TY - JOUR A1 - Sequeira, Gerald Joy A1 - Patel, Akshay A1 - Afraj, Shahabaz A1 - Lugner, Robert A1 - Brandmeier, Thomas T1 - FEM-based methodology for crash severity estimation in frontal crash scenarios JF - IOP Conference Series: Materials Science and Engineering N2 - With the technological development of forward-looking sensors, researchers are exploring their use not only for advanced driver assistance systems but also to gain important pre-crash information. Based on this pre-crash information, if the occupant motion inside the vehicle structure can be predicted for the oncoming crash scenario, then an optimal restraint strategy can be planned before the crash. This paper introduces a two-step FEM simulation based methodology for predicting the occupant severity in head-on crash scenarios. In the first step, we simulate the vehicle level model with different impact positions and relative approach angles. The results of these simulations, linear velocities in the longitudinal and lateral direction and angular velocities (roll, pitch, and yaw) during in-crash phase are the loading conditions for next simulation step (occupant level). This step simulates the motion of the driver in different crash scenarios. In this paper, we investigate the head, neck, and chest injury risks from vehicle-to-vehicle crash both traveling at 50 kilometers per hour. Prediction of the head injury criterion, identifying the cases where additional deployment of side-airbags and discussion of injury criteria with contour plots are the main outcome of this paper. UR - https://doi.org/10.1088/1757-899X/831/1/012019 Y1 - 2020 UR - https://doi.org/10.1088/1757-899X/831/1/012019 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13159 SN - 1757-899X SN - 1757-8981 VL - 2020 IS - 831 PB - IOP CY - Bristol ER - TY - CHAP A1 - Fadl, Islam A1 - Schön, Torsten A1 - Behret, Valentino A1 - Brandmeier, Thomas A1 - Palme, Frank A1 - Helmer, Thomas ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Environment Setup and Model Benchmark of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 3) N2 - Adverse meteorological conditions, particularly fog and rain, present significant challenges to computer vision algorithms and autonomous systems. This work presents MuFoRa a novel, controllable, and measured multimodal dataset recorded at CARISSMA’s indoor test facility, specifically designed to assess perceptual difficulties in foggy and rainy environments. The dataset bridges research gap in the public benchmarking datasets, where quantifiable weather parameters are lacking. The proposed dataset comprises synchronized data from two sensor modalities: RGB stereo cameras and LiDAR sensors, captured under varying intensities of fog and rain. The dataset incorporates synchronized meteorological annotations, such as visibility through fog and precipitation levels of rain, and the study contributes a detailed explanation of the diverse weather effects observed during data collection in the methods section. The dataset’s utility is demonstrated through a baseline evaluation example, asse ssing the performance degradation of state-of-the-art YOLO11 and DETR 2D object detection algorithms under controlled and quantifiable adverse weather conditions. The public release of the dataset (https://doi.org/10.5281/zenodo.14175611) facilitates various benchmarking and quantitative assessments of advanced multimodal computer vision and deep learning models under the challenging conditions of fog and rain. UR - https://doi.org/10.5220/0013307900003912 Y1 - 2025 UR - https://doi.org/10.5220/0013307900003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58070 SN - 978-989-758-728-3 SP - 729 EP - 737 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Sezgin, Fatih A1 - Vriesman, Daniel A1 - Steinhauser, Dagmar A1 - Lugner, Robert A1 - Brandmeier, Thomas T1 - Safe Autonomous Driving in Adverse Weather: Sensor Evaluation and Performance Monitoring T2 - IEEE IV 2023: Symposium Proceedings UR - https://doi.org/10.1109/IV55152.2023.10186596 Y1 - 2023 UR - https://doi.org/10.1109/IV55152.2023.10186596 SN - 979-8-3503-4691-6 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Vriesman, Daniel A1 - Junior, Alceu Britto A1 - Zimmer, Alessandro A1 - Brandmeier, Thomas T1 - Multimodal Early Fusion of Automotive Sensors based on Autoencoder Network: An anchor-free approach for Vehicle 3D Detection T2 - 2023 26th International Conference on