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Jacob Langner
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Estimating the uniqueness of test scenarios derived from recorded real-world-driving-data using autoencoders
J Langner, J Bach, L Ries, S Otten, M Holzäpfel, E Sax
2018 IEEE Intelligent Vehicles Symposium (IV), 1860-1866, 2018
682018
Data-driven development, a complementing approach for automotive systems engineering
J Bach, J Langner, S Otten, M Holzäpfel, E Sax
2017 IEEE International Systems Engineering Symposium (ISSE), 1-6, 2017
382017
Test scenario selection for system-level verification and validation of geolocation-dependent automotive control systems
J Bach, J Langner, S Otten, E Sax, M Holzäpfel
2017 International Conference on Engineering, Technology and Innovation (ICE …, 2017
362017
Logical Scenario Derivation by Clustering Dynamic-Length-Segments Extracted from Real-World-Driving-Data.
J Langner, H Grolig, S Otten, M Holzäpfel, E Sax
VEHITS, 458-467, 2019
282019
A taxonomy and survey on validation approaches for automated driving systems
C King, L Ries, J Langner, E Sax
2020 IEEE International Symposium on Systems Engineering (ISSE), 1-8, 2020
232020
Leveraging regular expressions for flexible scenario detection in recorded driving data
P Elspas, J Langner, M Aydinbas, J Bach, E Sax
2020 IEEE International Symposium on Systems Engineering (ISSE), 1-8, 2020
162020
A driving scenario representation for scalable real-data analytics with neural networks
L Ries, J Langner, S Otten, J Bach, E Sax
2019 IEEE Intelligent Vehicles Symposium (IV), 2215-2222, 2019
162019
Towards a data engineering process in data-driven systems engineering
P Petersen, H Stage, J Langner, L Ries, P Rigoll, CP Hohl, E Sax
2022 IEEE International Symposium on Systems Engineering (ISSE), 1-8, 2022
132022
Capturing the Variety of Urban Logical Scenarios from Bird-view Trajectories.
C King, T Braun, C Braess, J Langner, E Sax
VEHITS, 471-480, 2021
112021
Framework for using real driving data in automotive feature development and validation
J Langner, J Bach, S Otten, E Sax, M Holzäpfel
8. Tagung Fahrerassistenz, 2017
72017
A Process Reference Model for the Virtual Application of Predictive Control Features
J Langner, KL Bauer, M Holzäpfel, E Sax
2020 IEEE Intelligent Vehicles Symposium (IV), 1759-1764, 2020
52020
Validation of range estimation for electric vehicles based on recorded real-world driving data
P Petersen, J Langner, S Otten, E Sax, S Scheubner, M Vaillant, ...
19. Internationales Stuttgarter Symposium: Automobil-und Motorentechnik, 331-344, 2019
52019
Analysis and comparison of datasets by leveraging data distributions in latent spaces
H Stage, L Ries, J Langner, S Otten, E Sax
Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022
32022
An Efficient Strategy for Testing ADAS on HiL Test Systems with Parallel Condition-based Assessments.
C Steinhauser, M Boncler, J Langner, S Strebel, E Sax
VEHITS, 391-399, 2022
32022
GOOSE: Goal-Conditioned Reinforcement Learning for Safety-Critical Scenario Generation
J Ransiek, J Plaum, J Langner, E Sax
arXiv preprint arXiv:2406.03870, 2024
22024
Unveiling objects with sola: An annotation-free image search on the object level for automotive data sets
P Rigoll, J Langner, L Ries, E Sax
2024 IEEE Intelligent Vehicles Symposium (IV), 1053-1059, 2024
22024
Data-Driven Development
J Bach, J Langner, S Otten, M Holzäpfel, E Sax
A Complementing Approach for Automotive Systems Engineering, 2017
22017
Reducing Computer Vision Dataset Size via Selective Sampling
H Stage, L Ewecker, J Langner, TS Sohn, T Villmann, E Sax
2023 IEEE 26th International Conference on Intelligent Transportation …, 2023
12023
Qualitative Feature Assessment for Longitudinal and Lateral Control-features.
J Langner, C Seiffer, S Otten, KL Bauer, M Holzäpfel, E Sax
VEHITS, 115-122, 2020
12020
Detecting Oncoming Vehicles at Night in Urban Scenarios-An Annotation Proof-Of-Concept
L Ewecker, N Wagner, T Brühl, R Schwager, TS Sohn, A Engelsberger, ...
2024 IEEE Intelligent Vehicles Symposium (IV), 2117-2124, 2024
2024
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