TY - CHAP A1 - Dietl, Guido A1 - Botsch, Michael A1 - Dietrich, F. A. A1 - Utschick, Wolfgang T1 - Robust and reduced-rank matrix Wiener filter based on the conjugate gradient algorithm T2 - 2005 IEEE 6th Workshop on Signal Processing Advances in Wireless Communications UR - https://doi.org/10.1109/SPAWC.2005.1506201 Y1 - 2005 UR - https://doi.org/10.1109/SPAWC.2005.1506201 SN - 0-7803-8867-4 SP - 555 EP - 559 PB - IEEE CY - Piscataway ER - TY - INPR A1 - Kalyanasundaram, Abinav A1 - Chandra Sekaran, Karthikeyan A1 - Stäuber, Philipp A1 - Lange, Michael A1 - Utschick, Wolfgang A1 - Botsch, Michael T1 - Uncertainty-Aware Hybrid Machine Learning in Virtual Sensors for Vehicle Sideslip Angle Estimation N2 - Precise vehicle state estimation is crucial for safe and reliable autonomous driving. The number of measurable states and their precision offered by the onboard vehicle sensor system are often constrained by cost. For instance, measuring critical quantities such as the Vehicle Sideslip Angle (VSA) poses significant commercial challenges using current optical sensors. This paper addresses these limitations by focusing on the development of high-performance virtual sensors to enhance vehicle state estimation for active safety. The proposed Uncertainty-Aware Hybrid Learning (UAHL) architecture integrates a machine learning model with vehicle motion models to estimate VSA directly from onboard sensor data. A key aspect of the UAHL architecture is its focus on uncertainty quantification for individual model estimates and hybrid fusion. These mechanisms enable the dynamic weighting of uncertainty-aware predictions from machine learning and vehicle motion models to produce accurate and reliable hybrid VSA estimates. This work also presents a novel dataset named Real-world Vehicle State Estimation Dataset (ReV-StED), comprising synchronized measurements from advanced vehicle dynamic sensors. The experimental results demonstrate the superior performance of the proposed method for VSA estimation, highlighting UAHL as a promising architecture for advancing virtual sensors and enhancing active safety in autonomous vehicles. UR - https://doi.org/10.48550/arXiv.2504.06105 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.06105 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59578 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Wurst, Jonas A1 - Balasubramanian, Lakshman A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Expert-LaSTS: Expert-Knowledge Guided Latent Space for Traffic Scenarios T2 - 2022 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV51971.2022.9827187 KW - clustering KW - novelty detection KW - scenario-based testing KW - deep learning Y1 - 2022 UR - https://doi.org/10.1109/IV51971.2022.9827187 SN - 978-1-6654-8821-1 SP - 484 EP - 491 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Elter, Tim A1 - Dirndorfer, Tobias A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Interaction-aware Prediction of Occupancy Regions based on a POMDP Framework T2 - 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC55140.2022.9922127 KW - Trajectory planning KW - Estimation KW - Collaboration KW - Markov process KW - Complexity theory KW - Reliability KW - Junctions Y1 - 2022 UR - https://doi.org/10.1109/ITSC55140.2022.9922127 SN - 978-1-6654-6880-0 SP - 980 EP - 987 PB - IEEE CY - Piscataway ER - TY - INPR A1 - Neumeier, Marion A1 - Tollkühn, Andreas A1 - Dorn, Sebastian A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Gradient Derivation for Learnable Parameters in Graph Attention Networks UR - https://doi.org/10.48550/arXiv.2304.10939 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2304.10939 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Gallitz, Oliver A1 - de Candido, Oliver A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Interpretable Early Prediction of Lane Changes Using a Constrained Neural Network Architecture T2 - 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) UR - https://doi.org/10.1109/ITSC48978.2021.9564555 Y1 - 2021 UR - https://doi.org/10.1109/ITSC48978.2021.9564555 SN - 978-1-7281-9142-3 SP - 493 EP - 499 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Chaulwar, Amit A1 - Al-Hashimi, Hussein