Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification

5 Apr 2020Friedrich KruberJonas WurstEduardo Sánchez MoralesSamarjit ChakrabortyMichael Botsch

The goal of this paper is to provide a method, which is able to find categories of traffic scenarios automatically. The architecture consists of three main components: A microscopic traffic simulation, a clustering technique and a classification technique for the operational phase... (read more)

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