A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
A Spatiotemporal Model and Language for Moving Objects on Road Networks
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Indexing the Trajectories of Moving Objects in Networks*
Geoinformatica
Techniques for Efficient Road-Network-Based Tracking of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
On map-matching vehicle tracking data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Modeling and querying moving objects in networks
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient Cost-Based Tracking of Scheduled Vehicle Journeys
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
Location update strategies for network-constrained moving objects
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Effective map-matching on the most simplified road network
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Semantic trajectories modeling and analysis
ACM Computing Surveys (CSUR)
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To track network-matched trajectories of moving objects is important in a lot of applications such as trajectory-based traffic-flow analysis and trajectory data mining. However, current network-based location tracking methods for moving objects need digital maps installed at the moving object side, which is not realistic in a lot of circumstances. In this paper, we propose a new moving objects database framework, Euclidean-batch-sampling and Network-matched-trajectory based Moving Objects Database (EuNetMOD) model, to support network-matched trajectory tracking without digital maps installed at the moving object side.