I'm an avid cyclist and want to reverse-engineer how Strava groups bike riders together. Here is their method to determine if cyclists are riding together (they use time and lat/lon of a ride): http://resources.esri.com/help/9.3/arcgisengine/java/gp_toolref/geoprocessing/proximity_analysis.htm

I want to create the algorithm and play with it in Tableau. The only methods I can think of are very computation intensive. The data has lat/lon every second. I then put a proximity zone of 150m around each point and then compare each and every point with other riders' locations at the same time. The result of each compare is 1 (yes) or 0 (no). After completing the comparison of every point, determine if the rider was within the proximity zone 70% of the time. With thousands of files to parse, this will take massive CPU power.

There must be a better way. I really want to add a proximity zone around each route. Then turn that route into some kind of "signature". I would then overlay the signature of one route to another adjusted for time to determine if two people rode their bikes together.

Can anyone point me in the direction of solving this problem?

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.