TY - INPR A1 - Novicki Neto, Leonardo A1 - Reway, Fabio A1 - Poledna, Yuri A1 - Funk Drechsler, Maikol A1 - Parente Ribeiro, Eduardo A1 - Huber, Werner A1 - Icking, Christian T1 - TWICE Dataset: Digital Twin of Test Scenarios in a Controlled Environment N2 - Ensuring the safe and reliable operation of autonomous vehicles under adverse weather remains a significant challenge. To address this, we have developed a comprehensive dataset composed of sensor data acquired in a real test track and reproduced in the laboratory for the same test scenarios. The provided dataset includes camera, radar, LiDAR, inertial measurement unit (IMU), and GPS data recorded under adverse weather conditions (rainy, night-time, and snowy conditions). We recorded test scenarios using objects of interest such as car, cyclist, truck and pedestrian -- some of which are inspired by EURONCAP (European New Car Assessment Programme). The sensor data generated in the laboratory is acquired by the execution of simulation-based tests in hardware-in-the-loop environment with the digital twin of each real test scenario. The dataset contains more than 2 hours of recording, which totals more than 280GB of data. Therefore, it is a valuable resource for researchers in the field of autonomous vehicles to test and improve their algorithms in adverse weather conditions, as well as explore the simulation-to-reality gap. UR - https://doi.org/10.48550/arXiv.2310.03895 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2310.03895 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59887 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Aksoy, Eren Erdal A1 - Raisuddin, Abu Mohammed A1 - Holmblad, Jesper A1 - Haghighi, Hamed A1 - Poledna, Yuri A1 - Funk Drechsler, Maikol A1 - Donzella, Valentina T1 - Rehearse-3d: A Multi-Modal Emulated Rain Dataset for 3d Point Cloud De-Raining T2 - SSRN UR - https://dx.doi.org/10.2139/ssrn.5360105 Y1 - 2025 UR - https://dx.doi.org/10.2139/ssrn.5360105 PB - Elsevier CY - Amsterdam ER -