A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Efficient hybrid machine learning algorithm for trajectory planning in critical traffic-scenarios T2 - The 4th International Conference on Intelligent Transportation Engineering, ICITE 2019 UR - https://doi.org/10.1109/ICITE.2019.8880266 KW - Trajectory Planning KW - Hybrid Machine Learning KW - Embedded Implementation Y1 - 2019 UR - https://doi.org/10.1109/ICITE.2019.8880266 SN - 978-1-7281-4553-2 SP - 196 EP - 202 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Gallitz, Oliver A1 - de Candido, Oliver A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Interpretable feature generation using deep neural networks and its application to lane change detection T2 - 2019 IEEE Intelligent Transportation Systems Conference (ITSC) UR - https://doi.org/10.1109/ITSC.2019.8917524 KW - Time series analysis KW - Kernel KW - Convolution KW - Feature extraction KW - Finite impulse response filters KW - Neural networks KW - Heating systems Y1 - 2019 UR - https://doi.org/10.1109/ITSC.2019.8917524 SN - 978-1-5386-7024-8 SP - 3405 EP - 3411 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Botsch, Michael A1 - Dietl, Guido A1 - Utschick, Wolfgang T1 - Iterative Multi-User Detection Using Reduced-Complexity Equalization T2 - TURBO – CODING – 2006: 4th International Symposium on Turbo Codes & Related Topics, 6th International ITG-Conference on Source and Channel Coding KW - Decoding Y1 - 2006 UR - https://www.vde-verlag.de/proceedings-de/442947088.html SN - 978-3-8007-2947-0 PB - VDE CY - Berlin ER - TY - CHAP A1 - Balasubramanian, Lakshman A1 - Wurst, Jonas A1 - Egolf, Robin A1 - Botsch, Michael A1 - Utschick, Wolfgang A1 - Deng, Ke T1 - ExAgt: Expert-guided Augmentation for Representation Learning of Traffic Scenarios T2 - 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC55140.2022.9922453 KW - Representation learning KW - Visualization KW - Codes KW - Self-supervised learning KW - Prediction methods KW - Distortion KW - Stability analysis Y1 - 2022 UR - https://doi.org/10.1109/ITSC55140.2022.9922453 SN - 978-1-6654-6880-0 SP - 1471 EP - 1478 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Neumeier, Marion A1 - Tollkühn, Andreas A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - A Multidimensional Graph Fourier Transformation Neural Network for Vehicle Trajectory Prediction T2 - 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC55140.2022.9922419 KW - Road transportation KW - Computational modeling KW - Computer architecture KW - Predictive models KW - Network architecture KW - Trajectory KW - Decoding Y1 - 2022 UR - https://doi.org/10.1109/ITSC55140.2022.9922419 SN - 978-1-6654-6880-0 SP - 687 EP - 694 PB - IEEE CY - Piscataway ER - TY - BOOK A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Fahrzeugsicherheit und automatisiertes Fahren BT - Methoden der Signalverarbeitung und des maschinellen Lernens UR - https://doi.org/10.3139/9783446468047 Y1 - 2020 UR - https://doi.org/10.3139/9783446468047 SN - 978-3-446-46804-7 SN - 978-3-446-45326-5 PB - Hanser CY - München ER - TY - CHAP A1 - de Candido, Oliver A1 - Koller, Michael A1 - Gallitz, Oliver A1 - Melz, Ron A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - Towards feature validation in time to lane change classification using deep neural networks T2 - 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC45102.2020.9294555 KW - Feature extraction KW - Convolution KW - Computer architecture KW - Road transportation KW - Standards KW - Machine learning algorithms KW - Acceleration Y1 - 2020 UR - https://doi.org/10.1109/ITSC45102.2020.9294555 SN - 978-1-7281-4149-7 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Herrmann, Stephan A1 - Utschick, Wolfgang A1 - Botsch, Michael A1 - Keck, Frank T1 - Supervised learning via optimal control labeling for criticality classification in vehicle active safety T2 - Proceedings: 2015 IEEE 18th International Conference on Intelligent Transportation Systems UR - https://doi.org/10.1109/ITSC.2015.328 KW - vehicles KW - acceleration KW - trajectory KW - collision avoidance KW - tires KW - force KW - optimal control Y1 - 2015 UR - https://doi.org/10.1109/ITSC.2015.328 SN - 978-1-4673-6596-3 SN - 2153-0017 SP - 2024 EP - 2031 PB - IEEE CY - Los Alamitos ER - TY - CHAP A1 - Chaulwar, Amit A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - A Hybrid Machine Learning Approach for Planning Safe Trajectories in Complex Traffic-Scenarios T2 - 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA) UR - https://doi.org/10.1109/ICMLA.2016.0095 KW - Hybrid learning algorithms KW - Trajectory Planning in Road Traffic KW - 3D-ConvNets Y1 - 2016 UR - https://doi.org/10.1109/ICMLA.2016.0095 SN - 978-1-5090-6167-9 SP - 540 EP - 546 PB - IEEE CY - Los Alamitos ER - TY - CHAP A1 - Chaulwar, Amit A1 - Botsch, Michael A1 - Utschick, Wolfgang T1 - A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios T2 - 2017 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IVS.2017.7995735 KW - Acceleration KW - Trajectory KW - Heuristic algorithms KW - Vehicle dynamics KW - Planning KW - Prediction algorithms KW - Roads Y1 - 2017 UR - https://doi.org/10.1109/IVS.2017.7995735 SN - 978-1-5090-4804-5 SP - 297 EP - 303 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Müller, Marcus A1 - Botsch, Michael A1 - Böhmländer, Dennis A1 - Utschick, Wolfgang ED - Klaffke, Werner T1 - A Simulation Framework for Vehicle Safety Testing T2 - Aktive Sicherheit und Automatisieres Fahren : 3. Interdisziplinärer Expertendialog (IEDAS) T2 - Ein Simulationsframework für die Absicherung von Fahrzeugsicherheitsfunktionen Y1 - 2017 SN - 978-3-8169-3405-9 SP - 147 EP - 167 PB - expert Verlag CY - Renningen ER - TY - JOUR A1 - Müller, Marcus A1 - Botsch, Michael A1 - Böhmländer, Dennis A1 - Utschick, Wolfgang T1 - Machine Learning Based Prediction of Crash Severity Distributions for Mitigation Strategies JF - Journal of Advances in Information Technology N2 - In road traffic, critical situations pass by as quickly as they appear. Within the blink of an eye, one has to come to a decision, which can make the difference between a low severity, high severity or fatal crash. Because time is important, a machine learning driven Crash Severity Predictor (CSP) is presented which provides the estimated crash severity distribution of an imminent crash in less than 0.2ms. This is 63⋅ 103 times faster compared to predicting the same distribution through computationally expensive numerical simulations. With the proposed method, even very complex crash data, like the results of Finite Element Method (FEM) simulations, can be made available ahead of a collision. Knowledge, which can be used to prepare occupants and vehicle to an imminent crash, activate and adjust safety measures like airbags or belt tensioners before of a collision or let self-driving vehicles go for the maneuver with the lowest crash severity. Using a real-world crash test it is shown that significant safety potential is left unused if instead of the CSP-proposed driving maneuver, no or the wrong actions are taken. UR - https://doi.org/10.12720/jait.9.1.15-24 KW - crash severity KW - vehicle safety KW - reliable prediction KW - machine learning Y1 - 2018 UR - https://doi.org/10.12720/jait.9.1.15-24 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-24644 SN - 1798-2340 VL - 9 (2018) IS - 1 SP - 15 EP - 24 PB - Engineering and Technology Publishing CY - Rowland Heights (CA) ER - TY - CHAP A1 - Chaulwar, Amit A1 - Botsch, Michael A1 - Utschick, Wolfgang ED - Kurková, Vera ED - Manolopoulos, Yannis ED - Hammer, Barbara ED - Iliadis, Lazaros ED - Maglogiannis, Ilias T1 - Generation of Reference Trajectories for Safe Trajectory Planning T2 - Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks,Rhodes, Greece, October 4–7, 2018 : Proceedings, Part I UR - https://doi.org/10.1007/978-3-030-01418-6_42 KW - Safe trajectory planning KW - Hybrid machine learning KW - Variational autoencoder Y1 - 2018 UR - https://doi.org/10.1007/978-3-030-01418-6_42 SN - 978-3-030-01418-6 SN - 978-3-030-01417-9 SP - 423 EP - 434 PB - Springer CY - Cham ER - TY - CHAP A1 - Gallitz, Oliver A1 - Botsch, Michael A1 - de Candido, Oliver A1 - Utschick, Wolfgang T1 - Validation of Machine Learning Algorithms through Visualization Methods T2 - ELIV-MarketPlace 2018 UR - https://doi.org/10.51202/9783181023389-29 Y1 - 2018 UR - https://doi.org/10.51202/9783181023389-29 SN - 978-3-18-092338-3 SN - 978-3-18-102338-9 SP - 29 EP - 46 PB - VDI Verlag CY - Düsseldorf ER -