Multi-Surface
Experience System
6 coordinated surfaces · Real-time state · Physical + VR prototyping · AI interaction
Client
Glydways
Role
Principal Design Technologist
Year
2025 — Present
Tools
Unreal Engine 5 · Figma · Swift · Arduino · Python · ElevenLabs
01
The Problem
Glydways is building a new category of autonomous transit — small, on-demand pods operating in dedicated guideways. No prior design patterns exist for how a rider should be onboarded, guided, and comforted through an experience that has no driver, no conductor, and no established behavioral script.
The brief had to be written before the work could begin. That meant defining what the experience even was — across physical space, digital surfaces, acoustic environment, and thermal comfort — before designing any of it.
And it had to be answered the only way a question like this can be: put real people inside it, repeatedly, and watch what they do. Except there was no vehicle to put them in. Hardware arrives across the organization in pieces, on engineering's schedule, and when a unit does come online it is a strained resource — engineering needs it close to exclusively to do their own work. A design team queueing for access to the real thing would not have run a single session.
So the means of execution had to be designed too. Two environments the design team owned outright, available on demand, each standing in for what the vehicle could not yet provide — and each honest about the half of the problem it could not reach.
“There was no vehicle to test in. Waiting for one was not a plan, so we built the two we needed.”
02
System Architecture
Coordinating across six surfaces simultaneously — each with its own timing, fidelity, and failure mode.
Kiosk
Access point · Ticketing · Wayfinding
VMS
Variable message sign · Platform status
In-Cabin Display
Onboarding · Journey state · Egress
Lighting
Interior + exterior state signaling
Audio
AVAS · In-cabin AI interaction
Mobile App
Booking · Destination · Ride status
All six respond to a single state event — boarding, in-transit, arrival, emergency — carried over WebSocket across Arduino, iOS, and Linux devices. Building that coordination in hardware is its own story: the UXR lab rig.
03
At Scale
A bench can only ever be one pod. Scale — a fleet in service, several access points, a rider moving between touchpoints on a real street — has to be built somewhere else.
So the same system was rebuilt in Unreal Engine 5 and walked end to end in VR: first-person, hand-tracked, from booking on the phone through platform signage, boarding, the ride itself, and arrival. Every surface runs on the same state model as the physical rig.
UE5 — end-to-end rider journey: booking, platform, boarding, cabin
04
The Real Counterpart
The same system also exists on a bench the design team built and kept — displays, lighting, audio, and an NFC boarding tap wired to one coordinator, running whenever a session needed it rather than whenever a vehicle was free. It cannot show a fleet or a street, but it is real, at real brightness and real volume, which is where embodied response actually comes from.
Lab prototype — kiosk & station mockup
UXSync — prototype coordination (localhost)
Neither medium is the validation environment for the other. They are two instruments with opposite bargains, and choosing between them per question is the method.
VR
Buys scale and continuity — a fleet, a street, one unbroken journey across every touchpoint. Pays in fiction: participants know it is not real, so findings are directional, strong on sequence and legibility, weak on comfort and stress.
Physical rig
Buys embodied response — disbelief actually suspends, and the acoustic and timing findings come from here. Pays in reach: one pod, one context, no network. Built and instrumented subsystem by subsystem in the UXR lab.
05
Outcomes
6
Coordinated surfaces
Kiosk · App · VMS · Display · Lighting · Audio — all responding to a single state event
0→1
Zero prior patterns
No existing UX conventions for autonomous transit rider experience to reference or adapt
2
Prototyping media
A bench rig for embodied response, a UE5 build for fleet scale — both design-owned, neither waiting on vehicle access
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