Nearest-Neighbor Queries in Customizable Contraction Hierarchies and Applications

V. Buchhold, D. Wagner
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引用次数: 1

Abstract

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.
自定义收缩层次结构和应用程序中的最近邻查询
由于其简单和通用性,可定制的收缩层次结构是实践中最流行的路线规划框架之一。在这项工作中,我们提出了一种新的算法,通过系统地探索相关的分隔符分解树,在可定制的收缩层次结构中找到k个最近邻。与以前的基于桶的方法相比,我们的算法需要更少的目标相关的预处理工作。此外,我们在两个具体应用中使用了我们的新方法。第一个应用程序是在线k-最近兴趣点查询,其中兴趣点仅在查询时显示。我们在大陆道路网络上实现了大约25毫秒的查询时间,这对于交互式系统来说已经足够快了。第二个应用是旅游需求生成。我们展示了如何使用我们新颖的最近邻算法将最近引入的旅行需求生成器加速50倍以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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