Customizable contraction hierarchies are one of the most popular route planning frameworks in practice, due to their simplicity and versatility. In this work, we present a novel algorithm for finding k-nearest neighbors in customizable contraction hierarchies by systematically exploring the associated separator decomposition tree. Compared to previous bucket-based approaches, our algorithm requires much less target-dependent preprocessing effort. Moreover, we use our novel approach in two concrete applications. The first application are online k-closest point-of-interest queries, where the points of interest are only revealed at query time. We achieve query times of about 25 milliseconds on a continental road network, which is fast enough for interactive systems. The second application is travel demand generation. We show how to accelerate a recently introduced travel demand generator by a factor of more than 50 using our novel nearest-neighbor algorithm.
@InProceedings{buchhold_et_al:LIPIcs.SEA.2021.18, author = {Buchhold, Valentin and Wagner, Dorothea}, title = {{Nearest-Neighbor Queries in Customizable Contraction Hierarchies and Applications}}, booktitle = {19th International Symposium on Experimental Algorithms (SEA 2021)}, pages = {18:1--18:18}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-185-6}, ISSN = {1868-8969}, year = {2021}, volume = {190}, editor = {Coudert, David and Natale, Emanuele}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2021.18}, URN = {urn:nbn:de:0030-drops-137908}, doi = {10.4230/LIPIcs.SEA.2021.18}, annote = {Keywords: Nearest neighbors, points of interest, travel demand generation, radiation model, customizable contraction hierarchies} }
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