Abstract
Electric vehicles (EV) powered by batteries will play a significant role in the road traffic of the future. The unique characteristics of such EVs – limited cruising range, long recharge times, and the ability to regain energy during deceleration – require novel routing algorithms, since the task is now to determine the most economical route rather than just the shortest one. This paper proposes extensions to general shortest-path algorithms that address the problem of energy-optimal routing. Specifically, we (i) formalize energy-efficient routing in the presence of rechargeable batteries as a special case of the constrained shortest path problem (CSPP) with hard and soft constraints, and (ii) present an adaption of a general shortest path algorithm (using an energy graph, i.e., a graph with a weight function representing the energy consumption) that respects the given constraints and has a worst case complexity of O(n 3). The presented algorithms have been implemented and evaluated within a prototypic navigation system for energy-efficient routing.
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References
Dijkstra, E.: A note on two problems in connexion with graphs. Numerische Mathematik 1, 269–271 (1959)
Bellman, R.: On a routing problem. Quart. of Appl. Math. 16(1), 87–90 (1958)
Ford Jr., L.R.: Network flow theory. Technical report, RAND (1956)
Geisberger, R., Sanders, P., Schultes, D., Delling, D.: Contraction hierarchies: Faster and simpler hierarchical routing in road networks. In: McGeoch, C.C. (ed.) WEA 2008. LNCS, vol. 5038, pp. 319–333. Springer, Heidelberg (2008)
Sanders, P., Schultes, D.: Highway Hierarchies Hasten Exact Shortest Path Queries. In: Brodal, G.S., Leonardi, S. (eds.) ESA 2005. LNCS, vol. 3669, pp. 568–579. Springer, Heidelberg (2005)
Bast, H., Funke, S., Sanders, P., Schultes, D.: Fast routing in road networks with transit nodes. Science 316(5824), 566 (2007)
Joksch, H.C.: The shortest route problem with constraints. Journal of Mathematical Analysis and Applications 14, 191–197 (1966)
Garey, M., Johnson, D.: Computers and Intractibility: A Guide to the Theory of NP-Completeness. W. H. Freeman, New York (1979)
Gallo, G., Pallottino, S.: Shortest path methods: A unifying approach. Mathematical Programming Studies, vol. 26. Springer, Heidelberg (1986)
Cherkassky, B.V., Goldberg, A.V., Radzik, T.: Shortest paths algorithms: Theory and experimental evaluation. Mathematical Programming 73(2) (1993)
Johnson, D.B.: A note on Dijkstra’s shortest path algorithm. Journal of the ACM 20(3), 385–388 (1973)
Zhan, F.B., Noon, C.E.: A comparison between label-setting and label-correcting algorithms for computing one-to-one shortest paths. Journal of Geographic Information and Decision Analysis 4(2), 1–11 (2000)
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Artmeier, A., Haselmayr, J., Leucker, M., Sachenbacher, M. (2010). The Shortest Path Problem Revisited: Optimal Routing for Electric Vehicles. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds) KI 2010: Advances in Artificial Intelligence. KI 2010. Lecture Notes in Computer Science(), vol 6359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16111-7_35
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DOI: https://doi.org/10.1007/978-3-642-16111-7_35
Publisher Name: Springer, Berlin, Heidelberg
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