High-definition (HD) maps serve as crucial infrastructure for autonomous driving technology, facilitating vehicles in positioning, environmental perception, and motion planning without being affected by weather changes or sensor-visibility limitations. Maintaining precision and freshness in HD maps is paramount, as delayed or inaccurate information can significantly impact the safety of autonomous vehicles. Utilizing crowdsourced data for HD map updating is widely recognized as a superior method for preserving map accuracy and freshness. Although it has garnered considerable attention from researchers, there remains a lack of comprehensive exploration into the entire process of updating HD maps through crowdsourcing. For this reason, it is imperative to review and discuss crowdsourcing techniques. This paper aims to provide an overview of the overall process of crowdsourced updates, followed by a detailed examination and comparison of existing methodologies concerning the key techniques of data collection, information extraction, and change detection. Finally, this paper addresses the challenges encountered in crowdsourced updates for HD maps.

中文翻译：

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高清地图众包更新方法综述

高清 (HD) 地图是自动驾驶技术的重要基础设施，有助于车辆进行定位、环境感知和运动规划，而不受天气变化或传感器可见度限制的影响。保持高清地图的精确度和新鲜度至关重要，因为延迟或不准确的信息可能会严重影响自动驾驶车辆的安全。利用众包数据进行高清地图更新被广泛认为是保持地图准确性和新鲜度的优越方法。尽管受到了研究者的广泛关注，但对于众包更新高精地图的整个过程还缺乏全面的探索。因此，有必要回顾和讨论众包技术。本文旨在概述众包更新的整个过程，然后详细检查和比较有关数据收集、信息提取和变化检测等关键技术的现有方法。最后，本文讨论了高清地图众包更新中遇到的挑战。