Sparse Map-Matching in Public Transit Networks with Turn Restrictions

We investigate the following map-matching problem: given a sequence of stations taken by a public transit vehicle and given the underlying network, find the most likely geographical course taken by that vehicle. We provide a new algorithm and tool, which is based on a hidden Markov model and takes characteristics of transit networks into account. Our tool can be useful for the visualization of transit lines in map services, for transit data providers, and for an on-line matching of live passenger GPS data to a public transit vehicle. We evaluate our tool on real-world data, and compare it against two baselines. The shapes produced by our tool are very close to the true shapes. We have made our software publicly available, enabling full reproducibility of our results.