Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Lukas Elster"'
Autor:
Arsalan Haider, Lukas Haas, Shotaro Koyama, Lukas Elster, Michael H. Kohler, Michael Schardt, Thomas Zeh, Hideo Inoue, Martin Jakobi, Alexander W. Koch
Publikováno v:
IEEE Access, Vol 12, Pp 13020-13036 (2024)
Automated vehicles use light detection and ranging (LiDAR) sensors for environmental scanning. However, the relative motion between the scanning LiDAR sensor and objects leads to a distortion of the point cloud. This phenomenon is known as the motion
Externí odkaz:
https://doaj.org/article/86b3a8bcd1984d218aa3129afbf09ab9
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11405 (2023)
Virtual validation of radar sensor models is becoming increasingly important for the safety validation of Light Detection and Rangings (lidars). Therefore, methods for quantitative comparison of radar measurements in the context of model validation n
Externí odkaz:
https://doaj.org/article/1a901e06d7ef499f8f90cead25903112
Publikováno v:
IEEE Access, Vol 10, Pp 118236-118242 (2022)
Many recent approaches for automated driving (AD) functions currently include components relying on deep neural networks (DNNs). One approach in order to test AD functions is the scenario-based approach. This work formalizes and evaluates the paramet
Externí odkaz:
https://doaj.org/article/20a8c1a7ce3e4acaa8612242bc708f56
Publikováno v:
Sensors, Vol 22, Iss 14, p 5266 (2022)
Safety validation of automated driving functions is a major challenge that is partly tackled by means of simulation-based testing. The virtual validation approach always entails the modeling of automotive perception sensors and their environment. In
Externí odkaz:
https://doaj.org/article/ca7da51bc0304900a3789bdad6657e3f
Publikováno v:
Energies, Vol 15, Iss 3, p 989 (2022)
In the course of the development of automated driving, there has been increasing interest in obtaining ground truth information from sensor recordings and transferring road traffic scenarios to simulations. The quality of the “ground truth” annot
Externí odkaz:
https://doaj.org/article/3cbf3f9a1db54540b36ec584969a68e3
Publikováno v:
IEEE Sensors Journal. 23:4873-4882
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5100d21102ddafc42c250f93c057eefb
https://doi.org/10.1109/jsen.2023.3238015
https://doi.org/10.1109/jsen.2023.3238015
Publikováno v:
Sensors; Volume 22; Issue 14; Pages: 5266
Safety validation of automated driving functions is a major challenge that is partly tackled by means of simulation-based testing. The virtual validation approach always entails the modeling of automotive perception sensors and their environment. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::cc2858380db79c1ec87344ec5471bbca
Publikováno v:
Energies; Volume 15; Issue 3; Pages: 989
In the course of the development of automated driving, there has been increasing interest in obtaining ground truth information from sensor recordings and transferring road traffic scenarios to simulations. The quality of the “ground truth” annot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::fb2d297b31c506a02312791c9e4d63b7
Autor:
Hermann Winner, Lukas Elster, Philipp Rosenberger, Clemens Linnhoff, Simon Schmidt, Rainer Stark
Publikováno v:
ITSC
Perception sensor modeling is essential for the safety validation of automated driving systems in virtual environments. Nevertheless, the community lacks a methodical approach to derive requirements for such sensor models that enables a serious appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94136bb3624c26d9e843b7230378d2f9
