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Julian Bock
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2020 – today
- 2022
- [j2]Adrian Zlocki, Alexander König, Julian Bock, Hendrik Weber, Husam Muslim, Hiroki Nakamura, Sandra Préfontaine-Watanabe, Jacobo Antona-Makoshi, Satoshi Taniguchi:
Logical Scenarios Parameterization for Automated Vehicle Safety Assessment: Comparison of Deceleration and Cut-In Scenarios From Japanese and German Highways. IEEE Access 10: 26817-26829 (2022) - [c9]Tobias Moers, Lennart Vater, Robert Krajewski, Julian Bock, Adrian Zlocki, Lutz Eckstein:
The exiD Dataset: A Real-World Trajectory Dataset of Highly Interactive Highway Scenarios in Germany. IV 2022: 958-964 - 2021
- [j1]Maike Scholtes, Lukas Westhofen, Lara Ruth Turner, Katrin Lotto, Michael Schuldes, Hendrik Weber, Nicolas Wagener, Christian Neurohr, Martin Bollmann, Franziska Körtke, Johannes Hiller, Michael Hoss, Julian Bock, Lutz Eckstein:
6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment. IEEE Access 9: 59131-59147 (2021) - [c8]Robert Krajewski, Lennart Vater, Marvin Klimke, Tobias Moers, Julian Bock, Lutz Eckstein:
Drone-based Generation of Sensor Reference and Training Data for Highly Automated Vehicles. ITSC 2021: 3067-3074 - [i4]Alexander Tenbrock, Alexander König, Thomas Keutgens, Julian Bock, Hendrik Weber, Robert Krajewski, Adrian Zlocki:
The ConScenD Dataset: Concrete Scenarios from the highD Dataset According to ALKS Regulation UNECE R157 in OpenX. CoRR abs/2103.09772 (2021) - 2020
- [c7]Robert Krajewski, Tobias Moers, Julian Bock, Lennart Vater, Lutz Eckstein:
The rounD Dataset: A Drone Dataset of Road User Trajectories at Roundabouts in Germany. ITSC 2020: 1-6 - [c6]Robert Krajewski, Michael Hoss, Adrian Meister, Fabian Thomsen, Julian Bock, Lutz Eckstein:
Using Drones as Reference Sensors for Neural-Networks-Based Modeling of Automotive Perception Errors**The research leading to these results is funded by the Federal Ministry for Economic Affairs and Energy within the project "VVM - Verification and Validation Methods for Automated Vehicles Level 4 and 5". The authors would like to thank the consortium for the successful cooperation. IV 2020: 708-715 - [c5]Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde, Lennart Vater, Lutz Eckstein:
The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections. IV 2020: 1929-1934 - [i3]Maike Scholtes, Lukas Westhofen, Lara Ruth Turner, Katrin Lotto, Michael Schuldes, Hendrik Weber, Nicolas Wagener, Christian Neurohr, Martin Bollmann, Franziska Körtke, Johannes Hiller, Michael Hoss, Julian Bock, Lutz Eckstein:
6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment. CoRR abs/2012.06319 (2020)
2010 – 2019
- 2019
- [c4]Julian Bock, Philipp Nolte, Lutz Eckstein:
Continuously Improving Model of Road User Movement Patterns using Recurrent Neural Networks at Intersections with Connected Sensors. VEHITS 2019: 319-326 - [i2]Julian Bock, Robert Krajewski, Tobias Moers, Steffen Runde, Lennart Vater, Lutz Eckstein:
The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections. CoRR abs/1911.07602 (2019) - 2018
- [c3]Robert Krajewski, Julian Bock, Laurent Kloeker, Lutz Eckstein:
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. ITSC 2018: 2118-2125 - [i1]Robert Krajewski, Julian Bock, Laurent Kloeker, Lutz Eckstein:
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems. CoRR abs/1810.05642 (2018) - 2017
- [c2]Julian Bock, Till Beemelmanns, Markus Klösges, Jens Kotte:
Self-learning Trajectory Prediction with Recurrent Neural Networks at Intelligent Intersections. VEHITS 2017: 346-351 - 2014
- [c1]Björn Fröhlich, Julian Bock, Uwe Franke:
Is it safe to change the lane? - Visual exploration of adjacent lanes for autonomous driving. ITSC 2014: 2304-2309
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