Data Issues in High Definition Maps Furniture – A Survey

IF 1.2 Q4 REMOTE SENSING

ACM Transactions on Spatial Algorithms and Systems Pub Date : 2023-10-12 DOI:10.1145/3627160

Andi Zang, Runsheng Xu, Goce Trajcevski, Fan Zhou

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引用次数: 0

Abstract

The rapid advancements in sensing techniques, networking and AI algorithms in the recent years have brought the autonomous driving vehicles closer to common use in vehicular transportation. One of the fundamental components to enable the autonomous driving functionalities are the High Definition (HD) maps – a type of maps that carry highly accurate and much richer information than conventional maps. The creation and use of HD maps rely on advances in multiple disciplines such as computer vision/object perception, geographic information system, sensing, simultaneous localization and mapping, machine learning, etc. To date, several survey papers have been published, describing the literature related to HD maps and their use in specialized contexts. In this survey, we aim to provide: (1) a comprehensive overview of the issues and solutions related to HD maps and their use, without attachment to a particular context; (2) a detailed coverage of the important domain knowledge of HD map furniture, from acquisition techniques and extraction approaches, through HD maps related datasets, to furniture quality assessment metrics, for the purpose of providing a comprehensive understanding of the entire workflow of HD map furniture generation, as well as its use.

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高清晰度地图家具中的数据问题-调查

近年来，传感技术、网络和人工智能算法的快速发展，使自动驾驶汽车更接近于在车辆运输中的普遍应用。实现自动驾驶功能的基本组件之一是高清(HD)地图，这是一种比传统地图携带高度精确和更丰富信息的地图。高清地图的创建和使用依赖于多个学科的进步，如计算机视觉/物体感知、地理信息系统、传感、同步定位和制图、机器学习等。迄今为止，已经发表了几篇调查论文，描述了与高清地图及其在专门情况下的使用有关的文献。在这项调查中，我们的目标是提供:(1)全面概述与高清地图及其使用相关的问题和解决方案，而不依附于特定的背景;(2)详细介绍高清地图家具的重要领域知识，从获取技术和提取方法，通过高清地图相关数据集，到家具质量评估指标，以便全面了解高清地图家具生成的整个工作流程，以及它的使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACM Transactions on Spatial Algorithms and Systems REMOTE SENSING-

CiteScore

4.40

自引率

5.30%

发文量

期刊介绍： ACM Transactions on Spatial Algorithms and Systems (TSAS) is a scholarly journal that publishes the highest quality papers on all aspects of spatial algorithms and systems and closely related disciplines. It has a multi-disciplinary perspective in that it spans a large number of areas where spatial data is manipulated or visualized (regardless of how it is specified - i.e., geometrically or textually) such as geography, geographic information systems (GIS), geospatial and spatiotemporal databases, spatial and metric indexing, location-based services, web-based spatial applications, geographic information retrieval (GIR), spatial reasoning and mining, security and privacy, as well as the related visual computing areas of computer graphics, computer vision, geometric modeling, and visualization where the spatial, geospatial, and spatiotemporal data is central.