Shortest-path and minimum-delay algorithms in networks with time-dependent edge-length
Journal of the ACM (JACM)
Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Cost and Imprecision in Modeling the Position of Moving Objects
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
On map-matching vehicle tracking data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Addressing the Need for Map-Matching Speed: Localizing Globalb Curve-Matching Algorithms
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Finding time-dependent shortest paths over large graphs
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Scalable network distance browsing in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Continuous probabilistic nearest-neighbor queries for uncertain trajectories
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Indexing the Trajectories of Moving Objects in Symbolic Indoor Space
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Graph Model Based Indoor Tracking
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
MOIR/MT: monitoring large-scale road network traffic in real-time
Proceedings of the VLDB Endowment
Effectively indexing uncertain moving objects for predictive queries
Proceedings of the VLDB Endowment
Probabilistic path queries in road networks: traffic uncertainty aware path selection
Proceedings of the 13th International Conference on Extending Database Technology
Spatio-temporal network databases and routing algorithms: a summary of results
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
T-drive: driving directions based on taxi trajectories
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Algorithms for compressing GPS trajectory data: an empirical evaluation
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Probabilistic range queries for uncertain trajectories on road networks
Proceedings of the 14th International Conference on Extending Database Technology
Modeling of Traffic-Aware Travel Time in Spatial Networks
MDM '13 Proceedings of the 2013 IEEE 14th International Conference on Mobile Data Management - Volume 01
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Route planning and recommendation have received significant attention in recent years. In this light, we propose and investigate the novel problem of finding traffic-aware fastest paths (TAFP query) in spatial networks by considering the related traffic conditions. Given a sequence of user specified intended places Oq and a departure time t, TAFP finds the fastest path connecting Oq in order to guarantee that moving objects (e.g., travelers and bags) can arrive at the destination in time. This type of query is mainly motivated by indoor space applications, but is also applicable in outdoor space, and we believe that it may bring important benefits to users in many popular applications, such as tracking VIP bags in airports and recommending convenient routes to travelers. TAFP is challenged by two difficulties: (i) how to model the traffic awareness practically, and (ii) how to evaluate TAFP efficiently under different query settings. To overcome these challenges, we construct a traffic-aware spatial network Gta(V,E) by analysing uncertain trajectory data of moving objects. Based on Gta(V,E), two efficient algorithms are developed based on best-first and heuristic search strategies to evaluate TAFP query. The performance of TAFP has been verified by extensive experiments on real and synthetic spatial datasets.