Project 07 · Contextual Inquiry · UX Research
RU Radar Rutgers Campus Bus Tracker

Making campus
transit legible
for everyone

A contextual inquiry study into how Rutgers students navigate campus using RU Radar — and a prototype that rethinks the final mile from bus stop to destination.

Project Type Graduate Research — Contextual Inquiry
Course 16:137:532 · Dr. Misra
Year 2025
Methods Contextual Interview, Affinity Diagram, Prototyping
Participants 6 Rutgers Students
02 — The App

RU Radar is useful —
until it isn't

RU Radar is an iOS-exclusive campus bus tracking app built specifically for Rutgers University students. It shows live bus locations, real-time arrival estimates, and route status. For a single-route trip, it's fast and reliable. But the moment a student needs to plan a multi-stop journey or figure out the last mile on foot — the app leaves them stranded.

The app has no destination search. No transfer planning. No walking directions after you step off the bus. Android users are locked out entirely. The result: students memorize routes, improvise on arrival, and supplement with Google Maps for everything RU Radar can't do.

RU Radar routes list showing Weekend 1, A Route, B Route and others
RU Radar map view showing Weekend 1 route with bus stop markers
RU Radar dark map view showing routes near Somerset and Werblin Recreation Center

Current RU Radar UI — Routes list, live map (light), live map (dark)

iOS
Only platform — Android users have no access
0
Destination search or trip planning features
3
Core tasks tested with 6 participants
5/6
Participants struggled with multi-stop transit planning
Compared to alternatives

Where RU Radar stands

🎯 RU Radar
  • Live bus locations
  • Clean, focused UI
  • Rutgers-specific routes
  • iOS only
  • No destination search
  • No transfer info
  • Inaccurate ETAs
🗺 Google Maps
  • Destination search
  • Turn-by-turn walking
  • Transfer planning
  • Cross-platform
  • Rutgers bus data often stale
  • Not campus-aware
🚌 PassioGo
  • Shows driver break status
  • More accurate stops
  • Complex UI
  • Less familiar to students
  • No walking directions
03 — Research Approach

Phenomenological
contextual inquiry

We conducted a phenomenological study — exploring the lived experience of using RU Radar, not just measuring task success. Six Rutgers students were interviewed over Zoom, each walking through three structured tasks while thinking aloud. Interviews were recorded, transcribed, and interpreted as a team.

6
Final participants (after 3 pilot interviews)
4M / 2F
Gender split across participants
23.8
Average age of participants
45 min
Per interview session via Zoom
Participant profile
🎓
Participant 1
23 · Male · Data Science MS
7 months at Rutgers · No car
🎓
Participant 2
27 · Female · Graduate student
1.5 years at Rutgers · No car
🎓
Participant 3
25 · Male · Graduate student
Near bus stop · Daily rider
🎓
Participant 4
22 · Female · Undergraduate
Regular commuter · Has car
🎓
Participant 5
24 · Male · Graduate student
Near bus stop · Daily rider
🎓
Participant 6
23 · Male · Graduate student
Near bus stop · Frequent rider
Three-stage interview structure
1
Route Tracking

Track routes EE, A, and B on RU Radar. Find the current position of buses and locate capacity info. This task tested the app's core function — the one it does best.

"It is easy to view, initially it was difficult, but once I got familiar with the routes, it got easy." — P2

Easy
2
No-Transit Trip Planning

Plan a trip from Rutgers University Inn to Busch Student Center — a single-bus route with no transfers needed. Most found this possible but slow due to no destination search.

"If it can show me the distance and ETA to walk to the nearest stop, it would be much better." — P1

Moderate
3
Transit Planning with Transfer

Plan a trip from Rutgers University Inn to the SERC Building — requiring a transfer between routes. Nearly every participant found this task too difficult or impossible without Google Maps.

"It doesn't show me the buses I need to take to go from Rutgers Inn to SERC. I need to manually check which buses go there." — P1

Hardest
04 — Interview Findings

What participants
told us

Across all six interviews, a consistent picture emerged: RU Radar is reliable for checking bus times, but completely breaks down when students need to go somewhere unfamiliar. The pain wasn't frustration with the app's core — it was the gap between "I know the bus is coming" and "I know how to get where I'm going."

"Sometimes, the buses ETA is wrong — it makes me wait too long and I miss my classes."
— Participant 1 · Master's in Data Science
"When a bus driver goes on a break, it doesn't show as bus dwelling — whereas in PassioGo it shows."
— Participant 1 · on feature gap vs. PassioGo
🔍
No Destination Search

The most frequently requested feature. Students can't type a destination and get a route — they have to manually find the right bus themselves.

