Building representative velocity profiles using FastDTW and spectral clustering
The use of map based representative velocity profiles allows to predict the future state of a vehicle. The suggested approach is based on Fast Dynamic Time Warping. Spectral clustering is used to distinguish velocity profiles. Applying abstraction can significantly reduce computation time with a minor effect on cluster allocation. Outlier removal increases the quality of cluster identification. The approach was applied to the road network of Munich, to prove the universal applicability.
FTM Smarte Mobilität
Book / Congress title:
14th International Conference on ITS Telecommunications