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Lab Notebook · Rail Domain Line

Designer-quality PIDS screens with AI-assisted design — for a global transit programme

An advanced Passenger Information Display System built for a global transit passenger-information programme (name withheld), with AI-powered design assistance and a drag-and-drop widget system — proof AI can meaningfully assist visual and UX decisions on a safety-critical display, not just generate code.

JR
Jon RossFounder, vocabotics — 15 years building safety-critical systemsLab report · dated 1 August 2025
Verified by a human. Drafted with AI, verified by a human. Jon Ross, 1 Aug 2025
Living document. Reviewed 1 Aug 2025
Entry date
1 August 2025
Category
Tooling
Access
🔓 Public
Shipped & measuredProven

A functional-but-plain passenger display became designer-quality with AI in the loop — on a screen where legibility under pressure is a safety constraint, not a preference.

React/TypeScript + Vite
frontend stack
AI designer
assisted theme customisation feature, shipped

Honest evaluation

Proven

The improvement is real and delivered, but reported as a qualitative shift ("functional-but-plain to designer-quality"), not a measured figure — stated as such rather than inflated into a number.

What would prove or disprove it further

What would prove or disprove it further: a structured before/after design review (task-completion time, error rate, or a panel rating) against the same screens would convert "designer-quality" from a qualitative judgement into a measured one, and either strengthen or puncture the claim with a number instead of a description.

The evidence — full reasoning behind the verdict

Verdict: proven. The claim was that AI-assisted design tooling could meaningfully improve a safety-relevant passenger display's visual and UX quality without taking judgement away from a human designer — and a shipped, working, delivered system carrying an AI-assisted "designer" feature and a drag-and-drop widget layer is real evidence for that, not a demo reel.

The evidence is qualitative rather than a number, and the report says so directly: the result is described as moving the PIDS "from functional-but-plain to designer-quality," not as a measured percentage improvement. That's an honest way to report a genuinely subjective outcome — legibility and visual coherence aren't naturally single numbers — but it does mean this verdict rests on delivered, working software and a stated qualitative judgement, not a hard metric. The boundary the report holds carefully — AI assisted the designer's decisions, it did not set the legibility/contrast/glanceability constraints itself — is exactly the claim being tested, and it holds.

A passenger information display that works is one thing; a passenger information display that's legible, coherent, and actually well-designed under real operating conditions is a different, harder bar. This project put AI design assistance directly in front of that bar.

What it was

An advanced Passenger Information Display System (PIDS) built for a global transit passenger-information programme — the operator is withheld by name per our policy of never naming clients in safety-critical/transit work. The system included AI-powered design assistance and a drag-and-drop widget system for building display layouts.

What we built

Shipped & measured

A working React/TypeScript frontend on Vite, with an LLM API driving an "AI designer" feature: theme customisation and layout suggestions generated with AI assistance, on top of a drag-and-drop widget system for assembling what actually appears on a passenger screen. The system shipped and worked.

What we learned — including the honest negative

The real result was qualitative, not a number: this took a PIDS from functional-but-plain to designer-quality, with AI meaningfully assisting visual and UX decisions rather than just generating boilerplate code. That's a genuinely different kind of AI-assistance claim than "it wrote the CRUD layer" — here it was helping shape what a passenger actually sees and reads at a glance.

The honest edge is exactly that boundary: design assistance, not design autonomy, on a display surface where the cost of getting legibility wrong is real.

Where it went / status

Working and delivered, sitting alongside the operations-control side of the same domain (see the rail PA/PIDS platform) as one of two production passenger-information systems built the same year — one running the control plane, this one making the screens themselves better designed.

What is still open — kept visible

The honest edges, next to the wins. This is what turns 🔬 into 🟢 — honestly.

  • The transit authority this was built for is withheld by name, per our no-client-names policy — described here only as "a global transit passenger-information programme."
  • AI-powered design assistance augmented a human designer's decisions; it did not replace design judgement, particularly for the safety-relevant legibility constraints a PIDS has to meet.

Where this connects

Sources

  1. vocabotics project audit — Transit PIDS AI design system (client withheld), Aug 2025vocabotics internal project history · as of August 2025

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