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TRANSITA (temp name)
License: GPLv3
A superior public transit app.
It seems like this is the sort of app that should be built as an open-source project.
(It's also surprising that after 2 years no one's done what seems like pretty obvious
functionality for a transit app, so, no time like the present to get started I guess.)
Target Platforms
* public RESTy API for transit data, prediction proxying
* Android version (thanks to Bradley Horowitz, see: )
* Eventually targeting: Pure HTML5, Palm Pre, Phone Gap
* Start w/ sfbay since
1) I live here and
2) gives full data dumps and
3) BART and NextMuni gives full realtime data
v1 should provide for loading of any GTFS data for use w/ transit systems that provide them.
* REST API for data
* Proxy for realtime data
* Caching or full local DB of stops, routes, tiles
* Collecting data on favorite routes, stops, destinations
* Reverse chronological history of searched (maybe even taken) routes
* Easy reversals or routes, destinations
* Seeing route lines
Route Choosing:
* visually lay out alternative routes
* pull in realtime data
* show more info on arrivals time, transfers
* Reminders for last return trip if you're out on the town
* Alarms for longer commuter trips (geoloc/time elapsed, absolute time)
* "First time" / "lost" affordances - what are the previous stops, where are you now, etc.
* Good "offline" support (precaching areas, definitely routes)
* dialing commuter help where available
Nearby View:
* See nearby stops, specifically when they're coming.
This is especially useful if you know that multiple routes can take you to the same place... (I can take the 26, 14/49, or BART to get back home)
v2 (the fun stuff)
Integration w/ Glympse would be interesting.
Along those lines, the next thing that would be of interest to tackle (v2) is NYC - b/c of the Subway/undergroundness of it all and lack of any "real time" data, the NYC version would be focused on developing crowdsourcing capabilities - ie, when you head into and out of a Subway station, perhaps the ability to mark in/out times and aggregating and processing that data. I haven't fully thought through the algorithms, but I bet just by when people are leaving at previous stops you can find out if you're looking at a 5m or 25m wait...
Once this sort of algorithm is perfected, if it'll work in NYC, it'll work (better!) for any city that has aboveground transit (buses) w/ schedules but no exact times...
For some earlier work I've done (this goes back to RFID beaconing and piconet stuff I was playing around w/ back in grad school):