Effective graph clustering for path queries in digital map databases
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs
SIAM Journal on Scientific Computing
Dijkstra's algorithm on-line: an empirical case study from public railroad transport
Journal of Experimental Algorithmics (JEA)
An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps
IEEE Transactions on Knowledge and Data Engineering
Using Multi-level Graphs for Timetable Information in Railway Systems
ALENEX '02 Revised Papers from the 4th International Workshop on Algorithm Engineering and Experiments
Computing the shortest path: A search meets graph theory
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Engineering multilevel overlay graphs for shortest-path queries
Journal of Experimental Algorithmics (JEA)
SHARC: Fast and robust unidirectional routing
Journal of Experimental Algorithmics (JEA)
Goal-directed shortest-path queries using precomputed cluster distances
Journal of Experimental Algorithmics (JEA)
SEA '09 Proceedings of the 8th International Symposium on Experimental Algorithms
Engineering Route Planning Algorithms
Algorithmics of Large and Complex Networks
Combining hierarchical and goal-directed speed-up techniques for dijkstra's algorithm
Journal of Experimental Algorithmics (JEA)
Fast and compact oracles for approximate distances in planar graphs
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Contraction hierarchies: faster and simpler hierarchical routing in road networks
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Graph indexing of road networks for shortest path queries with label restrictions
Proceedings of the VLDB Endowment
Efficient routing in road networks with turn costs
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
A hub-based labeling algorithm for shortest paths in road networks
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
Graph Partitioning with Natural Cuts
IPDPS '11 Proceedings of the 2011 IEEE International Parallel & Distributed Processing Symposium
Algorithm engineering for route planning: an update
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Fully dynamic maintenance of arc-flags in road networks
SEA'12 Proceedings of the 11th international conference on Experimental Algorithms
Fast balanced partitioning is hard even on grids and trees
MFCS'12 Proceedings of the 37th international conference on Mathematical Foundations of Computer Science
Hierarchical hub labelings for shortest paths
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
HLDB: location-based services in databases
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Crowdsourcing computing resources for shortest-path computation
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Efficient route compression for hybrid route planning
MedAlg'12 Proceedings of the First Mediterranean conference on Design and Analysis of Algorithms
Proceedings of the 5th ACM SIGSPATIAL International Workshop on Computational Transportation Science
Energy-optimal routes for electric vehicles
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Customizable point-of-interest queries in road networks
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Optimizing Landmark-Based Routing and Preprocessing
Proceedings of the Sixth ACM SIGSPATIAL International Workshop on Computational Transportation Science
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We present an algorithm to compute shortest paths on continental road networks with arbitrary metrics (cost functions). The approach supports turn costs, enables real-time queries, and can incorporate a new metric in a few seconds--fast enough to support real-time traffic updates and personalized optimization functions. The amount of metric-specific data is a small fraction of the graph itself, which allows us to maintain several metrics in memory simultaneously.