Inferring routing preferences from user-generated trajectories using a compression criterion

IF 1.8 Q2 GEOGRAPHY
Axel Forsch, Johannes Oehrlein, Benjamin Niedermann, J. Haunert
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引用次数: 1

Abstract

The optimal path between two vertices in a graph depends on the optimization objective, which is often defined as a weighted sum of multiple criteria. When integrating two criteria, their relative importance is expressed with a balance factor α. We present a new approach for inferring α from trajectories. The core of our approach is a compression algorithm that requires a graph G representing a transportation network, two edge costs modeling routing criteria, and a path P in G representing the trajectory. It yields a minimum subsequence S of the sequence of vertices of P and a balance factor α, such that the path P can be fully reconstructed from S, G, its edge costs, and α. By minimizing the size of S over α, we learn the balance factor that corresponds best to the user's routing preferences. In an evaluation with crowd-sourced cycling trajectories, we weigh the usage of official signposted cycle routes against other routes. More than 50% of the trajectories can be segmented into five optimal sub-paths or less. Almost 40% of the trajectories indicate that the cyclist is willing to take a detour of 50% over the geodesic shortest path to use an official cycle path.
使用压缩标准从用户生成的轨迹推断路由偏好
图中两个顶点之间的最优路径取决于优化目标,优化目标通常被定义为多个标准的加权和。当整合两个准则时,它们的相对重要性用平衡因子α表示。我们提出了一种从轨迹推断α的新方法。我们方法的核心是一种压缩算法,它需要一个表示运输网络的图G,两个边缘成本建模路由标准,以及G中的路径P表示轨迹。它产生了P的顶点序列的最小子序列S和一个平衡因子α,使得路径P可以由S、G、它的边代价和α完全重构。通过最小化S / α的大小,我们学习最符合用户路由偏好的平衡因子。在对众包自行车轨迹的评估中,我们权衡了官方路标自行车路线与其他路线的使用情况。超过50%的轨迹可以被分割成5个或更少的最优子路径。近40%的轨迹表明,骑车者愿意在测地线最短路径上绕行50%,以使用官方自行车道。
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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来源期刊
CiteScore
5.10
自引率
0.00%
发文量
5
审稿时长
9 weeks
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