Computing the minimum Hausdorff distance for point sets under translation
SCG '90 Proceedings of the sixth annual symposium on Computational geometry
Computing the minimum Hausdorff distance between two point sets on a line under translation
Information Processing Letters
SCG '92 Proceedings of the eighth annual symposium on Computational geometry
Introduction to algorithms
Modeling and querying moving objects in networks
The VLDB Journal — The International Journal on Very Large Data Bases
Trajectory Similarity Search in Spatial Networks
IDEAS '06 Proceedings of the 10th International Database Engineering and Applications Symposium
Searching for similar trajectories in spatial networks
Journal of Systems and Software
Spatio-temporal Similarity Measure for Trajectories on Road Networks
ICICSE '09 Proceedings of the 2009 Fourth International Conference on Internet Computing for Science and Engineering
Flows in Networks
An incremental Hausdorff distance calculation algorithm
Proceedings of the VLDB Endowment
Computing with Spatial Trajectories
Computing with Spatial Trajectories
NNCluster: an efficient clustering algorithm for road network trajectories
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Nonmaterialized motion information in transport networks
ICDT'05 Proceedings of the 10th international conference on Database Theory
Searching for similar trajectories on road networks using spatio-temporal similarity
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
Spatio-temporal similarity analysis between trajectories on road networks
ER'05 Proceedings of the 24th international conference on Perspectives in Conceptual Modeling
Summarizing trajectories into k-primary corridors: a summary of results
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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Given a set of trajectories on a road network, the goal of the All-Pair Network Trajectory Similarity (APNTS) problem is to calculate the similarity between all trajectories using the Network Hausdorff Distance. This problem is important for a variety of societal applications, such as facilitating greener travel via bicycle corridor identification. The APNTS problem is challenging due to the high cost of computing the exact Network Hausdorff Distance between trajectories in spatial big datasets. Previous work on the APNTS problem takes over 16 hours of computation time on a real-world dataset of bicycle GPS trajectories in Minneapolis, MN. In contrast, this paper focuses on a scalable method for the APNTS problem using the idea of row-wise computation, resulting in a computation time of less than 6 minutes on the same datasets. We provide a case study for transportation services using a data-driven approach to identify primary bicycle corridors for public transportation by leveraging emerging GPS trajectory datasets.