@unpublished{NovickiNetoRewayPolednaetal.2023, author = {Novicki Neto, Leonardo and Reway, Fabio and Poledna, Yuri and Funk Drechsler, Maikol and Parente Ribeiro, Eduardo and Huber, Werner and Icking, Christian}, title = {TWICE Dataset: Digital Twin of Test Scenarios in a Controlled Environment}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2310.03895}, year = {2023}, abstract = {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their algorithms in adverse weather conditions, as well as explore the simulation-to-reality gap.}, language = {en} } @unpublished{FidelisRewayRibeiroetal.2023, author = {Fidelis, Eduardo and Reway, Fabio and Ribeiro, Herick Y. S. and Campos, Pietro and Huber, Werner and Icking, Christian and Faria, Lester and Sch{\"o}n, Torsten}, title = {Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications using Generative Adversarial Networks}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2308.02632}, year = {2023}, abstract = {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.}, language = {en} } @inproceedings{CristofoliDuarteSilvaFunkDrechslerPolednaetal.2023, author = {Crist{\´o}foli Duarte Silva, Let{\´i}cia and Funk Drechsler, Maikol and Poledna, Yuri and Huber, Werner and Antonio Fiorentin, Thiago}, title = {Synthetic Extreme Weather for AI Training: Concept and Validation}, booktitle = {Proceedings: 2023 Third International Conference on Digital Data Processing, DDP 2023}, editor = {Ariwa, Ezendu and Fong, Simon}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-2901-8}, doi = {https://doi.org/10.1109/DDP60485.2023.00044}, pages = {188 -- 194}, year = {2023}, language = {en} } @inproceedings{PolednaRewayFunkDrechsleretal.2023, author = {Poledna, Yuri and Reway, Fabio and Funk Drechsler, Maikol and Huber, Werner and Icking, Christian and Parente Ribeiro, Eduardo}, title = {An Open-Source High-Level Fusion Algorithm in ROS for Automated Driving Applications}, booktitle = {Proceedings: 2022 10th International Conference in Software Engineering Research and Innovation (CONISOFT 2022)}, editor = {Ju{\´a}rez-Ram{\´i}rez, Reyes and Fern{\´a}ndez y Fern{\´a}ndez, Carlos and Perez Gonzalez, Hector G. and Ram{\´i}rez-Noriega, Alan and Jim{\´e}nez, Samantha and Guerra-Garc{\´i}a, C{\´e}sar and Licea Sandoval, Guillermo}, publisher = {IEEE}, address = {Los Alamitos}, isbn = {978-1-6654-6126-9}, doi = {https://doi.org/10.1109/CONISOFT55708.2022.00031}, pages = {174 -- 181}, year = {2023}, language = {en} } @article{FunkDrechslerSharmaRewayetal.2022, author = {Funk Drechsler, Maikol and Sharma, Varun and Reway, Fabio and Sch{\"u}tz, Christoph and Huber, Werner}, title = {Dynamic Vehicle-in-the-Loop: A Novel Method for Testing Automated Driving Functions}, volume = {5}, pages = {12-05-04-0029}, journal = {SAE International Journal of Connected and Automated Vehicles}, number = {4}, publisher = {SAE International}, address = {Warrendale}, issn = {2574-0741}, doi = {https://doi.org/10.4271/12-05-04-0029}, year = {2022}, abstract = {In automated driving functions (ADF) testing, novel methods have been developed to allow the combination of hardware and simulation to ensure safety in usage even at an early stage of development. This article proposes an architecture to integrate an entire test vehicle—denominated Dynamic Vehicle-in-the-Loop (DynViL)—in a virtual environment. This approach enables the interaction of a real vehicle with virtual traffic participants. The vehicle is physically tested on an empty track, but connected to the CARLA simulator, in which virtual driving scenarios are created. The simulated environment is transmitted to the vehicle driving function which controls the real vehicle in reaction to the virtual objects perceived in simulation. Furthermore, the performance of the DynViL in different test scenarios is evaluated. The results show that the reproducibility of the tests with the DynViL is satisfactory. Furthermore, the results indicate that the deviation between simulation and DynViL variates according to the vehicle speed and the complexity of the scenario. Based on the performance of the DynViL in comparison to simulation, the DynViL can be implemented as a complementary test method to be added to the transition between hardware in the loop (HiL) and proving ground. In this test method, erratic or unexpected behavior generated by the driving function and controllers can be detected in the real vehicle dynamics in a risk-free manner.