evanzyang91

evanzyang91 / transit-planner

Public

🚇 Build your own transit infrastructure with AI insights and comprehensive data

transit-planner-web.vercel.app
13
2
100% credibility
Found Mar 14, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

An interactive map-based tool that uses AI agents simulating a Toronto city council to debate, design, and approve new transit routes in real-time.

How It Works

1
🌐 Discover the tool

You land on a stunning 3D globe of Toronto showing spinning transit lines, inviting you to plan better public transport.

2
🗺️ Dive into the map

Click to enter an interactive map of Toronto with real transit lines, neighborhoods, population heat, and traffic overlays.

3
🔍 Pick your area

Click neighborhoods or existing stations to highlight underserved spots, or draw a custom boundary for your transit need.

4
🤖 Launch the AI council

Hit 'Generate Route' to watch a lively debate unfold live—AI experts argue costs, residents, equity, and PR in real time while the map updates.

5
🎤 Hear the discussion

Voices narrate each speaker's key quotes as routes evolve on the map, feeling like a real city hall meeting.

✅ Get your approved plan

Celebrate the final approved route with cost estimates, timelines, and stats—ready to share or refine your transit vision.

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Star Growth

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AI-Generated Review

What is transit-planner?

Transit-planner lets you build your own transit infrastructure for Toronto using AI insights and real-time geospatial data. Draw boundaries or select neighborhoods and stations on an interactive Mapbox map, then trigger a simulated city council where specialized AI agents debate routes across six rounds, streaming updates live with voice narration via ElevenLabs. The TypeScript Next.js frontend pairs with a Python FastAPI backend pulling PostGIS data for realistic proposals.

Why is it gaining traction?

It hooks devs with multi-agent AI deliberation that feels like real urban politics—ridership planners vs. NIMBY residents—while rendering subway paths instantly on the map, complete with population density and traffic overlays. No alternatives blend LLM council debates, 3D globe landings, and editable routes this engagingly, making it prime for building own AI agent demos or transit planner prototypes.

Who should use this?

Urban planners mocking up lines for stakeholder buy-in, AI devs experimenting with geospatial agents, or Toronto transit hackers building github portfolio projects around custom AI councils. Great for frontend teams wanting to build github app with live SSE streaming and Mapbox integration.

Verdict

Fork this Hack Canada winner to build your own AI transit planner or github copilot agent—code runs smoothly via Docker and GitHub Actions despite 13 stars and 1.0% credibility score. Maturity shows in polished UI and data flow, but expect tweaks for production scale.

(198 words)

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