BOSTON TRAIN APP
Train System App fostering trustworthy communication for Boston commuters
Figma · Brand Identity Design · Community posts
T Talk Overview
PROBLEM
This project was inspired by my own frustrations with the T, Boston’s public train system, where delays and disruptions are often unclear and difficult for riders to track in real time. I set out to design a mobile app that reimagines how riders interact with transit updates by creating a community-driven, social-style platform, essentially “Twitter for the T.”
SOLUTION
The app allows riders to quickly post about real-time events, share updates, and view what others nearby are experiencing. The design emphasizes clarity, speed, and usability, making it simple for commuters to both contribute and stay informed during their daily rides.
Mobile app walk through
APP DESIGN
Ideation
After clearly identifying the gaps in the existing MBTA app, I shifted into the ideation phase. This stage was about transforming raw frustrations and pain points into potential design opportunities. To do this, I used techniques like brainstorming, feature prioritization, and card sorting to imagine how a new kind of commuter app could look and feel. I focused on features that would directly address the most urgent commuter needs: clarity, safety, and reliability. Each idea was tied to a specific pain point uncovered during research:
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Community Posts:
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Instead of one-way announcements from the MBTA, riders could share their own real-time updates, such as delays, crowding, or unusual activity. This feature was inspired by the way commuters already use social media (Twitter, Reddit) to fill the gaps in official communication.
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Urgent Alerts:
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Not every post carries the same weight. To reduce information overload, I designed an “urgent” tagging system where time-sensitive or critical updates are highlighted at the top of feeds. For example, if smoke is reported at a station, or if a major delay is unfolding, this alert is immediately visible.
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Trending & Recent:
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Commuters need a way to separate signal from noise. The “Recent” tab captures all the latest updates in chronological order, while “Trending” surfaces posts that have gained traction from the community.. This dual approach ensures that both freshness and relevance are built into the experience.
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Threat Levels:
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Safety was a recurring theme in research, particularly for women and night commuters. I introduced a visual “threat level” system using clear iconography and color coding (e.g., green = safe, yellow = caution, red = high risk). These quick indicators allow riders to instantly assess the atmosphere at a station before deciding to enter.
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Verified Updates (Certified T):
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To combat misinformation, I added a verification layer. Certain posts, whether from trusted community members, repeated confirmations, or even official MBTA moderators, are flagged as “certified.” This feature builds trust and reliability into the app, ensuring that riders can differentiate between speculation and fact.
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Prioritization: I also applied a MoSCoW framework (Must-have, Should-have, Could-have, Won’t-have) to ensure features were scoped realistically for a minimum viable product
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Must-Have: Community posts, urgent alerts, trending/recent feeds
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Should-Have: Threat level indicators
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Could-Have: Certified/verified updates (expandable in future versions)
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Won’t-Have (for MVP): Complex integrations like MBTA ticketing or full trip planning (kept out of scope to maintain focus)
This helped me stay grounded and avoid safety concerns, while still envisioning a roadmap for how the app could evolve.
By the end of this stage, I had a clear blueprint for the app: a community-first platform with lightweight navigation, visually intuitive safety signals, and mechanisms for surfacing the most useful content. This foundation guided my transition into wireframing, where these ideas began to take tangible form.
UI Mood board
These references highlight patterns worth borrowing for your app: map-centric UI paired with social messaging (mirroring geolocation + peer updates at station level), strong route/background contrast (useful for layering alert or threat levels while keeping navigation clear), minimalist search and filter controls (ideal for quick line and station selection), and maps paired with info cards (a good model for overlaying your station feed—Recent, Trending—without clutter).
Ideating App Screens
Low Fidelity
The low-fidelity wireframes prioritize calm, clarity, and trust for rushed or anxious commuters. Familiar UI conventions reduce learning curves: a top search bar for instant discoverability, bottom-anchored navigation (Home + Posts) within thumb reach, and large, tap-friendly buttons for stations and lines to minimize error while moving. Pill-style tabs (Recent, Urgency, Trending) below the search bar create a scannable hierarchy without endless scrolling, while a bottom-right FAB keeps posting accessible without competing with the feed.
The overall aesthetic is minimal and utilitarian, letting urgency indicators and warning icons stand out against a neutral backdrop. The feed reads like a community bulletin board rather than social media, simple, timestamped posts with subtle metadata (distance, time). Consistent layouts and predictable, ergonomic placement of key actions (search, navigate, post) ensure the app feels reliable and usable even under pressure.
