A Trajectory Collaboration Based Map Matching Approach for Low-Sampling-Rate GPS Trajectories

Wentao Bian, Ge Cui, Xin Wang
2020 Sensors  
GPS (Global Positioning System) trajectories with low sampling rates are prevalent in many applications. However, current map matching methods do not perform well for low-sampling-rate GPS trajectories due to the large uncertainty between consecutive GPS points. In this paper, a collaborative map matching method (CMM) is proposed for low-sampling-rate GPS trajectories. CMM processes GPS trajectories in batches. First, it groups similar GPS trajectories into clusters and then supplements the
more » ... ing information by resampling. A collaborative GPS trajectory is then extracted for each cluster and matched to the road network, based on longest common subsequence (LCSS) distance. Experiments are conducted on a real GPS trajectory dataset and a simulated GPS trajectory dataset. The results show that the proposed CMM outperforms the baseline methods in both, effectiveness and efficiency.
doi:10.3390/s20072057 pmid:32268569 fatcat:jjfamsfwvzdofl27gdu6dn4eiq