Probabilistic range queries in moving objects databases with uncertainty
Proceedings of the 3rd ACM international workshop on Data engineering for wireless and mobile access
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
Reactive maintenance of continuous queries
ACM SIGMOBILE Mobile Computing and Communications Review
Context-aware optimization of continuous range queries maintenance for trajectories
Proceedings of the 4th ACM international workshop on Data engineering for wireless and mobile access
Adaptive schemes for location update generation in execution location-dependent continuous queries
Journal of Systems and Software
Developing a dynamic query system on location-based services
International Journal of Mobile Communications
Mining Frequent Trajectories of Moving Objects for Location Prediction
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Fast indexing and updating method for moving objects on road networks
WISEW'03 Proceedings of the Fourth international conference on Web information systems engineering workshops
Prediction of moving object location based on frequent trajectories
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Tracking network-constrained moving objects with group updates
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
Arrival time dependent shortest path by on-road routing in mobile ad-hoc network
W2GIS'04 Proceedings of the 4th international conference on Web and Wireless Geographical Information Systems
| Hi-index | 0.00 |
This work addresses the problem of updating Moving Objects Databases (MOD) using real-time traffic information. The motion of the object is represented by a trajectory, which can be constructed using the available electronic maps and the information about traffic patterns. However, the statistical information about traffic patterns may change due to accidents, extreme weather conditions, road work, etc.In this work, we present a model for updating the trajectories of moving objects when unexpected traffic conditions occur .Many sites provide an up-to-date information about traffic conditions on major express ways . However, the unexpected traffic conditions may affect not only the vehicles on the express ways for which an on-line monitoring is provided, but may also have an effect on the streets near those express ways. We propose a model of this spill-over effect and we utilize it in the process of identifying the trajectories which are affected by the abnormal traffic.