Mid Fidelity
The refined wireframes represent a significant step forward in clarity, usability, and context. By introducing strong header bars that include the MBTA “T” logo, the line or station name, and a home icon, each screen now gives commuters immediate orientation. This makes it much easier for users to know exactly where they are in the app, which is crucial when navigating under pressure. The addition of the vertical station map for the Orange Line also mirrors how riders already visualize the T, creating a more intuitive connection between the digital and physical transit experience.
Another improvement in the refined designs is the scannability of content. Posts are no longer plain text, they now include warning icons, timestamps, location data, and engagement metrics, making them more actionable at a glance. The tab system for filtering posts (Recent, Urgency, Trending) has also been visually strengthened, with clearer pill-shaped buttons and active states that reinforce context. Combined with large, tap-friendly station buttons and the consistent placement of the floating action button for creating posts, these refinements emphasize accessibility and ergonomics, ensuring commuters can interact comfortably even when in motion.
Overall, the refined wireframes establish a tone that feels structured, reliable, and community-centered. Where the earlier versions were conceptual and skeletal, these screens convey a real product experience. The careful use of icons, navigation anchors, and visual hierarchy transforms the app into something that doesn’t just map functionality, but actively supports commuters’ needs for safety, transparency, and quick decision-making.
High Fidelity
These mid-fidelity wireframes shift the app from a neutral prototype toward a branded, trustworthy MBTA product. Color-coded headers and line identifiers (Orange, Red, Green, Blue, Silver) ground the experience in Boston's transit language, while a vertical Orange Line map mirrors riders' real-world mental model of the subway system.
Station feeds gained warning icons, engagement counts, and status badges ("ongoing," "unknown") so commuters can visually parse urgency without reading every post. Pill-shaped filters (Recent, Urgency, Trending) now have clearer active states to keep context obvious.
The homepage now centers on a map—reflecting how commuters think geographically ("what's near me," "what's down the line")—with floating bottom navigation (Home + Posts) layered over it to stay thumb-accessible. Together, these changes give the app a tone that feels both trustworthy and community-driven.
The post creation flow is simple, structured, and safety-focused, letting commuters share updates with minimal friction. Fields follow a logical order, alert name, threat level, description, status, so key details can be entered in seconds. Color-coded threat icons and status pills make severity and resolution instantly scannable, reducing reliance on text. A large, thumb-friendly Post button anchored bottom-right ensures easy submission on the go, making the flow feel efficient and trustworthy.
Feature Addition
While conducting user testing,
I realized that commuters needed a way to engage directly with posts, not just consume updates. Many users wanted to ask follow-up questions, share what they were seeing at the station, or validate what others had reported.
To address this, I added a threaded reply system, allowing riders to build rapport and provide additional context around alerts. During testing, I also noticed concerns about the accuracy of information, so I introduced the “Certified T Worker” badge. This gave official voices a clear presence within community discussions, helping commuters quickly distinguish verified updates from peer commentary. Together, these changes made the app feel more collaborative, transparent, and trustworthy.
These thread screens highlight how the app balances community conversation with credibility. The main alert is anchored at the top with a warning icon and clear details, ensuring the core issue stays visible as discussion unfolds. Replies are displayed in a threaded format, making conversations easy to follow and less chaotic than flat comment lists. What really elevates this flow is the addition of a “Certified T Worker” badge, which clearly distinguishes verified updates from general rider chatter. This creates a space where commuters can share real-time perspectives while still relying on trusted voices for accurate information. The result is a feature that feels both social and authoritative, reinforcing the app’s role as a community-driven yet reliable platform for navigating safety concerns on the T.
Final App Walkthrough
RESEARCH
The app allows riders to quickly post about real-time events, share updates, and view what others nearby are experiencing. The design emphasizes clarity, speed, and usability, making it simple for commuters to both contribute and stay informed during their daily rides.
Objective: Challenge point: cant rely on Train
Design goal: Live updates about the Train
Solution: Twitter(X) but for the T, where people can post a live update about a certain T stop and if its packed or a train didnt come, etc.
When I examined the existing MBTA app, I found that while it provides core transportation updates such as schedules and service alerts, it falls short in delivering meaningful, real-time information that riders actually need during their daily commutes. The updates are often vague, broad, and inconsistent across stations, which leaves users guessing about what’s really happening in the moment. For example, a service alert might simply say there are “minor delays” without specifying where they are occurring, how long they are expected to last, or whether there are alternative options available. Riders are left relying on word of mouth, social media, or personal experience to fill in the gaps.
Competitive and Comparative Analysis
To expand my understanding, I looked at other transit solutions in major cities:
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NYC Subway Apps (CitiMapper, Subway Time): Offer real-time countdowns and rider-sourced tips.
