CrowdAtlas: self-updating maps for cloud and personal use
CrowdAtlas: self-updating maps for cloud and personal use
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DOI：
10.1145/2462456.2465730
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发表时间：
2013
影响因子：
13.5
通讯作者：
Yin Wang;Xuemei Liu;Hong Wei;George Forman;Yanmin Zhu
中科院分区：
文献类型：
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作者：
Yin Wang;Xuemei Liu;Hong Wei;George Forman;Yanmin Zhu
数字路线图已经成为我们生活中许多方面的必需品。不幸的是，无论是在发展中国家还是在发达国家，它们都存在持续的质量问题，最近苹果和谷歌地图之争就是明证。一项针对英国司机的调查显示，26%的司机曾被GPS引导进入禁入区，新闻定期报道由数字地图引起或与之相关的车祸。除了纠正现有的错误外，还需要经常更新地图，以反映最新的构造、闭包和重新配置。TomTom估计，道路每年的变化幅度高达15%。对其他类型地图的需求也在不断增长，包括越野驾驶、自行车、徒步旅行和滑雪地图。有一些服务可以让人们共享GPS轨迹，但没有一个能创建可导航的地图。更新和维护地图需要大量的努力和延迟。今天的地图是通过昂贵的地质调查绘制的，辅以航空图像的手工编辑工作或由愤怒的地图用户提交的更正。NavTeq（现为诺基亚）的定位内容团队在全球拥有7000多名员工，负责更新地图。我们介绍了CrowdAtlas系统，该系统利用来自各种来源的日益丰富的GPS轨迹作为副产品更新数字地图：车队管理系统、远程信息处理系统和智能手机应用程序（例如导航和基于位置的服务）。我们修改了最先进的地图匹配算法，以适应现有地图不完整的可能性。它使用与地图匹配的轨迹来监控道路封闭和固定道路几何形状。它使用来自许多与地图不匹配的车辆的跟踪路段的紧密簇，以推断与现有道路相连的缺失道路。现有的道路提供了良好的轨迹分割，以产生高质量的集群，从而能够自动（甚至无监督）添加缺失的道路。通过对北京70辆出租车一周的追踪，CrowdAtlas推断出了61公里的新道路，我们将其上传到OpenStreetMap，并成为其第一套计算机生成的道路。为了实现个性化地图，我们还基于开源导航应用OSMAnd开发了CrowdAtlas app，在作为CrowdAtlas服务器的GPS数据源时，提供的数据可以更好地优化地图更新，减少通信。当在独立模式下工作时，它可以将缺失的道路添加到其车载导航地图中。这款应用程序可以在用户经过确认后立即添加每条新道路，而不是聚合多个GPS轨迹以获得高可信度。我们在独立模式下使用我们的CrowdAtlas应用程序，在30分钟内绘制出上海浦东4.5km^2区域内的主要道路，并在不到一天的时间内绘制出上海交通大学校园的步行地图。CrowdAtlas可以从根本上改变人们创建和更新地图的方式。再加上从街景和航空图像中提取道路元数据的孵化技术，现代制图可能会发生革命性的变化，减少或消除目前使用的昂贵而缓慢的手动制图过程。我们的视频演示的高清版本可在vimeo.com/62912005上获得，我们随附的全长论文描述了CrowdAtlas的技术细节。
Digital road maps have become essential to many aspects of our lives. Unfortunately, they have persistent quality issues, both in developing countries as well as in developed countries, evidenced by the recent Apple-Google map war. A survey of British drivers showed 26% have been directed by their GPS to go into no-entry areas, and the news periodically reports car accidents caused by or related to digital maps. In addition to correcting existing errors, maps need to be frequently updated to reflect the latest constructions, closures, and reconfigurations. TomTom estimates that roads change by as much as 15% each year. There are also growing demands for other types of maps, including off-road driving, cycling, hiking, and skiing maps. There are services for people to share GPS traces, but none creates navigable maps. Getting maps up to date and maintaining them involves a great deal of effort and delay. Today's maps are built by expensive geological surveys, supplemented by manual editing work from aerial imagery or corrections submitted by aggravated map users. NavTeq (now Nokia) employs more than 7,000 employees worldwide in its Location Content team to update maps. We present the CrowdAtlas system, which updates digital maps using the increasingly abundant GPS traces available as byproducts from a variety of sources: fleet management systems, telematics systems, and smartphone apps (e.g., navigation and location based services). We modified state-of-the-art map matching algorithms to accommodate the possibility that the existing map is incomplete. It uses the traces that match the map to monitor for road closures and fix road geometry. It uses tight clusters of trace segments from many vehicles that do not match the map in order to infer missing roads that connect to existing roads. The existing roads provide good segmentation of the traces to produce high quality clusters, enabling the automated (and even unsupervised) addition of missing roads. Using one week of traces from 70 taxis in Beijing, CrowdAtlas inferred 61km of new roads, which we uploaded to OpenStreetMap and became its first set of computer generated roads. To enable personalized maps, we also developed CrowdAtlas app based on OSMAnd, an open source navigation app. When acting as a GPS data source to CrowdAtlas server, it contributes data better optimized for map update with less communication. When acting in standalone-mode, it can add missing roads to its onboard navigation map. Instead of aggregating multiple GPS traces for high confidence, this app can add each new road immediately after the user traverses it, given user confirmation. We used our CrowdAtlas app in standalone-mode to map out major roads in a 4.5km^2 area of Shanghai Pudong in less than 30 minutes and build the walking map of the SJTU campus in less than a day. CrowdAtlas could fundamentally change the way people create and update maps. Together with incubating technologies that extract road metadata from street views and aerial imagery, modern cartography could be revolutionized, reducing or eliminating the expensive and slow manual mapping process used today. The high-definition version of our video presentation is available at vimeo.com/62912005, and our accompanying full-length paper describes the technical details of CrowdAtlas.