}, language = {en} } @inproceedings{WachtelGranadoSchuesslervondemBusscheHuennefeldetal.2024, author = {Wachtel Granado, Diogo and Sch{\"u}ßler, Christian and von dem Bussche-H{\"u}nnefeld, Tetmar and Rothmeier, Thomas and Vossiek, Martin and Huber, Werner}, title = {Evaluation of Automotive Radar Simulation Tools for Adverse Weather Conditions: A Comparative Analysis of Real Measurement, HFSS and Monte-Carlo GO Methods}, booktitle = {2024 IEEE Radar Conference (RadarConf24) Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-2920-9}, doi = {https://doi.org/10.1109/RadarConf2458775.2024.10549398}, year = {2024}, language = {en} } @inproceedings{WachtelGranadoRothmeiervondemBusscheHuennefeldetal.2024, author = {Wachtel Granado, Diogo and Rothmeier, Thomas and von dem Bussche-H{\"u}nnefeld, Tetmar and Huber, Werner and Vossiek, Martin}, title = {Radar in the Rain: Understanding and Simulating Environmental Effects on ADAS Radar Sensors}, booktitle = {2024 IEEE Radar Conference (RadarConf24) Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-2920-9}, doi = {https://doi.org/10.1109/RadarConf2458775.2024.10548570}, year = {2024}, language = {en} } @inproceedings{WachtelGranadoTasabatRothmeieretal.2025, author = {Wachtel Granado, Diogo and Tasabat, Sinan and Rothmeier, Thomas and Crist{\´o}foli Duarte Silva, Let{\´i}cia and Huber, Werner}, title = {Exploring Synthetic Radar Data and Deep Learning for Road User Classification in Autonomous Vehicles}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10919565}, pages = {2021 -- 2026}, year = {2025}, language = {en} } @inproceedings{WachtelGranadoTrevisolRothmeieretal.2025, author = {Wachtel Granado, Diogo and Trevisol, Heitor Derder and Rothmeier, Thomas and Nassu, Bogdan Tomoyuki and Huber, Werner}, title = {Navigating on Adverse Weather: Enhancing LiDAR-Based Detection with the DBSPRY Dataset}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10920224}, pages = {4034 -- 4039}, year = {2025}, language = {en} } @inproceedings{RothmeierDalVescoHogerNassuetal.2025, author = {Rothmeier, Thomas and Dal Vesco Hoger, Mayara and Nassu, Bogdan Tomoyuki and Huber, Werner and Knoll, Alois}, title = {Out of the Box: Weather Augmentation for Enhanced Detection in Bad Visibility Conditions}, booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-0592-9}, doi = {https://doi.org/10.1109/ITSC58415.2024.10919529}, pages = {1410 -- 1417}, year = {2025}, language = {en} } @inproceedings{WachtelGranadoRothmeierCristofoliDuarteSilvaetal.2024, author = {Wachtel Granado, Diogo and Rothmeier, Thomas and Crist{\´o}foli Duarte Silva, Let{\´i}cia and Vossiek, Martin and Huber, Werner}, title = {Simulation and Validation of Automotive Radar Performance with Water Spray Over Radome}, booktitle = {2024 IEEE Sensors 2024: Conference Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-6351-7}, doi = {https://doi.org/10.1109/SENSORS60989.2024.10784774}, year = {2024}, language = {en} } @inproceedings{WachtelGranadoSchroederRewayetal.2022, author = {Wachtel Granado, Diogo and Schr{\"o}der, Sabine and Reway, Fabio and Huber, Werner and Vossiek, Martin}, title = {Validation of a radar sensor model under non-ideal conditions for testing automated driving systems}, booktitle = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7921-9}, doi = {https://doi.org/10.1109/IVWorkshops54471.2021.9669205}, pages = {83 -- 89}, year = {2022}, language = {en} } @inproceedings{FunkDrechslerPolednaHjortetal.2024, author = {Funk Drechsler, Maikol and Poledna, Yuri and Hjort, Mattias and Kharrazi, Sogol and Huber, Werner}, title = {Vehicle Dynamics Parameter Estimation Methodology for Virtual Automated Driving Testing}, booktitle = {2024 IEEE International Automated Vehicle Validation Conference (IAVVC), Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-5407-2}, doi = {10.1109/IAVVC63304.2024.10786416}, year = {2024}, language = {en} } @inproceedings{BiankHuberMeyeretal.2019, author = {Biank, Sanjana and Huber, Werner and Meyer, Matthias and Hof, Hans-Joachim and Hempen, Thomas}, title = {Model-based security and safety assurance for automotive safety systems}, booktitle = {Proceedings of 3. ACM Computer Science in Cars Symposium (CSCS 2019)}, subtitle = {Extended Abstract}, publisher = {ACM}, address = {New York}, url = {https://acm-cscs.org/_/2019/}, year = {2019}, language = {en} } @inproceedings{RewayHoffmannWachtelGranadoetal.2021, author = {Reway, Fabio and Hoffmann, Abdul and Wachtel Granado, Diogo and Huber, Werner and Knoll, Alois and Parente Ribeiro, Eduardo}, title = {Test Method for Measuring the Simulation-to-Reality Gap of Camera-based Object Detection Algorithms for Autonomous Driving}, booktitle = {2020 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6673-5}, doi = {https://doi.org/10.1109/IV47402.2020.9304567}, pages = {1249 -- 1256}, year = {2021}, language = {en} } @inproceedings{RothmeierHuber2021, author = {Rothmeier, Thomas and Huber, Werner}, title = {Performance Evaluation of Object Detection Algorithms Under Adverse Weather Conditions}, booktitle = {Intelligent Transport Systems, From Research and Development to the Market Uptake: 4th EAI International Conference, INTSYS 2020; Virtual Event, December 3, 2020: Proceedings}, editor = {Martins, Ana L{\´u}cia and Amaro Ferreira, Joao Carlos and Kocian, Alexander and Costa, Vera}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-71454-3}, doi = {https://doi.org/10.1007/978-3-030-71454-3_13}, pages = {211 -- 222}, year = {2021}, language = {en} } @inproceedings{SeifertHempenHuber2019, author = {Seifert, Georg and Hempen, Thomas and Huber, Werner}, title = {Aufbau einer Mixed-Reality-Versuchsumgebung zur Absicherung autonomer Systeme}, booktitle = {Echtzeit 2019: Autonome Systeme - 50 Jahre PEARL}, publisher = {Springer}, address = {Wiesbaden}, isbn = {978-3-658-27808-3}, doi = {https://doi.org/10.1007/978-3-658-27808-3_5}, pages = {43 -- 52}, year = {2019}, language = {de} } @inproceedings{FunkDrechslerPeintnerSeifertetal.2021, author = {Funk Drechsler, Maikol and Peintner, Jakob and Seifert, Georg and Huber, Werner and Riener, Andreas}, title = {Mixed Reality Environment for Testing Automated Vehicle and Pedestrian Interaction}, booktitle = {Adjunct Proceedings: 13th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications}, publisher = {ACM}, address = {New York}, isbn = {978-1-4503-8641-8}, doi = {https://doi.org/10.1145/3473682.3481878}, pages = {229 -- 232}, year = {2021}, language = {en} } @inproceedings{PeintnerFunkDrechslerRewayetal.2021, author = {Peintner, Jakob and Funk Drechsler, Maikol and Reway, Fabio and Seifert, Georg and Huber, Werner and Riener, Andreas}, title = {Mixed Reality Environment for Complex Scenario Testing}, booktitle = {Tagungsband Mensch \& Computer 2021}, editor = {Schneegass, Stefan and Pfleging, Bastian and Kern, Dagmar}, publisher = {ACM}, address = {New York}, isbn = {978-1-4503-8645-6}, doi = {https://doi.org/10.1145/3473856.3474034}, pages = {605 -- 608}, year = {2021}, language = {en} } @inproceedings{FunkDrechslerSeifertPeintneretal.2022, author = {Funk Drechsler, Maikol and Seifert, Georg and Peintner, Jakob and Reway, Fabio and Riener, Andreas and Huber, Werner}, title = {How Simulation based Test Methods will substitute the Proving Ground Testing?}, booktitle = {2022 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8821-1}, doi = {https://doi.org/10.1109/IV51971.2022.9827394}, pages = {903 -- 908}, year = {2022}, language = {en} } @article{FunkDrechslerPeintnerRewayetal.2022, author = {Funk Drechsler, Maikol and Peintner, Jakob and Reway, Fabio and Seifert, Georg and Riener, Andreas and Huber, Werner}, title = {MiRE, A Mixed Reality Environment for Testing of Automated Driving Functions}, volume = {71}, journal = {IEEE Transactions on Vehicular Technology}, number = {4}, publisher = {IEEE}, address = {New York}, issn = {0018-9545}, doi = {https://doi.org/10.1109/TVT.2022.3160353}, pages = {3443 -- 3456}, year = {2022}, language = {en} } @inproceedings{PeintnerFunkDrechslerMangeretal.2022, author = {Peintner, Jakob and Funk Drechsler, Maikol and Manger, Carina and Seifert, Georg and