Efficient Algorithms for Shortest Paths in Sparse Networks
Journal of the ACM (JACM)
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
Engineering multilevel overlay graphs for shortest-path queries
Journal of Experimental Algorithmics (JEA)
Engineering Route Planning Algorithms
Algorithmics of Large and Complex Networks
Robust and Online Large-Scale Optimization
The shortest path problem revisited: optimal routing for electric vehicles
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
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
Real-time routing with OpenStreetMap data
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Exact Routing in Large Road Networks Using Contraction Hierarchies
Transportation Science
Quick and energy-efficient routes: computing constrained shortest paths for electric vehicles
Proceedings of the 5th ACM SIGSPATIAL International Workshop on Computational Transportation Science
Minimum time-dependent travel times with contraction hierarchies
Journal of Experimental Algorithmics (JEA)
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We study the problem of electric vehicle route planning, where an important aspect is computing paths that minimize energy consumption. Thereby, any method must cope with specific properties, such as recuperation, battery constraints (over- and under-charging), and frequently changing cost functions (e. g., due to weather conditions). This work presents a practical algorithm that quickly computes energy-optimal routes for networks of continental scale. Exploiting multi-level overlay graphs [25, 30], we extend the Customizable Route Planning approach [7] to our scenario in a sound manner. This includes the efficient computation of profile queries and the adaption of bidirectional search to battery constraints. Our experimental study uses detailed consumption data measured from a production vehicle (Peugeot iOn). It reveals for the network of Europe that a new cost function can be incorporated in about five seconds, after which we answer random queries within 0.3 ms on average. Additional evaluation on an artificial but realistic [21, 35] vehicle model with unlimited range demonstrates the excellent scalability of our algorithm: Even for long-range queries across Europe it achieves query times below 5 ms on average---fast enough for interactive applications. Altogether, our algorithm exhibits faster query times than previous approaches, while improving (metric-dependent) preprocessing time by three orders of magnitude.