Inaccurate ETA

The app's arrival estimates don't account for stops along the way or driver breaks — causing missed classes and missed connections.

🔄
No Transfer Information

Multi-stop trips require students to manually cross-reference routes. The app gives no guidance on where or when to switch buses.

🚶
No Walking Directions

After exiting a bus, students are on their own. No indication of which direction to walk, how far, or which entrance to use.

📱
iOS Only

Android users — a significant portion of the student body — have no access to the app at all, forcing them to rely on Google Maps entirely.

🗺
Manual Route Finding

Students must know route names (A, B, EE) before they can use the app. There's no way to search by campus or building name.

Overall experiences

In Stage 3 interviews, four of six participants said they would prefer driving if they had a car — revealing that bus reliance is driven by necessity, not preference. The most common requested feature across all participants was destination-based trip planning, followed by improved ETA accuracy.

05 — Key Insights

Interpreting
the evidence

After interviews, the team synthesized findings using an Affinity Diagram and a Day-in-the-Life model — two research tools that help transform individual observations into shared patterns.

Affinity diagram — user experience of RU Radar
Affinity diagram mapping RU Radar user experience into categories: features working good, things that can be improved, features absent, and user wants

Affinity diagram clustering interview notes across 4 thematic columns

Day-in-the-life model
Day-in-the-life model showing a Rutgers student's journey: Home → On the Way → Arrived at Campus → On the Way Back, with questions and emotions at each stage

Contextual model showing how RU Radar fits — and fails — across the full commute journey

📍
The "Last Mile" Gap

Students consistently reach a dead-end after getting off the bus. The app's job ends at the stop — but the student's journey doesn't.

🧠
Route Knowledge as Barrier

The app requires students to already know route names. New students spend weeks learning the system before RU Radar becomes useful.

📲
Dual App Behavior

Most participants use both RU Radar and Google Maps — RU Radar for live tracking, Google Maps for everything else. The app could close this gap.

Design Question
"How might we extend RU Radar's helpfulness from the moment a student decides to travel — all the way to arriving at the right entrance of the right building?"
06 — Design Opportunities

From insight
to opportunity

The storyboard below captures the core user journey we designed around: a student deciding to catch a bus, wondering which one to take, boarding successfully, and then facing confusion again at the destination. Each design opportunity addresses one moment in this story.

Final storyboards — four user scenarios

We developed four storyboards mapping distinct moments in the student journey — from first deciding where to go, to comparing route options, riding the bus, and finally navigating the last mile to their destination.

Storyboard 1: Making Travel Plans — trip planner wireframe with departure and destination fields, saved plans view, and pop-up plan options on map
Storyboard 1
Making Travel Plans

Enter departure + destination, view Plan A/B/C options above the map area. Bookmark and save routes for reuse.

Storyboard 2: Comparing and selecting a plan — plan list with sort options, detailed plan view showing route A → EE with walk segments and ETA
Storyboard 2
Comparing & Selecting a Plan

Sort plans by time of arrival, less walk, less transit, less crowded. Expand for full step-by-step breakdown with ETA.

Storyboard 3: Starting the trip and on the way — bus tracking with trip progress bar, bus info with capacity, full timetable, report for wrong status
Storyboard 3
Starting the Trip & On the Way

Live trip progress tracker, bus capacity at 58%, full timetable on click, report button for wrong bus status.

Storyboard 4: Arriving at the destination — trip status screen, walking navigation turn-by-turn, feedback for wrong bus/walking info, arrived flag
Storyboard 4
Arriving at the Destination

Walking navigation with "Turn right at the cross road" guidance, feedback for unsatisfied parts, arrived flag.

Vision boards — concept exploration

Before finalising the prototype, the team sketched three vision boards exploring the complete user journey and system architecture — mapping how destination search, trip planning, live tracking, and last-mile navigation could all connect.

Vision board 1: Full user journey sketch showing check location → plan ride → take bus → check stop → arrive at Science Building, with annotated UI wireframes
Vision 1
Full Journey Map
Vision board 2: 'I should go to campus' — search destination, choose plan, live bus info with direction indicators, retake previous trips, arrive at destination
Vision 2
Destination-First Flow
Vision board 3: Simple flow — I need to meet a friend → car or bus? → route map → start trip → walk 5 min to board → stop arrived → arrived at building
Vision 3
Simplified Journey
Four design opportunities
🗺
Destination Search + Trip Planning

Let students type a campus building or destination and receive a complete bus route — including transfers — without prior knowledge of route names.