Reway, Fabio and Huber, Werner and Riener, Andreas}, title = {Comparing Different Pedestrian Representations for Testing Automated Driving Functions in Mixed Reality Environments}, booktitle = {Proceedings of the International Conference on Vehicle Electronics and Safety (ICVES 2022)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7698-0}, doi = {https://doi.org/10.1109/ICVES56941.2022.9986669}, year = {2022}, language = {en} } @inproceedings{YahyaeiSeifertHempenetal.2022, author = {Yahyaei, Mahdi and Seifert, Georg and Hempen, Thomas and Huber, Werner}, title = {Review of exteroceptive sensors for autonomous driving}, booktitle = {2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-6880-0}, doi = {https://doi.org/10.1109/ITSC55140.2022.9922379}, pages = {4005 -- 4010}, year = {2022}, language = {en} } @inproceedings{RewayFunkDrechslerMurthyetal.2022, author = {Reway, Fabio and Funk Drechsler, Maikol and Murthy, Ravikiran and Poledna, Yuri and Huber, Werner and Icking, Christian}, title = {Simulation-based test methods with an automotive camera-in-the-loop for automated driving algorithms}, booktitle = {2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7095-7}, doi = {https://doi.org/10.1109/ICECCME55909.2022.9988437}, year = {2022}, language = {en} } @inproceedings{BotschHuberBalasubramanianetal.2023, author = {Botsch, Michael and Huber, Werner and Balasubramanian, Lakshman and Flores Fernandez, Alberto and Geisler, Markus and Gudera, Christian and Morales Gomez, Mauricio Rene and Riegl, Peter and S{\´a}nchez Morales, Eduardo and Chandra Sekaran, Karthikeyan and Weinzierl, Michael}, title = {Data Collection and Safety Use Cases in Smart Infrastructures}, booktitle = {15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0112-2}, doi = {https://doi.org/10.1145/3581961.3609858}, pages = {333 -- 336}, year = {2023}, language = {en} } @inproceedings{RothmeierWachtelGranadovondemBusscheHuennefeldetal.2023, author = {Rothmeier, Thomas and Wachtel Granado, Diogo and von dem Bussche-H{\"u}nnefeld, Tetmar and Huber, Werner}, title = {I Had a Bad Day: Challenges of Object Detection in Bad Visibility Conditions}, booktitle = {IEEE IV 2023 Symposium Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4691-6}, doi = {https://doi.org/10.1109/IV55152.2023.10186674}, year = {2023}, language = {en} } @inproceedings{RothmeierHuberKnoll2024, author = {Rothmeier, Thomas and Huber, Werner and Knoll, Alois}, title = {Time to Shine: Fine-Tuning Object Detection Models with Synthetic Adverse Weather Images}, booktitle = {Proceedings, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2024}, publisher = {IEEE}, address = {Los Alamitos}, isbn = {979-8-3503-1892-0}, doi = {https://doi.org/10.1109/WACV57701.2024.00439}, pages = {4435 -- 4444}, year = {2024}, language = {en} } @inproceedings{WachtelGranadoQueirozSchoenetal.2024, author = {Wachtel Granado, Diogo and Queiroz, Samuel and Sch{\"o}n, Torsten and Huber, Werner and Faria, Lester}, title = {A novel Conditional Generative Adversarial Networks for Automotive Radar Range-Doppler Targets Synthetic Generation}, booktitle = {2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-9946-2}, doi = {https://doi.org/10.1109/ITSC57777.2023.10422067}, pages = {3964 -- 3969}, year = {2024}, language = {en} } @inproceedings{PolednaFunkDrechslerDonzellaetal.2024, author = {Poledna, Yuri and Funk Drechsler, Maikol and Donzella, Valentina and Chan, Pak Hung and Duthon, Pierre and Huber, Werner}, title = {REHEARSE: adveRse wEatHEr datAset for sensoRy noiSe modEls}, booktitle = {2024 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4881-1}, doi = {https://doi.org/10.1109/IV55156.2024.10588491}, pages = {2451 -- 2457}, year = {2024}, language = {en} } @inproceedings{RewayFunkDrechslerWachtelGranadoetal.2020, author = {Reway, Fabio and Funk Drechsler, Maikol and Wachtel Granado, Diogo and Huber, Werner}, title = {Validity Analysis of Simulation-based Testing concerning Free-space Detection in Autonomous Driving}, booktitle = {Proceedings of the 6th International Conference on Vehicle Technology and Intelligent Transport Systems}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-419-0}, issn = {2184-495X}, doi = {https://doi.org/10.5220/0009573705520558}, pages = {552 -- 558}, year = {2020}, language = {en} } @unpublished{ChandraSekaranGeislerRoessleetal.2025, author = {Chandra Sekaran, Karthikeyan and Geisler, Markus and R{\"o}ßle, Dominik and Mohan, Adithya and Cremers, Daniel and Utschick, Wolfgang and Botsch, Michael and Huber, Werner and Sch{\"o}n, Torsten}, title = {UrbanIng-V2X: A Large-Scale Multi-Vehicle, Multi-Infrastructure Dataset Across Multiple Intersections for Cooperative Perception}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2510.23478}, year = {2025}, language = {en} } @article{DenkFroehlingBrunneretal.2024, author = {Denk, Florian and Fr{\"o}hling, Felix and Brunner, Pascal and Huber, Werner and Margreiter, Martin and Bogenberger, Klaus and Kates, Ronald}, title = {Influence of gaze strategies and cognitive load on safeguarding performance of motorists in right-turning scenarios involving potential conflicts with vulnerable road users}, volume = {2025}, journal = {Transportation Research Part F: Traffic Psychology and Behaviour}, number = {109}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1873-5517}, doi = {https://doi.org/10.1016/j.trf.2024.11.012}, pages = {32 -- 49}, year = {2024}, abstract = {In urban traffic, while the fraction of collisions involving Vulnerable Road Users (VRU) is low, their importance is high due to the higher injury risk for VRU. Their infrequent occurrence on average (compared with far more common individual perceptual and behavioral errors by both drivers and VRUs) reflects an underlying fault tolerance in traffic processes. However, the degree of fault tolerance varies among traffic situations. The underlying perceptual and cognitive processes involved are complex and can require a high level of attention and concentration, particularly in situations with intersecting trajectories. These processes can occasionally fail, leading to collision risk. The situation of right-turning motorists (in right-hand-drive countries) encountering cyclists moving straight on a bike lane (with right of way) has a particularly low error tolerance, since motorists must actively scan for cyclists approaching from behind. In order to develop, test and assess solutions that mitigate collision risk in this situation, the behavior-related causation mechanisms need investigation. This is the focus of this article. We conducted a trial on our closed test track with n = 35 subjects. The experiment was designed as a within-subject design with three independent factors: maneuver, target velocity, and cognitive load in an n-back task. The trial included observations of participants' gaze control. A primary research focus was the quality and efficiency of the safeguarding gaze behavior of participants in order to draw conclusions on the causation mechanisms of collisions in this situation. For this purpose we define metrics in order to quantify the quality and efficiency of a specific gaze behavior. Furthermore, we studied the effect of factors cognitive load and target velocity on safety and secondary (n-back) task performance. Remarkably, only four out of 35 participants reached a collision risk of 0\% relating to the defined quality metric. Furthermore, we identified four distinct gaze strategy groups through hierarchical clustering, where one group performed particularly few glances overall. This group showed significant differences with respect to the defined quality metric whereas the other groups showed only slight differences to each other. The results have implications on subsequent crash causation model development.