Ever wanted to meet up with friends after work, but struggled to find a good spot that’s easy for everyone to get to? That was a frustration I had when I first moved to San Francisco, which led to the idea for an app that would locate optimal meeting places based on travel times. I built the app, “Common Ground”, with 3 friends at Hack Reactor coding bootcamp. To find a meeting place, you enter each person’s location and where you want to meet (e.g. “bar” or “Chinese food”), then the app generates results that are easy for everyone to get to. You can also select different travel modes for each person - walk, bike, drive or transit.

Common Ground

Distance vs Time

Crucially, that app doesn’t simply find geographically central locations - it minimizes travel times. This means that a restaurant near a subway stop, for example, might show up higher in the results than a closer restaurant not near a stop. I developed the algorithm that locates places, which works as follows: first it casts a wide net, using Yelp’s API to generate a list of potential candidate meeting places in the general vicinity. It then samples those places, using Google’s Directions API to identify clusters which minimize total travel time. This process is repeated until 10 optimally located places are found, which it serves ranked by travel times. I later added in weight for travel equity to the algorithm, to help prevent one individual from having a significantly longer travel time than everyone else.

The site is no longer live, but you can find the code here.