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pro vyhledávání: '"Morales, Eduardo Sánchez"'
The trend towards autonomous driving and the continuous research in the automotive area, like Advanced Driver Assistance Systems (ADAS), requires an accurate localization under all circumstances. An accurate estimation of the vehicle state is a basic
Externí odkaz:
http://arxiv.org/abs/2005.06798
Autonomous driving is an important trend of the automotive industry. The continuous research towards this goal requires a precise reference vehicle state estimation under all circumstances in order to develop and test autonomous vehicle functions. Ho
Externí odkaz:
http://arxiv.org/abs/2005.06791
Autor:
Morales, Eduardo Sánchez, Membarth, Richard, Gaull, Andreas, Slusallek, Philipp, Dirndorfer, Tobias, Kammenhuber, Alexander, Lauer, Christoph, Botsch, Michael
Due to the current developments towards autonomous driving and vehicle active safety, there is an increasing necessity for algorithms that are able to perform complex criticality predictions in real-time. Being able to process multi-object traffic sc
Externí odkaz:
http://arxiv.org/abs/2005.06773
Autor:
Morales, Eduardo Sánchez, Kruber, Friedrich, Botsch, Michael, Huber, Bertold, Higuera, Andrés García
Due to their capability of acquiring aerial imagery, camera-equipped Unmanned Aerial Vehicles (UAVs) are very cost-effective tools for acquiring traffic information. However, not enough attention has been given to the validation of the accuracy of th
Externí odkaz:
http://arxiv.org/abs/2005.06314
Publikováno v:
2020 IEEE Intelligent Vehicles Symposium (IV)
The availability of real-world data is a key element for novel developments in the fields of automotive and traffic research. Aerial imagery has the major advantage of recording multiple objects simultaneously and overcomes limitations such as occlus
Externí odkaz:
http://arxiv.org/abs/2004.08206
Autor:
Kruber, Friedrich, Wurst, Jonas, Morales, Eduardo Sánchez, Chakraborty, Samarjit, Botsch, Michael
Publikováno v:
2019 IEEE Intelligent Vehicles Symposium (IV)
The goal of this paper is to provide a method, which is able to find categories of traffic scenarios automatically. The architecture consists of three main components: A microscopic traffic simulation, a clustering technique and a classification tech
Externí odkaz:
http://arxiv.org/abs/2004.02126
Akademický článek
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Autor:
Morales ES; Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany., Dauth J; Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany., Huber B; GeneSys Elektronik GmbH, In der Spöck 10, 77656 Offenburg, Germany., García Higuera A; European Parliamentary Research Service, Rue Wiertz 60, B-1047 Brussels, Belgium., Botsch M; Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany.
Publikováno v:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2021 Feb 06; Vol. 21 (4). Date of Electronic Publication: 2021 Feb 06.