How might campus transit adapt to student wellness without becoming surveillance? Ran co-design workshops and prototyped an app grounded in the key finding: people want systems that adapt for groups, not individuals.
Timeline
4 Weeks, Fall 2025
Team
3 People
My role
UX Design & Prototyping, Futures Scenario Development, Workshop Documentation & Synthesis
Wearable wellness technologies are becoming increasingly integrated into daily life through sleep tracking, stress monitoring, and biometric feedback systems. We explored what happens when these technologies intersect with public infrastructure like campus transit.
How might mobility systems adapt to student wellbeing without creating surveillance or over-optimization?
To explore this tension, we used futures thinking to imagine both desirable and undesirable mobility futures shaped by wellness technology, accessibility, and behavioral data.
We developed two contrasting 2050 futures to explore how wellness-integrated mobility systems might evolve over time.
The preferred scenario, Connected Care in Motion, imagined transit systems that supported wellbeing collectively through accessible technology, environmental adaptation, and shared care infrastructures.
The undesirable scenario, The Optimization Trap, explored the risks of hyper-personalization, surveillance, and algorithmic pressure shaping everyday mobility experiences.
We then backcasted from these futures to explore what a near-term mobility system in 2027 might look like.
To connect these speculative futures to existing mobility experiences, we analyzed current campus transit systems and accessibility gaps through service blueprinting and WCAG evaluation exercises.
We focused on moments of uncertainty, cognitive overload, and accessibility friction across the commuting experience, particularly around:
confusing wayfinding,
fluctuating ETAs,
limited multimodal support,
and transit stress during time-sensitive commutes.
One recurring insight was that uncertainty itself created stress. Students often described wanting clearer guidance and reassurance during transit rather than additional optimization or behavioral nudges.
Using backcasting methods, we translated the 2050 vision into a near-term mobility service grounded in existing transit behaviors and technologies.
AuraRoute explored how campus transit could support wellbeing through:
optional personalization,
environmental comfort indicators,
accessibility-first navigation,
and community-informed mobility insights.
Rather than relying on continuous biometric surveillance, the system used lightweight, opt-in inputs such as commute preferences, accessibility settings, and optional wellness integrations.
The goal was not to optimize individuals, but to reduce stress, uncertainty, and cognitive load across the commuting experience.
We then ran participatory workshops with students, faculty, and practitioners to explore how people imagined the future of mobility, wellness, and accessibility evolving over time.
The workshops were designed to move from personal reflection toward collective future-building through activities including:
mood check-ins,
commute storytelling,
speculative “pick-a-path” exercises,
future postcards,
and embodied journey simulations.
Rather than evaluating the interface directly, the workshops explored broader questions around comfort, privacy, uncertainty, social connection, and collective care in mobility systems.
While the project initially explored highly personalized wellness-integrated transit, workshop participants consistently pushed back against systems centered around biometric profiling and individual optimization.
Instead, they imagined systems that improved mobility collectively through:
clearer wayfinding,
reduced uncertainty,
shared environmental support,
and optional social interaction.
Participants repeatedly emphasized that stress often came from unpredictability and cognitive overload rather than lack of personalized data.
This shifted AuraRoute from designing for optimization toward designing for collective care.
Workshop findings directly shaped several aspects of the final prototype.
For example:
participants describing buses as physically uncomfortable led to the addition of air quality indicators and “Fresh Air System” route tags,
uncertainty around navigation reinforced the decision to prioritize voice guidance and anticipatory notifications,
and discussions around multimodal mobility expanded the system to include bike-route options and broader accessibility support.
The final prototype emphasized low-friction interaction, optional personalization, and accessibility-first navigation rather than intensive biometric optimization.
One of the biggest takeaways from this project was how differently participants defined “supportive” mobility experiences than we initially expected.
While our early concepts leaned toward highly personalized optimization, participants consistently preferred systems that reduced uncertainty, supported accessibility collectively, and preserved autonomy through optional interaction and privacy-aware design.
The workshops also revealed how much everyday transit stress comes from small moments of friction like confusing wayfinding, unpredictability, crowding, and sensory discomfort, rather than lack of data or personalization alone.