In recent years, the rapid development of high-precision map technology combined with artificial intelligence has ushered in a new development opportunity in the field of intelligent vehicles. High-precision map technology is an important guarantee for intelligent vehicles to achieve autonomous driving. However, due to the lack of research on high-precision map technology, it is difficult to rationally use this technology in the field of intelligent vehicles. Therefore, relevant researchers studied a fast and effective algorithm to generate high-precision GPS data from a large number of low-precision GPS trajectory data fusion, and generated several key data points to simplify the description of GPS trajectory, and realized the "crowdsourced update" model based on a large number of social vehicles for map data collection came into being. This kind of algorithm has the important significance to improve the data accuracy, reduce the measurement cost and reduce the data storage space. On this basis, this paper analyzes the implementation form of crowdsourcing map, so as to improve the various information data in the high-precision map according to the actual situation, and promote the high-precision map can be reasonably applied to the intelligent car.

翻译：近年来，高精度地图技术与人工智能的快速发展为智能车辆领域带来了新的发展机遇。高精度地图技术是实现智能车辆自动驾驶的重要保障。然而，由于对高精度地图技术研究不足，该技术在智能车辆领域难以得到合理应用。为此，相关研究人员研究了一种快速有效的算法，通过融合大量低精度GPS轨迹数据生成高精度GPS数据，并生成若干关键数据点以简化GPS轨迹描述，由此催生了基于海量社会车辆进行地图数据采集的“众包更新”模式。此类算法对于提高数据精度、降低测量成本、减少数据存储空间具有重要意义。在此基础上，本文分析了众包地图的实现形式，以根据实际情况完善高精度地图中的各类信息数据，推动高精度地图能够合理应用于智能汽车领域。