Inferring the Parametric Weight of a Bicriteria Routing Model from Trajectories

Abstract

Finding a shortest path between two nodes in a graph is a well-studied problem whose applicability in practice crucially relies on the choice of the applied cost function. Especially, for the key application of vehicle routing the cost function may consist of more than one optimization criterion (e.g., distance, travel time, etc.). Finding a good balance between these criteria is a challenging and essential task. We present an approach that learns that balance from existing GPS-tracks. The core of our approach is to find a balance factor α for a given set of GPS-tracks such that the tracks can be decomposed into a minimum number of optimal paths with respect to α. In an experimental evaluation on real-world GPS-tracks of bicyclists we show that our approach yields an appropriate balance factor in a reasonable amount of time.