Qian Zhiqi, Ye Zhirui, Shi Xiaomeng
School of Transportation, Southeast University, 35 Jinxianghe Road, Nanjing 210018, China.
Sensors (Basel). 2024 Jun 25;24(13):4115. doi: 10.3390/s24134115.
High-definition maps can provide necessary prior data for autonomous driving, as well as the corresponding beyond-line-of-sight perception, verification and positioning, dynamic planning, and decision control. It is a necessary element to achieve L4/L5 unmanned driving at the current stage. However, currently, high-definition maps still have problems such as a large amount of data, a lot of data redundancy, and weak data correlation, which make autonomous driving fall into difficulties such as high data query difficulty and low timeliness. In order to optimize the data quality of high-definition maps, enhance the degree of data correlation, and ensure that they better assist vehicles in safe driving and efficient passage in the autonomous driving scenario, it is necessary to clarify the information system thinking of high-definition maps, propose a complete and accurate model, determine the content and functions of each level of the model, and continuously improve the information system model. The study aimed to put forward a complete and accurate high-definition map information system model and elaborate in detail the content and functions of each component in the data logic structure of the system model. Through research methods such as the modeling method and literature research method, we studied the high-definition map information system model in the autonomous driving scenario and explored the key technologies therein. We put forward a four-layer integrated high-definition map information system model, elaborated in detail the content and functions of each component (map, road, vehicle, and user) in the data logic structure of the model, and also elaborated on the mechanism of the combined information of each level of the model to provide services in perception, positioning, decision making, and control for autonomous driving vehicles. This article also discussed two key technologies that can support autonomous driving vehicles to complete path planning, navigation decision making, and vehicle control in different autonomous driving scenarios. The four-layer integrated high-definition map information model proposed by this research institute has certain application feasibility and can provide references for the standardized production of high-definition maps, the unification of information interaction relationships, and the standardization of map data associations.
高清地图可为自动驾驶提供必要的先验数据，以及相应的超视距感知、验证与定位、动态规划和决策控制。它是现阶段实现L4/L5级无人驾驶的必要要素。然而，目前高清地图仍存在数据量庞大、数据冗余多、数据关联性弱等问题，这使得自动驾驶陷入数据查询难度高、时效性低等困境。为了优化高清地图的数据质量，增强数据关联度，确保其在自动驾驶场景中更好地辅助车辆安全驾驶和高效通行，有必要厘清高清地图的信息系统思路，提出完整准确的模型，确定模型各层级的内容与功能，并不断完善信息系统模型。本研究旨在提出一个完整准确的高清地图信息系统模型，并详细阐述系统模型数据逻辑结构中各组件的内容与功能。通过建模方法、文献研究方法等研究手段，我们对自动驾驶场景下的高清地图信息系统模型进行了研究，并探索其中的关键技术。我们提出了一个四层一体化高清地图信息系统模型，详细阐述了模型数据逻辑结构中各组件（地图、道路、车辆和用户）的内容与功能，还阐述了模型各层级组合信息为自动驾驶车辆在感知、定位、决策和控制方面提供服务的机制。本文还探讨了能够支持自动驾驶车辆在不同自动驾驶场景下完成路径规划、导航决策和车辆控制的两项关键技术。本研究机构提出的四层一体化高清地图信息模型具有一定的应用可行性，可为高清地图的标准化生产、信息交互关系的统一以及地图数据关联的规范化提供参考。
