A weighted clustering algorithm for clarifying vehicle GPS traces

This paper presents a weighted clustering algorithm based on the physical attraction model, which improves the physical attraction model by assigning a different weight to the position points on a GPS trace for a fast convergence according to their velocity and directional changes. The physical attraction model pulls together traces that belong on the same road in response to simulated potential energy wells created around each trace. Assuming a vehicle with a high velocity has a little derivation to the road it runs on, we assign a high weight to its trace in the physical attraction model so that the clustering progress converges rapidly and closely to road. Within the clustering process, an angle-threshold based smoothing filter is appended to keep the consistency between the changes of those points on the adjusted trace at each loop. This algorithm was demonstrated to enable to effectively clarify those vehicle GPS traces on the same road. In comparison of previous work, it also shows an improved quality grouping GPS traces near road-crossing area by embedding the smoothing filter in clustering process.