高精度道路导航地图的进展与思考

Progress and Consideration of High Precision Road Navigation Map

随着互联网时代的高速发展,更多基于位置的新型行业逐步发展起来,例如"互联网+"智能交通、无人系统等,但这些行业的发展都需要高精度的位置数据作为支撑,而传统导航地图5 m的精度无法满足需求,因此高精度道路导航地图概念被提出。高精度道路导航地图具有更加丰富细致的道路信息,可以更加精准地反映道路的真实情况。与传统地图相比,它的图层数量更多,图层内容更加精细,具有新的地图结构划分。正是因为高精度道路导航地图丰富的信息含量,使得它具有庞大的数据量,而传统的集中式大数据处理模式无法满足它的计算需求。因此,本文提出"众包+边缘计算"的大数据处理模式来解决高精度道路导航地图的计算问题。目前,高精度道路导航地图已进入高速发展状态,但发展过程中仍面临着一些需要解决的问题。

With the rapid development of the Internet, an increasing number of new industries such as ＂Internet Plus＂ intelligent transportation and unmanned systems based on location-based services have been gradually developed. The development of these industries requires the support of high precision location data, which the 5 m accuracy of traditional navigation maps cannot provide. To overcome the drawbacks of traditional maps, high precision road navigation maps have been proposed. High precision road navigation maps can provide more detailed road information and are thus able to more accurately reflect the real situation of roads. Compared to traditional maps, high precision road navigation maps possess three advantages. First, they include additional map layers. Second, the content of the layers is finer. Third, a new map structure is divided. However, the rich information content of high precision maps leads to the generation of huge amounts of data. Traditional centralized big data processing modes are unable to meet the computing needs required for processing such huge amounts of data. Therefore, in this paper, we propose a big data processing model involving ＂crowdsourcing ＋ edge computing＂ to address the problem of high precision map calculation. At present, high precision road navigation maps have kicked into a high gear. Nevertheless, certain problems persist that need to be addressed during the process of development.