance for structures, lots, and garages through apps like Park Whiz and Park Mobile is convenient, most drivers we interviewed don't use these apps often, and they don't provide any free solutions. Moreover, they don't track and display the users' parking expenses and savings in time, money, and health (as in stress factors).
We also discovered that older users were apprehensive about having to learn a new app and use it while driving. In this problem space, safety is of utmost concern.
We generated four user personas to embody the average drivers searching for parking in crowded areas.
Out personas have the same goal but in different situations:Â finding parking in various crowded places with different senses of urgency, different sized vehicles, and in different states of mind.
How do we address user needs optimally?
Simulating users in diverse parking situations led to defining the problem: we needed to create a parking solution that provided free parking spaces as well as economically sensitive (cheap) paid ones; needed to minimize time spent searching; and needed to minimize stress during the search.
Our honing in on the problem revealed some interesting nuances of the search. Older and experienced drivers were more comfortable navigating on their own, while newer drivers or those with low confidence were more prone to seeking a digital solution. The focus had to be on making a solution accessible to the diverse types of drivers.
Defining the problem accurately led to ideas of how we could implement a solution for all drivers that filled competitor gaps and offered a diverse and inclusive solution for diverse drivers.
Design Goals HERE
TEST`
How do we address user needs optimally?
Simulating users in diverse parking situations led to defining the problem: we needed to create a parking solution that provided free parking spaces as well as economically sensitive (cheap) paid ones; needed to minimize time spent searching; and needed to minimize stress during the search.
Our honing in on the problem revealed some interesting nuances of the search. Older and experienced drivers were more comfortable navigating on their own, while newer drivers or those with low confidence were more prone to seeking a digital solution. The focus had to be on making a solution accessible to the diverse types of drivers.
Defining the problem accurately led to ideas of how we could implement a solution for all drivers that filled competitor gaps and offered a diverse and inclusive solution for diverse drivers.
As the driver nears the destination, SlotSpot highlights available parking zones using a real-time color system. With no taps required, the app visualizes legal optionsâgreen for high-trust areas, yellow for caution, and red for restrictionsâso drivers act instantly and safely.
When the driver changes their route or updates filters mid-trip, SlotSpot instantly recalculates. The zone overlay updates in real time, offering new legal options with minimal disruptionâkeeping parking simple, even when life isnât.
When the driver changes their route or updates filters mid-trip, SlotSpot instantly recalculates. The zone overlay updates in real time, offering new legal options with minimal disruptionâkeeping parking simple, even when life isnât.
We explored six popular parking apps to uncover their strengths, weaknesses, and untapped opportunities. This competitive snapshot helped shape SlotSpotâs core features around real-time availability, security, and free + paid parking options.
The SlotSpot prototype brings two real-world flows to life: a fast onboarding setup and a live, AI-assisted parking session. These journeys reflect SlotSpotâs missionâhelping drivers find legal, available parking with clarity, confidence, and minimal stress.
The interface builds on familiar mapping tools but adds intelligence through motion-guided prompts, legality filters, and voice-friendly input. Whether en route or already parked, users get just the right amount of guidance at the right momentâfrom walk-distance filters to smart zone alerts. Itâs a frictionless, mobile-optimized experience designed for real-time use in real driving conditions.
SlotSpot reduces the guesswork, circling, and frustration of urban parking by turning real driver behavior into timely, predictive suggestions. Its AI assistant layers data from APIs, traffic cams, and user preferences to deliver legal, personalized optionsâall wrapped in a calm, intuitive UI.
Testing began with remote, unmoderated usability sessions, where three users completed parking flows using the prototype. Despite limited onboarding, all testers quickly grasped the systemâs intent and interacted fluidly with voice, filters, and predictive suggestions. They praised SlotSpotâs clarity, responsiveness, and toneâespecially compared to clunky map-based tools.
Feedback was gathered through post-session interviews and is currently guiding refinements. Additional in-person observation testing is scheduled with three new users to evaluate performance in live mobile contexts. Some results so far:
Estimated Decision Time Reduction
Completed Tasks with Zero Confusion
Reported Increase in Parking Confidence
Said UI Felt Intuitive and Streamlined
SlotSpotâs biggest strength lies in how it cleverly fuses real-time inputsâtraffic cams, GPS, Tesla Vision, and crowdsourced dataâto accurately identify free and legal parking spots, not just paid garages. This multimodal orchestration makes it one of the only parking tools that helps drivers avoid fees, frustration, and wasted fuel. Testers appreciated how SlotSpot guided them clearly, felt like a co-pilot, and saved them both money and stress in real time.
Reflecting on the process, here are three things Iâll do differently moving forward:
â
1. Increase the sample size and diversity of testers earlier to better validate design assumptions across different driver personas and regions.
2. Prototype deeper system logic earlier, especially for legality filters and zone transitions, to allow more thorough testing of AI-driven decisions.
3. Design analytics features up front (like savings summaries, legality logs, and zone history) rather than retrofitting themâsince users responded so strongly to that data.
Whatâs next: With development and early funding underway, SlotSpot is entering its next phaseâbuilding out the backend, refining its real-time legality engine, and preparing for wider testing. The vision: a driverâs sidekick that not only finds smarter parking, but proves it with clear savings, fewer headaches, and zero guesswork.
Smart Sign Scan
Predictive Spot
Availability
IntegratedÂ
Payments
Map Layer Clarity
Trusted Legal
Information
Parking Zone
Notifications
SlotSpot uses dynamic color zones to simplify decision-making in real time. As drivers approach their destination, legal and high-confidence areas are surfaced in green, while caution and restricted zones fade into yellow or redâall without overwhelming the interface.
As the driver nears the destination, SlotSpot highlights available parking zones using a real-time color system. With no taps required, the app visualizes legal optionsâgreen for high-trust areas, yellow for caution, and red for restrictionsâso drivers act instantly and safely.
When the driver changes their route or updates filters mid-trip, SlotSpot instantly recalculates. The zone overlay updates in real time, offering new legal options with minimal disruptionâkeeping parking simple, even when life isnât.
SlotSpot delivers only what fitsâliterally. With filters set, for example,to large spaces within a 5-minute walk, your smart overlay narrows the noise to show safe, spacious options nearby. Less circling, more confidenceâtailored to your vehicle and time.
Unlike typical parking apps, SlotSpot delivers detailed post-drive insightsâtime saved, fuel conserved, and reduced stressâbased on real behavior. By quantifying each success, it shows users the full impact of smarter parking decisions, reinforcing its value through data other apps simply donât offer.
Please reach out to collaborateâI'd love to hear from you!
