Matching up for a carpool is too complicated. Why enter data that is already known?

How it works

You opt in to share your GPS data from your daily routine. Our advanced data analytics engine will cross-correlate your commute with our aggregate data.

We analyze:

  • other commuters for ride sharing
  • bikeshare routes
  • carshare lots
  • The Bus Routes

We will then email you with the perfect match for your commute. We will even email you if a potential new commute partner may offer an even faster commute.

Challenges I ran into

  • Finding already existing data to test with was very difficult -- The Bus data was too late and I spent most of my time creating an interface to get routes from Google Maps API.

Accomplishments that I'm proud of

  • I was able to get Google Maps to return routes that I could generate a correlation score with other * routes. Not giving up and getting something submitted.

What I learned

One man projects are hard :) Creating a spatial query to match routes are also hard.

What's next for

Getting a large dataset for real algorithm development

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