[bazzargh]

I'm curious about why that was? From the graph showing the raam datapoints, there's a region with large gaps between points, and it would choose a track point that's well away from the original?

I've written some code to deal with this before (in my case, I wrote a distributed timer for cycle races, predicting current rider locations and gaps from sparse user reports). For me, finding nearest point on the segments of the polyline worked, but choosing only vertices would have made the time estimates terrible. Were the points somehow more fixed than that, eg towns/motels on the route?

[jfpuget]

The waypoints are not distributed regularly, but the track points are.

Here is why performance mattered in my case.

I needed to predict future positions of the cyclist (see https://www.ibm.com/developerworks/community/blogs/jfp/entry...). The computation relied mostly on weather forecasts provided for each track points.

I then needed to know where to start my computation, i.e. find the track point closest to the current location of the cyclist.