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A Novel Dynamic Physical Storage Model for Vehicle Navigation Maps

机译:一种新的车辆导航地图动态物理存储模型

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摘要

The physical storage model is one of the key technologies for vehicle navigation maps used in a navigation system. However, the performance of most traditional storage models is limited in dynamic navigation due to the static storage format they use. In this paper, we proposed a new physical storage model, China Navigation Data Format (CNDF), which helped access and update the navigation data. The CNDF model used the reach-based hierarchy method to build a road hierarchal network, which enhanced the efficiency of data compression. It also adopted the Linear Link Coding method, in which the start position was combined with the end position as the identification code for multi-level links, and each link traced up-level links consistently without recording the array of identifications. The navigation map of East China (including Beijing, Tianjin, Shandong, Hebei, and Jiangsu) at 1:10,000, generated using the CNDF model, and the real time traffic information in Beijing were combined to test the performance of a navigation system using an embedded navigation device. Results showed that it cost less than 1 second each time to refresh the navigation map, and the accuracy of the hierarchal shortest-path algorithm was 99.9%. Our work implied that the CNDF model is efficient in vehicle navigation applications.
机译:物理存储模型是导航系统中使用的车辆导航地图的关键技术之一。但是,由于大多数传统存储模型使用静态存储格式,因此它们在动态导航中的性能受到限制。在本文中,我们提出了一种新的物理存储模型,中国导航数据格式(CNDF),该模型有助于访问和更新导航数据。 CNDF模型使用基于可达性的层次结构方法构建道路层次网络,从而提高了数据压缩效率。它还采用了“线性链接编码”方法,该方法将开始位置和结束位置组合为多级链接的标识代码,并且每个链接始终跟踪上级链接,而无需记录标识数组。使用CNDF模型生成的华东地区(包括北京,天津,山东,河北和江苏)的1:1:1导航图与北京的实时交通信息结合起来,使用嵌入式导航设备。结果表明,每次刷新导航地图的时间均不到1秒,并且层次最短路径算法的准确性为99.9%。我们的工作暗示CNDF模型在车辆导航应用中是有效的。

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