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Autonomous Driving Scenario Generation in Overtake Manoeuvres Through Data Fusion

机译:通过数据融合超越机动的自主驾驶场景

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For an effective study of specific driving scenarios, in particular related to overtaking manoeuvres, developing well-thought-out manoeuvre databases from the acquired data will greatly improve the analysis process. The key point being that identifying clearly the studied scenario and clustering the manoeuvres based on specific sub-cases of this will bring an extra dimension of information that allows to visualise existing correlations between a given set of conditions and the manoeuvres performed under them. This paper expands on how to obtain these databases starting from only from overtaken manoeuvres extracted from experimental data. Consisting in two main procedures, the manoeuvre classification itself, in which a hybrid-classifier that combines both supervised and unsupervised algorithms generates the scenario sub-cases, and the database compilation stage, in where it displays the different types of databases that can be created, based on the aim of the study.
机译:对于对特定驾驶场景的有效研究,特别是与超车机动相关的,从获取的数据中开发仔细考虑的机动数据库将大大改善分析过程。 关键点是识别基于特定子例的所学习的场景和聚类演习,将带来额外的信息维度,允许可视化给定的一组条件和它们下面的操作之间的现有相关性。 本文展开了如何从实验数据中提取的超值机动开始时获取这些数据库。 组成的两个主要过程,机动分类本身,其中一个组合监督和无监督算法的混合分类器生成方案子情况和数据库编译阶段,在它显示可以创建的不同类型的数据库 ,基于研究的目的。

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