应申, 蒋跃文, 顾江岩, 刘之林, 梁沅宜, 郭迟, 刘经南. 面向自动驾驶的高精地图模型及关键技术[J]. 武汉大学学报 ( 信息科学版), 2024, 49(4): 506-515. DOI: 10.13203/j.whugis20230227
引用本文: 应申, 蒋跃文, 顾江岩, 刘之林, 梁沅宜, 郭迟, 刘经南. 面向自动驾驶的高精地图模型及关键技术[J]. 武汉大学学报 ( 信息科学版), 2024, 49(4): 506-515. DOI: 10.13203/j.whugis20230227
YING Shen, JIANG Yuewen, GU Jiangyan, LIU Zhilin, LIANG Yuanyi, GUO Chi, LIU Jingnan. High Definition Map Model for Autonomous Driving and Key Technologies[J]. Geomatics and Information Science of Wuhan University, 2024, 49(4): 506-515. DOI: 10.13203/j.whugis20230227
Citation: YING Shen, JIANG Yuewen, GU Jiangyan, LIU Zhilin, LIANG Yuanyi, GUO Chi, LIU Jingnan. High Definition Map Model for Autonomous Driving and Key Technologies[J]. Geomatics and Information Science of Wuhan University, 2024, 49(4): 506-515. DOI: 10.13203/j.whugis20230227

面向自动驾驶的高精地图模型及关键技术

High Definition Map Model for Autonomous Driving and Key Technologies

  • 摘要: 高精地图作为自动驾驶中不可或缺的环节,其发展将在很大程度上影响自动驾驶水平。现有高精地图模型多样,面向机器思维不足,缺乏面向“人-车-路-图”的系统思维。基于分层更明确、要素更全面和用户特征更突出三方面的考量,细化和充实四层一体化高精地图模型,详细阐述了静态数据层、道路实时信息层、车辆动态信息层和用户模型层的内容和功能;指出了高精地图云边端协同更新机制、路口安全信息框架、交通事件驱动的导航决策3个关键技术如何支撑自动驾驶全局和局部路径导航决策以及车辆控制;从感知、定位、决策、控制4个层面解释了高精地图平台对自动驾驶的支持。

     

    Abstract: High definition (HD) map is an indispensable part of autonomous driving, and its development will greatly affect the level of autonomous driving.The existing HD map models are diverse, lacking the systems thinking of “human-vehicle-road-map”, and the vehicle-oriented consideration is not thoughtful enough. Based on the consideration of more explicit layers, more comprehensive elements and more prominent user characteristics, we attempt to refine and enrich the data logic structure of intelligent high precision map, and elaborate the contents and functions of static data layer, road real-time information layer, vehicle dynamic information layer and user model layer in detail. We point out three key technologies, the collaborative updating mechanism of “cloud-edge-vehicle”, the intersection safety information framework, and the navigation decision-making driven by traffic event.It describes how these three key technologies support the global and local path navigation decisions and the control of autonomous vehicle. Decision supports of HD map for autonomous driving are explained from four aspects, perception, positioning, decision-making, and control.

     

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