%0 Journal Article
%T 自动驾驶高精地图众包更新关键技术及机制<br>Key Technologies and Mechanisms for Crowdsourced Updates of High-Precision Maps in Autonomous Driving
%A 陈天祎
%A 赫子悦
%A 卞君洋
%A 杨军星
%A 黄鹤
%J Geomatics Science and Technology
%P 267-277
%@ 2329-7239
%D 2024
%I Hans Publishing
%R 10.12677/gst.2024.124033
%X 本文主要探讨了自动驾驶技术的快速发展及其对高精度地图实时更新的需求。分析基于不同数据的众包地图构建方法在自动驾驶高精地图中的关键作用以及不同地图更新要素的更新方法。其次&#65292;细化了高精地图更新的关键技术&#65292;综述了众源式高精度地图动态更新可靠性的方法&#65307;说明了如今数据采集传感器的多样性选择和相应的方法&#65307;总结了国内外数据模型的研究现状&#65307;描述了众包模式下奖励机制的重要程度。归纳了高精地图平台对自动驾驶的支持与作用&#65292;以及存在数据质量、信息安全、法律法规等问题与方法。<br>This paper explores the rapid development of autonomous driving technology and its demand for real-time updates of high-precision maps. It analyzes the critical role of crowdsourced map-building methods based on different data types in high-precision maps for autonomous driving, as well as the update methods for various map update elements. Furthermore, it details the key technologies for updating high-precision maps, reviews methods for ensuring the reliability of dynamically updated crowdsourced high-precision maps, and explains the diversity of current data collection sensors and their respective methods. The paper also summarizes the research status of domestic and international data models and describes the importance of reward mechanisms in crowdsourcing models. It concludes by summarizing the support and role of high-precision map platforms in autonomous driving and discusses issues and methods related to data quality, information security, and legal regulations.
%K 自动驾驶&#65292
%K 高精地图&#65292
%K 众包更新&#65292
%K 数据模型&#65292
%K 奖励机制<br>Autonomous Driving
%K High-Precision Maps
%K Crowdsourced Updates
%K Data Models
%K Reward Mechanisms
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=93881