Stefan Funke
ABSTRACT
Computing shortest paths in road networks with millions of nodes and edges is challenging on its own. In the last few years, several preprocessing-based acceleration techniques have been developed to enable query answering orders of magnitudes faster than a plain Dijkstra computation. But most of these techniques work only if the metric which determines the optimal path is static or rarely changes. In contrast to that, we aim at answering personalized route planning queries. Here, every single query comes with a specification of its very own metric. This increases the combinatorial complexity of the problem significantly. We develop new preprocessing schemes that allow for real-time personalized route planning in huge road networks while keeping the memory footprint of the preprocessed data and subsequent queries small.
- I. Abraham, D. Delling, A. V. Goldberg, and R. F. Werneck. Alternative routes in road networks. In Proceedings of the 9th international conference on Experimental Algorithms, SEA'10, pages 23--34, Berlin, Heidelberg, 2010. Springer-Verlag. Google Scholar
Digital Library
- I. Abraham, D. Delling, A. V. Goldberg, and R. F. Werneck. A hub-based labeling algorithm for shortest paths in road networks. In Experimental Algorithms, pages 230--241. Springer, 2011. Google ScholarDigital Library
- H. Bast, S. Funke, P. Sanders, and D. Schultes. Fast routing in road networks with transit nodes. Science, 316(5824):566--566, 2007.Google ScholarCross Ref
- G. V. Batz, D. Delling, P. Sanders, and C. Vetter. Time-dependent contraction hierarchies. In ALENEX, volume 9. SIAM, 2009. Google ScholarDigital Library
- G. D'Angelo, D. Frigioni, and C. Vitale. Dynamic arc-flags in road networks. In Experimental Algorithms, pages 88--99. Springer, 2011. Google ScholarDigital Library
- D. Delling, A. V. Goldberg, T. Pajor, and R. F. Werneck. Customizable route planning. In Experimental Algorithms, pages 376--387. Springer, 2011. Google ScholarDigital Library
- D. Delling, M. Kobitzsch, and R. F. Werneck. Customizing driving directions with gpus. In Euro-Par 2014 Parallel Processing, pages 728--739. Springer, 2014.Google ScholarCross Ref
- D. Delling and R. F. Werneck. Faster customization of road networks. SEA, 13:30--42, 2013.Google Scholar
- J. Dibbelt, B. Strasser, and D. Wagner. Customizable contraction hierarchies. In Experimental Algorithms - 13th International Symposium, SEA 2014, Copenhagen, Denmark, June 29 - July 1, 2014. Proceedings, pages 271--282, 2014. Google ScholarDigital Library
- J. Dibbelt, B. Strasser, and D. Wagner. Erratum: Customizable contraction hierarchies. In Experimental Algorithms - 13th International Symposium, SEA 2014, Copenhagen, Denmark, June 29 - July 1, 2014. Proceedings, 2014. Google ScholarDigital Library
- S. Funke, A. Nusser, and S. Storandt. On k-path covers and their applications. Proceedings of the VLDB Endowment, 7(10), 2014. Google ScholarDigital Library
- S. Funke and S. Storandt. Polynomial-time construction of contraction hierarchies for multi-criteria objectives. In Proceedings of the 15th Meeting on Algorithm Engineering and Experiments, ALENEX 2013, pages 41--54, 2013. Google ScholarDigital Library
- R. Geisberger, M. Kobitzsch, and P. Sanders. Route planning with flexible objective functions. In ALENEX'10, pages 124--137, 2010. Google ScholarDigital Library
- R. Geisberger, M. N. Rice, P. Sanders, and V. J. Tsotras. Route planning with flexible edge restrictions. J. Exp. Algorithmics, 17(1):1.2:1.1--1.2:1.20, Mar. 2012. Google ScholarDigital Library
- R. Geisberger, P. Sanders, D. Schultes, and C. Vetter. Exact routing in large road networks using contraction hierarchies. Transportation Science, 46(3):388--404, 2012. Google ScholarDigital Library
- A. V. Goldberg and C. Harrelson. Computing the shortest path: A search meets graph theory. In Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms, SODA '05, pages 156--165, Philadelphia, PA, USA, 2005. Society for Industrial and Applied Mathematics. Google ScholarDigital Library
- The CGAL Project. CGAL User and Reference Manual. CGAL Editorial Board, 4.4 edition, 2014.Google Scholar
Index Terms
- Personalized route planning in road networks
Recommendations
PARP: A Parallel Traffic Condition Driven Route Planning Model on Dynamic Road Networks
The problem of route planning on road network is essential to many Location-Based Services (LBSs). Road networks are dynamic in the sense that the weights of the edges in the corresponding graph constantly change over time, representing evolving traffic ...
Multi‐AGV route planning in automated warehouse system based on shortest‐time Q‐learning algorithm
AbstractRoute planning for automated guided vehicles (AGVs) is one of the key factors that affects work efficiency of automated storage and retrieval systems (AS/RSes). Route planning plays an important role in the operation of AGVs. Since the ...
Comments