53 citations · 107 across the 6 of their papers we have counts for
6 papers
Open-set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios
Lakshman Balasubramanian, Friedrich Kruber, Michael Botsch +1
An understanding and classification of driving scenarios are important for testing and development of autonomous driving functionalities. Machine learning models are useful for sce…
Accuracy Characterization of the Vehicle State Estimation from Aerial Imagery
Eduardo Sánchez Morales, Friedrich Kruber, Michael Botsch +2
Due to their capability of acquiring aerial imagery, camera-equipped Unmanned Aerial Vehicles (UAVs) are very cost-effective tools for acquiring traffic information. However, not e…
Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles
Friedrich Kruber, Eduardo Sánchez Morales, Samarjit Chakraborty +1
The availability of real-world data is a key element for novel developments in the fields of automotive and traffic research. Aerial imagery has the major advantage of recording mu…
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…
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization
Friedrich Kruber, Jonas Wurst, Michael Botsch
A modification of the Random Forest algorithm for the categorization of traffic situations is introduced in this paper. The procedure yields an unsupervised machine learning method…
Highway traffic data: macroscopic, microscopic and criticality analysis for capturing relevant traffic scenarios and traffic modeling based on the highD data set
Friedrich Kruber, Jonas Wurst, Samarjit Chakraborty +1
This work provides a comprehensive analysis on naturalistic driving behavior for highways based on the highD data set. Two thematic fields are considered. First, some macroscopic a…