In recent years, significant academic advancements have been made in the field of autonomous vehicles, with Local maps emerging as a crucial component of autonomous driving technology. Local maps not only provide intricate details of road networks but also serve as fundamental inputs for critical tasks such as vehicle localization, navigation, and decision-making. Given the characteristics of SD map (Standard Definition Map), which include low cost, ease of acquisition, and high versatility, perception methods that integrate SD map as prior information have demonstrated significant potential in the field of Local map perception. The purpose of this paper is to provide researchers with a comprehensive overview and summary of the latest advancements in the integration of SD map as prior information for Local map perception methods. This review begins by introducing the task definition and general pipeline of local map perception methods that incorporate SD maps as prior information, along with relevant public datasets. And then it focuses on the representation and encoding methods of multi-source information, as well as the methods for fusing multi-source information. In response to this burgeoning trend, this article presents a comprehensive and meticulous overview of the diverse research efforts in this particular field. Finally, the article addresses pertinent issues and future challenges with the aim of guiding researchers in understanding the current trends and methodologies prevalent in the field.

本研究探讨了局部地图在自动驾驶技术中的核心作用，尤其是将标准定义地图(SD地图)作为 prior 信息的整合方法。文章的关键发现是，SD地图的低成本、易获取性和高通用性为局部地图感知方法提供了显著的潜力，同时综述了当前研究的最新进展和未来的挑战，引导研究者更好地认识这一领域的趋势与方法。

基于标准定义地图的局部地图构建方法：一项新颖的调查