Information Fusion (FUSION) UR - https://doi.org/10.23919/FUSION52260.2023.10224140 KW - early fusion KW - lidar KW - camera KW - radar KW - vehicle detection Y1 - 2023 UR - https://doi.org/10.23919/FUSION52260.2023.10224140 SN - 979-8-89034-485-4 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Graf, Michael A1 - Vriesman, Daniel A1 - Brandmeier, Thomas T1 - Testmethodik zur Untersuchung, Validierung und Absicherung von Störeinflüssen auf Umfeldsensoren durch Witterung unter reproduzierbaren Bedingungen T2 - 14. VDI-Tagung Fahrzeugsicherheit, Fahrzeugsicherheit im Kontext neuer, nachhaltiger Mobilitätskonzepte UR - https://doi.org/10.51202/9783181024263-231 Y1 - 2023 UR - https://doi.org/10.51202/9783181024263-231 SN - 978-3-18-102426-3 SN - 978-3-18-092426-7 SP - 231 EP - 248 PB - VDI Verlag CY - Düsseldorf ER - TY - CHAP A1 - Chan, Lap Yan A1 - Zimmer, Alessandro A1 - Lopes da Silva, Joed A1 - Brandmeier, Thomas T1 - European Union dataset and annotation tool for real time automatic license plate detection and blurring T2 - 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC) UR - https://doi.org/10.1109/ITSC45102.2020.9294240 KW - european license plate dataset KW - machine learning KW - license plate detector Y1 - 2020 UR - https://doi.org/10.1109/ITSC45102.2020.9294240 SN - 978-1-7281-4149-7 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Lopes da Silva, Joed A1 - Tabata, Alan Naoto A1 - Cardoso Broto, Lucas A1 - Pereira Cocron, Marta A1 - Zimmer, Alessandro A1 - Brandmeier, Thomas ED - Campilho, Aurélio ED - Karray, Fakhri ED - Wang, Zhou T1 - Open Source Multipurpose Multimedia Annotation Tool T2 - Image Analysis and Recognition: 17th International Conference, ICIAR 2020, Proceedings, Part I UR - https://doi.org/10.1007/978-3-030-50347-5_31 KW - open source KW - video annotation KW - multipurpose KW - generic annotation Y1 - 2020 UR - https://doi.org/10.1007/978-3-030-50347-5_31 SN - 978-3-030-50346-8 SN - 978-3-030-50347-5 SN - 0302-9743 SN - 1611-3349 SP - 356 EP - 367 PB - Springer CY - Cham ER - TY - CHAP A1 - Cardoso Broto, Lucas A1 - Okimoto, Maria L.R. A1 - Pereira Cocron, Marta A1 - Zimmer, Alessandro A1 - Brandmeier, Thomas ED - Yurish, Sergey Y. T1 - Application of Low-cost Pulse Radar for Heart Rate Detection in Vehicle Interior T2 - Sensors and Electronic Instrumentation Advances: Proceedings of the 6th International Conference on Sensors and Electronic Instrumentation Advances and Frequency & Time: Proceedings of the 2nd IFSA Frequency & Time Conference Y1 - 2020 UR - https://www.seia-conference.com/publications.html SN - 978-84-09-23483-7 SP - 99 EP - 104 PB - IFSA CY - Castelldefels ER - TY - CHAP A1 - Sequeira, Gerald Joy A1 - Elnagdy, Elnagdy A1 - Danapal, Gokulesh A1 - Lugner, Robert A1 - Jumar, Ulrich A1 - Brandmeier, Thomas T1 - Investigation of Different Classification Algorithms for Predicting Occupant Injury Criterion to Decide the Required Restraint Strategy T2 - 2021 IEEE International Intelligent Transportation Systems Conference (ITSC) UR - https://doi.org/10.1109/ITSC48978.2021.9564868 KW - pre-crash injury prediction KW - Advanced Vehicle Safety KW - machine learning Y1 - 2021 UR - https://doi.org/10.1109/ITSC48978.2021.9564868 SN - 978-1-7281-9142-3 SP - 204 EP - 210 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Tomal Ribas, Luis Gustavo A1 - Pereira Cocron, Marta A1 - Lopes Da Silva, Joed A1 - Zimmer, Alessandro A1 - Brandmeier, Thomas T1 - In-Cabin vehicle synthetic data to test Deep Learning based human pose estimation models T2 - 2021 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV48863.2021.9576020 KW - Human Pose Estimation KW - in-cabin vehicle monitoring KW - OpenPose KW - Mask R-CNN Y1 - 2021 UR - https://doi.org/10.1109/IV48863.2021.9576020 SN - 978-1-7281-5394-0 SP - 610 EP - 615 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Sequeira, Gerald Joy A1 - Harlapur, Bhuvan A1 - Lugner, Robert A1 - Brandmeier, Thomas T1 - Investigation of three-arc contour prediction algorithm on KITTI LiDAR raw data set T2 - 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall): Proceedings UR - https://doi.org/10.1109/VTC2021-Fall52928.2021.9625355 KW - vehicular and wireless technologies KW - laser radar KW - trajectory planning KW - shape KW - roads KW - image edge detection KW - transportation Y1 - 2021 UR - https://doi.org/10.1109/VTC2021-Fall52928.2021.9625355 SN - 978-1-6654-1368-8 PB - IEEE CY - Piscataway ER -