TY - INPR A1 - Fidelis, Eduardo A1 - Reway, Fabio A1 - Ribeiro, Herick Y. S. A1 - Campos, Pietro A1 - Huber, Werner A1 - Icking, Christian A1 - Faria, Lester A1 - Schön, Torsten T1 - Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications using Generative Adversarial Networks N2 - The main approaches for simulating FMCW radar are based on ray tracing, which is usually computationally intensive and do not account for background noise. This work proposes a faster method for FMCW radar simulation capable of generating synthetic raw radar data using generative adversarial networks (GAN). The code and pre-trained weights are open-source and available on GitHub. This method generates 16 simultaneous chirps, which allows the generated data to be used for the further development of algorithms for processing radar data (filtering and clustering). This can increase the potential for data augmentation, e.g., by generating data in non-existent or safety-critical scenarios that are not reproducible in real life. In this work, the GAN was trained with radar measurements of a motorcycle and used to generate synthetic raw radar data of a motorcycle traveling in a straight line. For generating this data, the distance of the motorcycle and Gaussian noise are used as input to the neural network. The synthetic generated radar chirps were evaluated using the Frechet Inception Distance (FID). Then, the Range-Azimuth (RA) map is calculated twice: first, based on synthetic data using this GAN and, second, based on real data. Based on these RA maps, an algorithm with adaptive threshold and edge detection is used for object detection. The results have shown that the data is realistic in terms of coherent radar reflections of the motorcycle and background noise based on the comparison of chirps, the RA maps and the object detection results. Thus, the proposed method in this work has shown to minimize the simulation-to-reality gap for the generation of radar data. UR - https://doi.org/10.48550/arXiv.2308.02632 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2308.02632 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59872 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Biank, Sanjana A1 - Huber, Werner A1 - Meyer, Matthias A1 - Hof, Hans-Joachim A1 - Hempen, Thomas T1 - Model-based security and safety assurance for automotive safety systems BT - Extended Abstract T2 - Proceedings of 3. ACM Computer Science in Cars Symposium (CSCS 2019) KW - Model-based Testing KW - Security KW - Safety KW - Verification KW - Validation Y1 - 2019 UR - https://acm-cscs.org/_/2019/ UR - https://cscs19.cispa.saarland/ PB - ACM CY - New York ER - TY - CHAP A1 - Funk Drechsler, Maikol A1 - Peintner, Jakob A1 - Seifert, Georg A1 - Huber, Werner A1 - Riener, Andreas T1 - Mixed Reality Environment for Testing Automated Vehicle and Pedestrian Interaction T2 - Adjunct Proceedings: 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications UR - https://doi.org/10.1145/3473682.3481878 KW - Automated Driving Systems KW - Test Procedures KW - Vehicle-in-the-Loop KW - External Human-Machine Interfaces KW - Sensor stimulation Y1 - 2021 UR - https://doi.org/10.1145/3473682.3481878 SN - 978-1-4503-8641-8 SP - 229 EP - 232 PB - ACM CY - New York ER - TY - CHAP A1 - Peintner, Jakob A1 - Funk Drechsler, Maikol A1 - Reway, Fabio A1 - Seifert, Georg A1 - Huber, Werner A1 - Riener, Andreas ED - Schneegass, Stefan ED - Pfleging, Bastian ED - Kern, Dagmar T1 - Mixed Reality Environment for Complex Scenario Testing T2 - Tagungsband Mensch & Computer 2021 UR - https://doi.org/10.1145/3473856.3474034 Y1 - 2021 UR - https://doi.org/10.1145/3473856.3474034 SN - 978-1-4503-8645-6 SP - 605 EP - 608 PB - ACM CY - New York ER - TY - CHAP A1 - Funk Drechsler, Maikol A1 - Seifert, Georg A1 - Peintner, Jakob A1 - Reway, Fabio A1 - Riener, Andreas A1 - Huber, Werner T1 - How Simulation based Test Methods will substitute the Proving Ground Testing? T2 - 2022 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV51971.2022.9827394 KW - Wireless LAN KW - Actuators KW - Virtual environments KW - Systems architecture KW - Cameras KW - Software KW - Delays Y1 - 2022 UR - https://doi.org/10.1109/IV51971.2022.9827394 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-27177 SN - 978-1-6654-8821-1 SP - 903 EP - 908 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Funk Drechsler, Maikol A1 - Peintner, Jakob A1 - Reway, Fabio A1 - Seifert, Georg A1 - Riener, Andreas A1 - Huber, Werner T1 - MiRE, A Mixed Reality Environment for Testing of Automated Driving Functions JF - IEEE Transactions on Vehicular Technology UR - https://doi.org/10.1109/TVT.2022.3160353 KW - human factors KW - road vehicle testing KW - vehicle safety KW - virtual reality Y1 - 2022 UR - https://doi.org/10.1109/TVT.2022.3160353 SN - 0018-9545 SN - 1939-9359 VL - 71 IS - 4 SP - 3443 EP - 3456 PB - IEEE CY - New York ER - TY - CHAP A1 - Peintner, Jakob A1 - Funk Drechsler, Maikol A1 - Manger, Carina A1 - Seifert, Georg A1 - Reway, Fabio A1 - Huber, Werner A1 - Riener, Andreas T1 - Comparing Different Pedestrian Representations for Testing Automated Driving Functions in Mixed Reality Environments T2 - Proceedings of the International Conference on Vehicle Electronics and Safety (ICVES 2022) UR - https://doi.org/10.1109/ICVES56941.2022.9986669 KW - Target tracking KW - Roads KW - Mixed reality KW - Virtual environments KW - Motion capture KW - Complexity theory KW - Safety Y1 - 2022 UR - https://doi.org/10.1109/ICVES56941.2022.9986669 SN - 978-1-6654-7698-0 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Wachtel Granado, Diogo A1 - Queiroz, Samuel A1 - Schön, Torsten A1 - Huber, Werner A1 - Faria, Lester T1 - A novel Conditional Generative Adversarial Networks for Automotive Radar Range-Doppler Targets Synthetic Generation T2 - 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC57777.2023.10422067 Y1 - 2024 UR - https://doi.org/10.1109/ITSC57777.2023.10422067 SN - 979-8-3503-9946-2 SP - 3964 EP - 3969 PB - IEEE CY - Piscataway ER - TY - INPR A1 - Chandra Sekaran, Karthikeyan A1 - Geisler, Markus A1 - Rößle, Dominik A1 - Mohan, Adithya A1 - Cremers, Daniel A1 - Utschick, Wolfgang A1 - Botsch, Michael A1 - Huber, Werner A1 - Schön, Torsten T1 - UrbanIng-V2X: A Large-Scale Multi-Vehicle, Multi-Infrastructure Dataset Across Multiple Intersections for Cooperative Perception UR - https://doi.org/10.48550/arXiv.2510.23478 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2510.23478 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Denk, Florian A1 - Himmels, Chantal A1 - Andreev, Vladislav A1 - Lindner, Johannes A1 - Syed, Arslan Ali A1 - Riener, Andreas A1 - Huber, Werner A1 - Kates, Ronald T1 - Studying Interactions of Motorists and Vulnerable Road Users: Empirical Comparison of Test Track and Simulator Experiments T2 - 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC57777.2023.10421865 Y1 - 2024 UR - https://doi.org/10.1109/ITSC57777.2023.10421865 SN - 979-8-3503-9946-2 SP - 992 EP - 999 PB - IEEE CY - Piscataway ER -