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London Underground’s TfL App: Integrates safety alerts, accessible station details, and live updates.
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Waze (as a non-transit comparison): Uses community-powered updates to give drivers real-time road conditions.
The comparison shows that while apps in cities like New York and London (and even apps in unrelated industries like Waze) use real-time data, accessibility features, and community engagement to build trust, the MBTA app remains one-dimensional. It functions more as a static broadcast tool than a dynamic system responsive to riders’ lived experiences.
User interviews/Observations
To better understand the lived experiences of Boston commuters, I conducted informal interviews with 10 individuals representing a range of demographics, students, young professionals, parents with children, and retirees. I also complemented these conversations with on-site observations at several MBTA stations during both rush hour and late evening. This mix of qualitative data helped me uncover common frustrations, emotional pain points, and coping strategies that commuters employ to navigate the T’s unpredictability.
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Recurring Themes:
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Uncertainty: Almost every participant mentioned a sense of unpredictability when using the T. Even when the MBTA app showed an arrival time, riders expressed doubt about whether the train would actually arrive as scheduled. One young professional summed it up:
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“I never know if the train is actually coming when it says it is. I’ve stood on the platform watching the minutes count down, only to have the train vanish from the screen.”
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Safety Concerns
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Several riders, especially women and those commuting late at night, highlighted that safety is a major factor in their decision-making. Dimly lit platforms, deserted stations, and the lack of reliable updates about what was happening on-site amplified anxiety. One commuter shared:
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“At night, I wish I knew what the station felt like before heading there. Sometimes I avoid the T altogether because I don’t want to risk being alone in a sketchy station.”
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This insight revealed that safety isn’t just about crime, it’s also about perception and transparency.
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Reliance on Social Media
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Riders frequently turned to platforms like Twitter and Reddit for better, faster information than what the MBTA app provided. Many mentioned specific accounts or subreddit threads where fellow commuters shared real-time updates about delays, train conditions, or crowding.
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While this peer-to-peer system was often more reliable, it was fragmented and not always accessible in the moment. This demonstrated a clear opportunity for a more integrated, commuter-driven update system within the transit app itself.
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Frustration with Redundancy
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Many users noted the inconsistency across different apps. For example, Google Maps might suggest one arrival time, while the MBTA app gave another, and unofficial apps provided yet another version of the truth. A parent commuter described it as:
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“I end up checking three apps just to piece together what’s actually happening. It shouldn’t take this much effort just to get to work.” This redundancy eroded trust and wasted valuable time, leaving riders frustrated with the lack of a single, reliable source of truth.
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The reliance on social media showed that commuters are already inclined to crowdsource their experiences, pointing to an untapped opportunity for the MBTA app to integrate these behaviors in a structured, user-friendly way.
Also note: most of the information about safety is centered around the T which is a part of the MBTA system. Since the T is underground it has more of a safety concern.
Quote from a 32 year old woman who commutes late at night:
“Before I leave my shift I want to know how long I will have to actually wait at the station, standing there alone is scary sometimes."
Usability Scenarios
Scenario A: You are rushing from the office to catch a meeting across town. You check the MBTA app, which simply says “Minor delays on the Red Line.” You take the risk, only to find the train delayed for 20 minutes. You arrive late.
Scenario B: You’re leaving a late work dinner. You feel uneasy walking into a poorly lit, empty station. If only the app could provide peer updates about safety or activity at that stop.
Scenario C: You’re coordinating with friends during peak hours. Each of you receives slightly different updates from different apps, causing confusion.These scenarios highlight the gap between official information and real commuter needs.
Journey Mapping
This journey mapping reinforced the emotional toll of unreliable information, anxiety, wasted time, and safety concerns.
From the combined research methods, three themes emerged:
Information Gaps: The official MBTA app provides updates that are too vague, late, or irrelevant to specific commuter needs.
Safety Awareness: Commuters, especially women and night travelers want more transparency about station environments.
Community as a Resource: Riders are already turning to social media for real-time clarity, showing the potential of integrating community-powered updates directly into a transit app.
Research Conclusion
The research phase revealed that Boston commuters don’t just want an app that reports delays, they want an app that helps them feel informed, safe, and connected. I chose to focus specifically on the T (Boston’s train system) rather than the entire MBTA network. The T represents the area where commuters experience the most pressing challenges, delays, lack of real-time clarity, and heightened safety concerns due to its underground nature. By narrowing in on the train system, I could better address these issues with a community-driven app designed to foster transparency, connection, and a greater sense of security for riders.