}, language = {en} } @article{NovickiNetoRewayPolednaetal.2025, author = {Novicki Neto, Leonardo and Reway, Fabio and Poledna, Yuri and Funk Drechsler, Maikol and Icking, Christian and Huber, Werner and Parente Ribeiro, Eduardo}, title = {TWICE dataset: digital twin of test scenarios in a controlled environment}, volume = {19}, journal = {International Journal of Vehicle Systems Modelling and Testing (IJVSMT)}, number = {2}, publisher = {Inderscience}, address = {Genf}, issn = {1745-6436}, doi = {https://doi.org/10.1504/IJVSMT.2025.147353}, pages = {152 -- 170}, year = {2025}, language = {en} } @inproceedings{BrunnerDenkHuberetal.2019, author = {Brunner, Pascal and Denk, Florian and Huber, Werner and Kates, Ronald}, title = {Virtual safety performance assessment for automated driving in complex urban traffic scenarios}, booktitle = {2019 IEEE Intelligent Transportation Systems Conference (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-7024-8}, doi = {https://doi.org/10.1109/ITSC.2019.8917517}, pages = {679 -- 685}, year = {2019}, language = {en} } @inproceedings{DenkFroehlingBrunneretal.2023, author = {Denk, Florian and Fr{\"o}hling, Felix and Brunner, Pascal and Huber, Werner and Margreiter, Martin and Bogenberger, Klaus and Kates, Ronald}, title = {Design of an Experiment to Pinpoint Cognitive Failure Processes in the Interaction of Motorists and Vulnerable Road Users}, booktitle = {IEEE IV 2023: Symposium Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4691-6}, doi = {https://doi.org/10.1109/IV55152.2023.10186550}, year = {2023}, language = {en} } @inproceedings{DenkHimmelsAndreevetal.2024, author = {Denk, Florian and Himmels, Chantal and Andreev, Vladislav and Lindner, Johannes and Syed, Arslan Ali and Riener, Andreas and Huber, Werner and Kates, Ronald}, title = {Studying Interactions of Motorists and Vulnerable Road Users: Empirical Comparison of Test Track and Simulator Experiments}, booktitle = {2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-9946-2}, doi = {https://doi.org/10.1109/ITSC57777.2023.10421865}, pages = {992 -- 999}, year = {2024}, language = {en} } @inproceedings{BrunnerLoeckenDenketal.2021, author = {Brunner, Pascal and L{\"o}cken, Andreas and Denk, Florian and Kates, Ronald and Huber, Werner}, title = {Analysis of experimental data on dynamics and behavior of e-scooter riders and applications to the impact of automated driving functions on urban road safety}, booktitle = {2020 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6673-5}, doi = {https://doi.org/10.1109/IV47402.2020.9304835}, pages = {219 -- 225}, year = {2021}, language = {en} } @inproceedings{DenkHuberBrunneretal.2020, author = {Denk, Florian and Huber, Werner and Brunner, Pascal and Kates, Ronald}, title = {The role of perceptual failure and degrading processes in urban traffic accidents: a stochastic computational model for virtual experiments}, booktitle = {2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-4149-7}, doi = {https://doi.org/10.1109/ITSC45102.2020.9294498}, year = {2020}, language = {en} } @inproceedings{UlreichFunkDrechslerPolednaetal.2026, author = {Ulreich, Fabian and Funk Drechsler, Maikol and Poledna, Yuri and Chan, Pak Hung and Herraren, Tuomas and Ebert, Martin and Kaup, Andr{\´e} and Huber, Werner}, title = {Validating Camera Sensor Models for Virtual Testing of Vision Systems in Automated Driving}, booktitle = {2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7778-9}, doi = {https://doi.org/10.1109/ICVES65691.2025.11376043}, pages = {57 -- 64}, year = {2026}, language = {en} } @inproceedings{FunkDrechslerSellPolednaetal.2026, author = {Funk Drechsler, Maikol and Sell, Christoph Dominic and Poledna, Yuri and Huber, Werner}, title = {Accelerating the Approval of Automated Driving Vehicles through standardized XiL test environments}, booktitle = {2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7778-9}, doi = {https://doi.org/10.1109/ICVES65691.2025.11376566}, pages = {183 -- 188}, year = {2026}, language = {en} } @unpublished{SchlampGernerBogenbergeretal.2026, author = {Schlamp, Anna-Lena and Gerner, Jeremias and Bogenberger, Klaus and Huber, Werner and Schmidtner, Stefanie}, title = {ROSA: Roundabout Optimized Speed Advisory with Multi-Agent Trajectory Prediction in Multimodal Traffic}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2602.14780}, year = {2026}, language = {en} } @inproceedings{RothmeierHuber2021, author = {Rothmeier, Thomas and Huber, Werner}, title = {Let it Snow: On the Synthesis of Adverse Weather Image Data}, booktitle = {2021 IEEE International Intelligent Transportation Systems Conference (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-9142-3}, doi = {https://doi.org/10.1109/ITSC48978.2021.9565008}, pages = {3300 -- 3306}, year = {2021}, language = {en} }