Department of Automotive Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea.
Department of Smart Vehicle Engineering, Konkuk University, Seoul 05029, Korea.
Sensors (Basel). 2018 Nov 28;18(12):4172. doi: 10.3390/s18124172.
A High-Definition map (HD map) is a precise and detailed map composed of various landmark feature layers. The HD map is a core technology that facilitates the essential functions of intelligent vehicles. Recently, it has come to be required for the HD map to continuously add new feature layers in order to increase the performances of intelligent vehicles in more complicated environments. However, it is difficult to generate a new feature layer for the HD map, because the conventional method of generating the HD map based on several professional mapping cars has high costs in terms of time and money due to the need to re-drive on all of the public roads. In order to reduce these costs, we propose a crowd-sourced mapping process of the new feature layer for the HD map. This process is composed of two steps. First, new features in the environments are acquired from multiple intelligent vehicles. The acquired new features build each new feature layer in each intelligent vehicle using the HD map-based GraphSLAM approach, and these new feature layers are conveyed to a map cloud through a mobile network system. Next, the crowd-sourced new feature layers are integrated into a new feature layer in a map cloud. In the simulation, the performance of the crowd-sourced process is then analyzed and evaluated. Experiments in real driving environments confirm the results of the simulation.
高清地图（HD 地图）是由各种地标特征层组成的精确和详细的地图。HD 地图是智能车辆基本功能的核心技术。最近，为了提高智能车辆在更复杂环境中的性能，需要不断为 HD 地图添加新的特征层。然而，为 HD 地图生成新的特征层很困难，因为传统的基于几辆专业测绘汽车生成 HD 地图的方法由于需要在所有公共道路上重新行驶，因此在时间和金钱方面成本很高。为了降低这些成本，我们提出了一种 HD 地图新特征层的众包测绘过程。该过程由两个步骤组成。首先，从多辆智能车辆中获取环境中的新特征。使用基于 HD 地图的 GraphSLAM 方法，所获取的新特征构建每个智能车辆中的每个新特征层，这些新特征层通过移动网络系统传送到地图云。接下来，将众包的新特征层集成到地图云中的新特征层中。在仿真中，然后分析和评估众包过程的性能。在真实驾驶环境中的实验证实了仿真的结果。
