Michael Botsch

发表

Highway traffic data: macroscopic, microscopic and criticality analysis for capturing relevant traffic scenarios and traffic modeling based on the highD data set.

Samarjit Chakraborty, Friedrich Kruber, Jonas Wurst, 2019, 1903.04249.

Situation aspect modelling and classification using the Scenario Based Random Forest algorithm for convoy merging situations

Markus Maurer, Michael Botsch, Karl-Heinz Siedersberger, 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

Wireless Communication System for the Validation of Autonomous Driving Functions on Full-Scale Vehicles

Andrés García Higuera, Michael Botsch, Eduardo Sánchez Morales, 2018, 2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES).

A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios

Wolfgang Utschick, Michael Botsch, Amit Chaulwar, 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).

Machine Learning Based Prediction of Crash Severity Distributions for Mitigation Strategies

Wolfgang Utschick, Michael Botsch, Marcus Muller, 2018 .

A method for assigning a transmitter to a detected object in the vehicle-to-vehicle communication and vehicle

Michael Botsch, Sebastian Engel, Hendrik Rößler, 2012 .

Relative Motion Estimation Based on Sensor Eigenfusion Using a Stereoscopic Vision System and Adaptive Statistical Filtering

Michael Botsch, Gennaro Notomista, Mario Selvaggio, 2016 .

Construction of interpretable Radial Basis Function classifiers based on the Random Forest kernel

Josef A. Nossek, Michael Botsch, J. Nossek, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A Hybrid Machine Learning Approach for Planning Safe Trajectories in Complex Traffic-Scenarios

Wolfgang Utschick, Michael Botsch, Amit Chaulwar, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

Parallel Multi-Hypothesis Algorithm for Criticality Estimation in Traffic and Collision Avoidance

Philipp Slusallek, Richard Membarth, Michael Botsch, 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).

A fast airplane boarding strategy using online seat assignment based on passenger classification

Stanislao Grazioso, Michael Botsch, Gennaro Notomista, 2016 .

Interpretable Machine Learning Structure for an Early Prediction of Lane Changes

Oliver De Candido, Oliver Gallitz, Ron Melz, 2020, ICANN.

Maneuver segmentation for autonomous parking based on ensemble learning

Michael Botsch, Gennaro Notomista, M. Botsch, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Collision and / or passenger protection system for a motor vehicle and method thereof

Michael Botsch, Christian Weiss, Keck Frank, 2008 .

Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm

Sebastian Sardiña, Michael Botsch, Parthasarathy Nadarajan, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Complexity reduction using the Random Forest classifier in a collision detection algorithm

Christoph Lauer, Michael Botsch, M. Botsch, 2010, 2010 IEEE Intelligent Vehicles Symposium.

DRIVER ASSISTANCE AND INTEGRAL SAFETY

Michael Botsch, Horst Pankalla, Ralf Held, 2010 .

Probability estimation for Predicted-Occupancy Grids in vehicle safety applications based on machine learning

Michael Botsch, Parthasarathy Nadarajan, M. Botsch, 2016, 2016 IEEE Intelligent Vehicles Symposium (IV).

Real-Time Crash Severity Estimation with Machine Learning and 2D Mass-Spring-Damper Model

Wolfgang Utschick, Michael Botsch, Dennis Böhmländer, 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

Planning of Safe Trajectories in Dynamic Multi-Object Traffic-Scenarios

Michael Botsch, Thomas Miehling, Amit Chaulwar, 2016 .

A simulation framework for vehicle safety testing – Ein Simulationsframework für die Absicherung von Fahrzeugsicherheitsfunktionen

Wolfgang Utschick, Michael Botsch, Dennis Bohmlander, 2018 .

Collision and / or personal protection system for a motor vehicle

Christian Weiss, Michael Botsch, Andreas Kuhn, 2006 .

An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization

Friedrich Kruber, Jonas Wurst, Michael Botsch, 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

Model-Based Analysis of Sensor-Noise in Predictive Passive Safety Algorithms

Alois Knoll, Michael Botsch, Tobias Dirndorfer, 2011 .

Generation of Reference Trajectories for Safe Trajectory Planning

Wolfgang Utschick, Michael Botsch, Amit Chaulwar, 2018, ICANN.

A statistical learning approach for estimating the reliability of crash severity predictions

Wolfgang Utschick, Michael Botsch, Dennis Böhmländer, 2016, 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC).

Feature Selection for Change Detection in Multivariate Time-Series

Josef A. Nossek, Michael Botsch, J. Nossek, 2007, 2007 IEEE Symposium on Computational Intelligence and Data Mining.

A method for the preventive protection of occupants of a vehicle before a collision

Michael Botsch, Stefan Katzenbogen, 2012 .

Machine Learning Architectures for the Estimation of Predicted Occupancy Grids in Road Traffic

Michael Botsch, Sebastian Sardina, Parthasarathy Nadarajan, 2018 .

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

Samarjit Chakraborty, Friedrich Kruber, Jonas Wurst, 2019, 2019 IEEE Intelligent Vehicles Symposium (IV).

A Machine Learning Approach for the Segmentation of Driving Maneuvers and its Application in Autonomous Parking

Michael Botsch, Gennaro Notomista, M. Botsch, 2017, J. Artif. Intell. Soft Comput. Res..

Supervised Learning via Optimal Control Labeling for Criticality Classification in Vehicle Active Safety

Wolfgang Utschick, Michael Botsch, Stephan Herrmann, 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

Interpretable Early Prediction of Lane Changes Using a Constrained Neural Network Architecture

Oliver Gallitz, Wolfgang Utschick, Michael Botsch, 2021, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC).

Traffic Scenario Clustering by Iterative Optimisation of Self-Supervised Networks Using a Random Forest Activation Pattern Similarity

Jonas Wurst, Michael Botsch, Lakshman Balasubramanian, 2021, 2021 IEEE Intelligent Vehicles Symposium (IV).

Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space

Andreas Tollkühn, Michael Botsch, Thomas Berberich, 2021, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC).

Open-Set Recognition based on the Combination of Deep Learning and Ensemble Method for Detecting Unknown Traffic Scenarios

Friedrich Kruber, Michael Botsch, Lakshman Balasubramanian, 2021, 2021 IEEE Intelligent Vehicles Symposium (IV).

Novelty Detection and Analysis of Traffic Scenario Infrastructures in the Latent Space of a Vision Transformer-Based Triplet Autoencoder

Wolfgang Utschick, Jonas Wurst, Michael Botsch, 2021, 2021 IEEE Intelligent Vehicles Symposium (IV).