Michael Botsch
Michael Botsch
Technische Hochschule Ingolstadt
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Cited by
Cited by
An unsupervised random forest clustering technique for automatic traffic scenario categorization
F Kruber, J Wurst, M Botsch
2018 21st International conference on intelligent transportation systems …, 2018
A fast airplane boarding strategy using online seat assignment based on passenger classification
G Notomista, M Selvaggio, F Sbrizzi, G Di Maio, S Grazioso, M Botsch
Journal of Air Transport Management 53, 140-149, 2016
Method for associating a transmitter with a detected object in car-to-car communication and motor vehicle
S Engel, M Botsch, H Rößler
US Patent 10,650,674, 2020
Unsupervised and supervised learning with the random forest algorithm for traffic scenario clustering and classification
F Kruber, J Wurst, ES Morales, S Chakraborty, M Botsch
2019 IEEE Intelligent Vehicles Symposium (IV), 2463-2470, 2019
Situation aspect modelling and classification using the scenario based random forest algorithm for convoy merging situations
M Reichel, M Botsch, R Rauschecker, KH Siedersberger, M Maurer
13th International IEEE Conference on Intelligent Transportation Systems …, 2010
Variational autoencoder-based vehicle trajectory prediction with an interpretable latent space
M Neumeier, M Botsch, A Tollkühn, T Berberich
2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021
Machine learning based prediction of crash severity distributions for mitigation strategies
M Müller, M Botsch, D Böhmländer, W Utschick
Journal of Advances in Information Technology 9 (1), 15-24, 2018
A machine learning approach for the segmentation of driving maneuvers and its application in autonomous parking
G Notomista, M Botsch
Journal of Artificial Intelligence and Soft Computing Research 7 (4), 243-255, 2017
Machine learning architectures for the estimation of predicted occupancy grids in road traffic
P Nadarajan, M Botsch, S Sardina
Journal of Advances in Information Technology 9 (1), 1-9, 2018
A statistical learning approach for estimating the reliability of crash severity predictions
M Müller, P Nadarajan, M Botsch, W Utschick, D Böhmländer, ...
2016 IEEE 19th International Conference on Intelligent Transportation …, 2016
Probability estimation for predicted-occupancy grids in vehicle safety applications based on machine learning
P Nadarajan, M Botsch
2016 IEEE Intelligent Vehicles Symposium (IV), 1285-1292, 2016
Model-based analysis of sensor-noise in predictive passive safety algorithms
T Dirndorfer, M Botsch, A Knoll
Proceedings of the 22nd Enhanced Safety of Vehicles Conference, 2011
Fahrzeugsicherheit und automatisiertes Fahren: Methoden der Signalverarbeitung und des maschinellen Lernens
M Botsch, W Utschick
Carl Hanser Verlag GmbH Co KG, 2020
Real-time crash severity estimation with machine learning and 2d mass-spring-damper model
M Müller, X Long, M Botsch, D Böhmländer, W Utschick
2018 21st International Conference on Intelligent Transportation Systems …, 2018
A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios
A Chaulwar, M Botsch, W Utschick
2017 IEEE Intelligent Vehicles Symposium (IV), 297-303, 2017
Maneuver segmentation for autonomous parking based on ensemble learning
G Notomista, M Botsch
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
Vehicle position estimation with aerial imagery from unmanned aerial vehicles
F Kruber, ES Morales, S Chakraborty, M Botsch
2020 IEEE Intelligent Vehicles Symposium (IV), 2089-2096, 2020
Interpretable feature generation using deep neural networks and its application to lane change detection
O Gallitz, O De Candido, M Botsch, W Utschick
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 3405-3411, 2019
Highway traffic data: macroscopic, microscopic and criticality analysis for capturing relevant traffic scenarios and traffic modeling based on the highD data set
F Kruber, J Wurst, S Chakraborty, M Botsch
arXiv preprint arXiv:1903.04249, 2019
A hybrid machine learning approach for planning safe trajectories in complex traffic-scenarios
A Chaulwar, M Botsch, W Utschick
2016 15th IEEE International Conference on Machine Learning and Applications …, 2016
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