MapReuse: Recycling Routing API Queries

R. Stanojevic, Sofiane Abbar, M. Mokbel
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引用次数: 3

Abstract

Commercial maps often offer traffic awareness which is critical for many location based services. On the other hand free and open map services (such as government maps or OSM) are traffic oblivious and hence are of limited value for such services. In this paper we show that coarse information available from a commercial map routing API, can be dissected into fine-grained per-road-segment traffic information which can be reused in any application requiring traffic-awareness. Our system MapReuse queries a commercial map for a (relatively small) number of routes, and uses the returned routes and expected travel times, to infer travel time on each individual edge of the road network. Such fine-grained travel time information can be used not only to infer travel time on any given route but also to compute complex spatial queries (such as traffic-aware isochrone map) for free. We test our system on four representative metropolitan areas: Bogota, Doha, NYC and Rome, and report very encouraging results. Namely, we observe the median and mean percentage errors of MapReuse, measured against the travel times reported by the commercial map, to be in the range of 4% to 8%, implying that MapReuse is capable to accurately reconstruct the traffic conditions in all four studied cities.
MapReuse:回收路由API查询
商业地图通常提供交通意识,这对许多基于位置的服务来说是至关重要的。另一方面,免费和开放的地图服务(如政府地图或OSM)是交通无关的,因此对此类服务的价值有限。在本文中,我们展示了从商业地图路由API中获得的粗信息,可以被分解成细粒度的每个道路段的交通信息,这些信息可以在任何需要交通感知的应用程序中重用。我们的系统MapReuse在商业地图上查询(相对较少的)路线,并使用返回的路线和预期旅行时间来推断道路网络每个单独边缘的旅行时间。这种细粒度的旅行时间信息不仅可以用来推断任何给定路线上的旅行时间,还可以免费计算复杂的空间查询(如交通感知等时线地图)。我们在波哥大、多哈、纽约和罗马四个具有代表性的大都市地区测试了我们的系统,并报告了非常令人鼓舞的结果。也就是说,我们观察到MapReuse的中位数和平均百分比误差(相对于商业地图报告的旅行时间)在4%到8%的范围内,这意味着MapReuse能够准确地重建所有四个研究城市的交通状况。
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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