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

41 citations · 41 across the 3 of their papers we have counts for

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eess.SP2020

High Precision Indoor Navigation for Autonomous Vehicles

Eduardo Sánchez Morales, Michael Botsch, Bertold Huber +1

Autonomous driving is an important trend of the automotive industry. The continuous research towards this goal requires a precise reference vehicle state estimation under all circu…

eess.SP2020★ 41 cited

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

Friedrich Kruber, Jonas Wurst, Eduardo Sánchez Morales +2

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 microscopi…