🚶
Walking Directions After Bus

Once a student exits the bus, provide multiple walking route options (Fastest / Easiest) from the stop to their destination with ETA estimates.

🔗
3rd-Party Navigation Integration

Allow students to hand off to RU Radar, Google Maps, or Apple Maps for turn-by-turn directions — meeting them in the app they already know.

⚠️
Issue Reporting

Enable students to report inaccurate ETAs, driver breaks not displayed, or bus overcrowding — building a feedback loop to improve data quality.

07 — Prototype

Four screens,
four solutions

The prototype was tested with two scenario-based interviews. Testers navigated trip planning and issue reporting tasks, and their feedback directly shaped the design iterations. Each screen addresses one identified pain point.

Prototype screen: Walking route options from Hill Center bus stop to SERC Building. Shows Fastest: 7 min (800m) and Easiest: 10 min (900m) with Start buttons
Figure 11 — Arrival Screen
Walking Route Options After Bus

After alighting at the Hill Center bus stop, the app presents multiple walking routes to the destination — labelled Fastest and Easiest — with time and distance for each. No more guessing which direction to walk.

Prototype screen: 'Open the map in' modal with three options — RU Rader (highlighted in red), Google Map, Apple Map
Figure 12 — Nav Handoff
3rd-Party Navigation Integration

A contextual modal lets students choose their preferred navigation app for turn-by-turn directions. RU Radar is the default option — but students who trust Google Maps or Apple Maps can use those instead.

Prototype screen: Turn-by-turn navigation showing 5 min (500m) to destination, with step-by-step walking directions: Get off at Hill Center bus stop → Walk straight along sidewalk → SERC Building main entrance
Figure 13 — Navigation Screen
Turn-by-Turn Natural Language Directions

Clear, step-by-step walking instructions in plain language — "Walk straight along the sidewalk for approximately 50m. The SERC Building will be ahead of you." Removes all ambiguity from the final walk to class.

Prototype screen: 'Report the issues' modal with a dropdown 'What happened?' and Cancel/Send buttons, overlaid on the in-progress navigation screen
Figure 14 — Reporting Screen
Issue Reporting Feature

A lightweight modal lets students flag problems (inaccurate ETA, driver break, overcrowding) directly during their journey. Prototype testing revealed the need for a confirmation message after submission — an iteration made in response to user feedback.

Prototype testing insights
"The user was able to locate the starting point and generate a route — but was unsure how to exit the route planning page."
— Tester 1 · Task 1 observation → led to adding clear back/close button
"The user understood the issue reporting interface — but after submission, was unsure whether their report had been successfully sent."
— Tester 1 · Task 2 observation → led to adding confirmation message
08 — Reflection

What I learned

This was my first deep contextual inquiry study — not just asking users what they think, but observing what they actually do. The gap between what people say about an app and what they struggle with in practice turned out to be the most important thing we uncovered.

01
Task difficulty reveals mental models

The fact that Task 1 was easy while Task 3 was nearly impossible told us as much as the interviews did. The app's mental model (routes first, destinations never) is misaligned with how students actually think about getting somewhere.

02
Prototype testing changes your assumptions

We built screens we were proud of — and testers immediately found edge cases we hadn't thought of. The "no clear exit button" and "no submission confirmation" were both surprises that made the final design better.

03
Integration > replacement

Students didn't want a new app — they wanted RU Radar to do what it does, and also hand off gracefully to other tools. The 3rd-party navigation integration came directly from realizing students already live in multiple apps.

04
Affinity diagrams make patterns visible

Running the affinity diagram session as a team — not solo — surfaced patterns none of us had seen individually. The "no transit information" cluster emerged from five separate participants saying slightly different things that meant the same thing.

Team

Contextual Inquiry 16:137:532 · Group 7 · Rutgers University · 2025

Aashish Reddy Kandi
Chia-Chia Lia
Feiyang Wu
🎤
Contextual Interviewing

Conducted and moderated participant sessions, collected verbal and non-verbal data

🗂
Affinity Diagramming

Led team synthesis session to cluster interview notes into patterns and themes

📱
Prototype Design

Designed four prototype screens addressing the key journey gaps identified in research

🧪
Prototype Testing

Conducted scenario-based usability sessions with new testers to validate design decisions

📋
Research Documentation

Authored participant consent forms, interview protocol, and final research report

📊
Data Analysis

Analyzed transcripts for recurring themes, cross-participant patterns, and design implications