A Survey of Autonomous Driving Scenarios and Scenario Databases

Hongping Ren, Hui Gao, He Chen, Guangzhen Liu
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引用次数: 1

Abstract

With the development of autonomous driving technology, traditional road testing methods can no longer meet the needs of autonomous driving testing. These methods lack sufficiency, comprehensiveness and efficiency. Using the autonomous driving scenario databases for testing can greatly shorten the test time and cost, and can improve the safety and reliability of the test. By systematically sorting out a large number of related publications, this paper summarizes the research progress of autonomous driving scenarios and scenario databases. The article firstly compares and analyzes the different definitions of autonomous driving scenarios, clarifies the connotation of the scenarios, summarizes the types of elements of the scenarios, and introduces the scenario layered model; secondly, we outline the description standards of scenario. We mainly summarize the two scenario data formats, OpenDRIVE and OpenSCENARIO, which are commonly used in the world. Thirdly, the scenario data collection and research work carried out at home and abroad is reviewed from the perspective of scenario data sources, and different datasets are compared; In addition, the definition of the scenario database, the construction process of the scenario database and the typical scenario databases are summarized; Finally, the problems and future development trends of autonomous driving scenarios and scenario databases are discussed and prospected.
自动驾驶场景与场景数据库研究综述
随着自动驾驶技术的发展,传统的道路测试方法已经不能满足自动驾驶测试的需要。这些方法缺乏充分性、全面性和有效性。利用自动驾驶场景数据库进行测试,可以大大缩短测试时间和成本,提高测试的安全性和可靠性。通过对大量相关文献的系统梳理,总结了自动驾驶场景和场景数据库的研究进展。文章首先对自动驾驶场景的不同定义进行了比较分析,厘清了自动驾驶场景的内涵,总结了自动驾驶场景的要素类型,介绍了自动驾驶场景分层模型;其次,概述了场景的描述标准。我们主要总结了目前国际上常用的两种场景数据格式:opdrive和OpenSCENARIO。再次,从场景数据源的角度回顾了国内外开展的场景数据收集和研究工作,并对不同的数据集进行了比较;此外,对场景数据库的定义、场景数据库的建设过程和典型的场景数据库进行了总结;最后,对自动驾驶场景和场景数据库存在的问题及未来发展趋势进行了讨论和展望。
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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