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Mapping the most convenient ways to meet someone with public transit

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Hello!I built a map that generates a heatmap of the most convenient meeting spots between several people, based on public transit travel times.Move the markers anywhere in the map; all cities with sufficient transit data are supported!

HN · launched Mar 24, 2026 · 16 upvotes (top 30%) · 0 views

Niche: specialized navigation and tracking apps · 203 launches, 35 in the last 7 days ▲ +84% · Explore this niche →

Category and tags

  • Travel & hospitality
  • Search & retrieval
  • B2C
  • Not AI
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

Partial While rendering maps and heatmaps in frontend libraries is simple, computing multi-origin isochrones across real-world transit networks requires high-performance routing engines and heavy GTFS data processing.

What it would actually take: The stack would involve Leaflet/Mapbox on the frontend with a specialized transit routing backend like OpenTripPlanner, Valhalla, or custom RAPTOR implementations. Generating multi-origin heatmaps involves computing many-to-many travel times over full GTFS schedules, which quickly creates combinatorial scaling issues without efficient graph algorithms. Processing and caching national/global GTFS datasets in memory requires transit data pipeline engineering.

Discussion

2 comments analyzed.

Concerns raised: Infinite loading when insufficient data coverage, Limited transit data availability in some regions

Feature requests: Add warning when area lacks sufficient routing data

Competitors

Other products that read as similar to this one : 142 launches clear the similarity bar, closest 8 shown.

Attention rank: #52 of 143 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 103 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.