3 Search Results for "Wurst, Michael"

Document
DOI: 10.4230/LITES.8.1.2
Micro- and Macroscopic Road Traffic Analysis using Drone Image Data

Authors: Friedrich Kruber, Eduardo Sánchez Morales, Robin Egolf, Jonas Wurst, Samarjit Chakraborty, and Michael Botsch

Published in: LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1

Abstract
The current development in the drone technology, alongside with machine learning based image processing, open new possibilities for various applications. Thus, the market volume is expected to grow rapidly over the next years. The goal of this paper is to demonstrate the capabilities and limitations of drone based image data processing for the purpose of road traffic analysis. In the first part a method for generating microscopic traffic data is proposed. More precisely, the state of vehicles and the resulting trajectories are estimated. The method is validated by conducting experiments with reference sensors and proofs to achieve precise vehicle state estimation results. It is also shown, how the computational effort can be reduced by incorporating the tracking information into a neural network. A discussion on current limitations supplements the findings. By collecting a large number of vehicle trajectories, macroscopic statistics, such as traffic flow and density can be obtained from the data. In the second part, a publicly available drone based data set is analyzed to evaluate the suitability for macroscopic traffic modeling. The results show that the method is well suited for gaining detailed information about macroscopic statistics, such as traffic flow dependent time headway or lane change occurrences. In conclusion, this paper presents methods to exploit the remarkable opportunities of drone based image processing for joint macro- and microscopic traffic analysis.
Cite as

Friedrich Kruber, Eduardo Sánchez Morales, Robin Egolf, Jonas Wurst, Samarjit Chakraborty, and Michael Botsch. Micro- and Macroscopic Road Traffic Analysis using Drone Image Data. In LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1, pp. 02:1-02:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Article{kruber_et_al:LITES.8.1.2,
  author =	{Kruber, Friedrich and S\'{a}nchez Morales, Eduardo and Egolf, Robin and Wurst, Jonas and Chakraborty, Samarjit and Botsch, Michael},
  title =	{{Micro- and Macroscopic Road Traffic Analysis using Drone Image Data}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{02:1--02:27},
  ISSN =	{2199-2002},
  year =	{2022},
  volume =	{8},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LITES.8.1.2},
  doi =		{10.4230/LITES.8.1.2},
  annote =	{Keywords: traffic data analysis, trajectory data, drone image data}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2017.10
Communication Centric Design in Complex Automotive Embedded Systems

Authors: Arne Hamann, Dakshina Dasari, Simon Kramer, Michael Pressler, and Falk Wurst

Published in: LIPIcs, Volume 76, 29th Euromicro Conference on Real-Time Systems (ECRTS 2017)

Abstract
Automotive embedded applications like the engine management system are composed of multiple functional components that are tightly coupled via numerous communication dependencies and intensive data sharing, while also having real-time requirements. In order to cope with complexity, especially in multi-core settings, various communication mechanisms are used to ensure data consistency and temporal determinism along functional cause-effect chains. However, existing timing analysis methods generally only support very basic communication models that need to be extended to handle the analysis of industry grade problems which involve more complex communication semantics. In this work, we give an overview of communication semantics used in the automotive industry and the different constraints to be considered in the design process. We also propose a method for model transformation to increase the expressiveness of current timing analysis methods enabling them to work with more complex communication semantics. We demonstrate this transformation approach for concrete implementations of two communication semantics, namely, implicit and LET communication. We discuss the impact on end-to-end latencies and communication overheads based on a full blown engine management system.
Cite as

Arne Hamann, Dakshina Dasari, Simon Kramer, Michael Pressler, and Falk Wurst. Communication Centric Design in Complex Automotive Embedded Systems. In 29th Euromicro Conference on Real-Time Systems (ECRTS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 76, pp. 10:1-10:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{hamann_et_al:LIPIcs.ECRTS.2017.10,
  author =	{Hamann, Arne and Dasari, Dakshina and Kramer, Simon and Pressler, Michael and Wurst, Falk},
  title =	{{Communication Centric Design in Complex Automotive Embedded Systems}},
  booktitle =	{29th Euromicro Conference on Real-Time Systems (ECRTS 2017)},
  pages =	{10:1--10:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-037-8},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{76},
  editor =	{Bertogna, Marko},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2017.10},
  URN =		{urn:nbn:de:0030-drops-71624},
  doi =		{10.4230/LIPIcs.ECRTS.2017.10},
  annote =	{Keywords: Communication semantics, logical execution time, implicit communication, automotive, embedded systems, scheduling simulation, Amalthea}
}
Document
DOI: 10.4230/DagSemProc.07181.5
Multi-Aspect Tagging for Collaborative Structuring

Authors: Katharina Morik and Michael Wurst

Published in: Dagstuhl Seminar Proceedings, Volume 7181, Parallel Universes and Local Patterns (2007)

Abstract
Local tag structures have become frequent though Web 2.0: Users "tag" their data without specifying the underlying semantics. A collection of media items is tagged multiply using different aspects, e.g., topic, genre, occasion, mood. Given the large number of local, individual structures, users could benefit from the tagging work of others ("folksonomies"). In contrast to distributed clustering, no global structure is wanted. Each user wants to keep the tags already annotated, wants to keep the diverse aspects under which the items were organized, and only wishes to enhance the own structure by those of others. A clustering algorithm which structures items has to take into account the local, multi-aspect nature of the task structures. The LACE algorithm (Wurst et al. 2006) is such a clustering algorithm.
Cite as

Katharina Morik and Michael Wurst. Multi-Aspect Tagging for Collaborative Structuring. In Parallel Universes and Local Patterns. Dagstuhl Seminar Proceedings, Volume 7181, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{morik_et_al:DagSemProc.07181.5,
  author =	{Morik, Katharina and Wurst, Michael},
  title =	{{Multi-Aspect Tagging for Collaborative Structuring}},
  booktitle =	{Parallel Universes and Local Patterns},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7181},
  editor =	{Michael R. Berthold and Katharina Morik and Arno Siebes},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07181.5},
  URN =		{urn:nbn:de:0030-drops-12635},
  doi =		{10.4230/DagSemProc.07181.5},
  annote =	{Keywords: Ensemble Clustering, automatic tagging, localized clustering}
}
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