| The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems R Krajewski, J Bock, L Kloeker, L Eckstein 2018 21st international conference on intelligent transportation systems …, 2018 | 1085 | 2018 |
| The ind dataset: A drone dataset of naturalistic road user trajectories at german intersections J Bock, R Krajewski, T Moers, S Runde, L Vater, L Eckstein 2020 IEEE Intelligent Vehicles Symposium (IV), 1929-1934, 2020 | 364 | 2020 |
| The round dataset: A drone dataset of road user trajectories at roundabouts in germany R Krajewski, T Moers, J Bock, L Vater, L Eckstein 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 163 | 2020 |
| A framework for definition of logical scenarios for safety assurance of automated driving H Weber, J Bock, J Klimke, C Roesener, J Hiller, R Krajewski, A Zlocki, ... Traffic injury prevention 20 (sup1), S65-S70, 2019 | 91 | 2019 |
| The exid dataset: A real-world trajectory dataset of highly interactive highway scenarios in germany T Moers, L Vater, R Krajewski, J Bock, A Zlocki, L Eckstein 2022 IEEE Intelligent Vehicles Symposium (IV), 958-964, 2022 | 61 | 2022 |
| Data-driven maneuver modeling using generative adversarial networks and variational autoencoders for safety validation of highly automated vehicles R Krajewski, T Moers, D Nerger, L Eckstein 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 60 | 2018 |
| Data basis for scenario-based validation of HAD on highways J Bock, R Krajewski, L Eckstein, J Klimke, J Sauerbier, A Zlocki 27th Aachen colloquium automobile and engine technology, 8-10, 2018 | 37 | 2018 |
| The conscend dataset: Concrete scenarios from the highd dataset according to alks regulation unece r157 in openx A Tenbrock, A König, T Keutgens, H Weber 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 174-181, 2021 | 31 | 2021 |
| 2018 21st International Conference on Intelligent Transportation Systems (ITSC) R Krajewski, J Bock, L Kloeker, L Eckstein IEEE, 2018 | 30 | 2018 |
| Decoupled cooperative trajectory optimization for connected highly automated vehicles at urban intersections R Krajewski, P Themann, L Eckstein 2016 IEEE Intelligent Vehicles Symposium (IV), 741-746, 2016 | 19 | 2016 |
| Béziervae: Improved trajectory modeling using variational autoencoders for the safety validation of highly automated vehicles R Krajewski, T Moers, A Meister, L Eckstein 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 3788-3795, 2019 | 18 | 2019 |
| Discrete dynamic optimization in automated driving systems to improve energy efficiency in cooperative networks P Themann, R Krajewski, L Eckstein 2014 IEEE Intelligent Vehicles Symposium Proceedings, 370-375, 2014 | 17 | 2014 |
| The ind dataset: A drone dataset of naturalistic vehicle trajectories at german intersections J Bock, R Krajewski, T Moers, L Vater, S Runde, L Eckstein arXiv preprint arXiv:1911.07602, 2019 | 13 | 2019 |
| Using drones as reference sensors for neural-networks-based modeling of automotive perception errors R Krajewski, M Hoss, A Meister, F Thomsen, J Bock, L Eckstein 2020 IEEE Intelligent Vehicles Symposium (IV), 708-715, 2020 | 10 | 2020 |
| Highly accurate scenario and reference data for automated driving J Bock, L Vater, R Krajewski, T Moers ATZ worldwide 123 (5), 50-55, 2021 | 8 | 2021 |
| VeGAN: Using GANs for augmentation in latent space to improve the semantic segmentation of vehicles in images from an aerial perspective R Krajewski, T Moers, L Eckstein 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 1440-1448, 2019 | 7 | 2019 |
| Drones as a tool for the development and safety validation of highly automated driving R Krajewski, J Bock, L Eckstein Aachener Kolloquium 2019, 2019 | 7 | 2019 |
| Comparison of Camera-Equipped Drones and Infrastructure Sensors for Creating Trajectory Datasets of Road Users. A Kloeker, R Krajewski, L Eckstein VEHITS, 161-170, 2021 | 4 | 2021 |
| An automated analysis framework for trajectory datasets C Glasmacher, R Krajewski, L Eckstein arXiv preprint arXiv:2202.07438, 2022 | 3 | 2022 |
| Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles R Krajewski, L Vater, M Klimke, T Moers, J Bock, L Eckstein 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 1 | 2021 |
Lutz EcksteinLeiter des Instituts für Kraftfahrzeuge (ika), RWTH Aachen UniversityBestätigte E-Mail-Adresse bei ika.rwth-aachen.de
