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  </doc>
  <doc>
    <id>2942</id>
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    <publishedYear>2013</publishedYear>
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    <language>eng</language>
    <pageFirst>1335</pageFirst>
    <pageLast>1338</pageLast>
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    <title language="eng">Sufficient Real-Time Analysis for an Engine Control Unit with Constant Angular Velocities</title>
    <parentTitle language="eng">Design, Automation &amp; Test in Europe: Proceedings</parentTitle>
    <identifier type="isbn">978-1-4503-2153-2</identifier>
    <identifier type="url">https://dl.acm.org/doi/10.5555/2485288.2485607</identifier>
    <enrichment key="opus.import.data">@inproceedings10.5555/2485288.2485607, author = Pollex, Victor and Feld, Timo and Slomka, Frank and Margull, Ulrich and Mader, Ralph and Wirrer, Gerhard, title = Sufficient Real-Time Analysis for an Engine Control Unit with Constant Angular Velocities, year = 2013, isbn = 9781450321532, publisher = EDA Consortium, address = San Jose, CA, USA, abstract = Engine control units in the automotive industry are particular challenging real-time systems regarding their real-time analysis. Some of the tasks of such an engine control unit are triggered by the engine, i.e. the faster the angular velocity of the engine, the more frequent the tasks are executed. Furthermore, the execution time of a task may vary with the angular velocity of the engine. As a result the worst case does not necessarily occur when all tasks are activated simultaneously. Hence this behavior cannot be addressed appropriately with the currently available real-time analysis methods. In this paper we make a first step towards a real-time analysis for an engine control unit. We present a sufficient real-time analysis assuming that the angular velocity of the engine is arbitrary but fixed., booktitle = Proceedings of the Conference on Design, Automation and Test in Europe, pages = 1335–1338, numpages = 4, location = Grenoble, France, series = DATE ’13</enrichment>
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    <enrichment key="THI_conferenceName">DATE 13: Design, Automation and Test in Europe, Grenoble (France), 18.-22.03.2013</enrichment>
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    <author>
      <first_name>Victor</first_name>
      <last_name>Pollex</last_name>
    </author>
    <editor>
      <first_name>Kathy</first_name>
      <last_name>Preas</last_name>
    </editor>
    <author>
      <first_name>Timo</first_name>
      <last_name>Feld</last_name>
    </author>
    <author>
      <first_name>Frank</first_name>
      <last_name>Slomka</last_name>
    </author>
    <author>
      <first_name>Ulrich</first_name>
      <last_name>Margull</last_name>
    </author>
    <author>
      <first_name>Ralph</first_name>
      <last_name>Mader</last_name>
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    <author>
      <first_name>Gerhard</first_name>
      <last_name>Wirrer</last_name>
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      <first_name>Sinan</first_name>
      <last_name>Hasirlioglu</last_name>
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      <first_name>Andreas</first_name>
      <last_name>Riener</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rain</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>cameras</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>laser radar</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>data models</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>automotive engineering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>atmospheric modeling</value>
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    <pageFirst/>
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    <pageNumber>7</pageNumber>
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    <completedDate>2022-08-09</completedDate>
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    <title language="eng">Test Methodology for Vision-Based ADAS Algorithms with an Automotive Camera-in-the-Loop</title>
    <parentTitle language="eng">2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)</parentTitle>
    <identifier type="isbn">978-1-5386-3543-8</identifier>
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    <enrichment key="THI_conferenceName">2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES), Madrid (Spain), 12-14.09.2018</enrichment>
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    <author>
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      <last_name>Reway</last_name>
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    <author>
      <first_name>Werner</first_name>
      <last_name>Huber</last_name>
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    <author>
      <first_name>Eduardo</first_name>
      <last_name>Parente Ribeiro</last_name>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>cameras</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>sensors</value>
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    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>testing</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>automobiles</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>automotive engineering</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>radar</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>accidents</value>
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    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="24800">Huber, Werner</collection>
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    <completedDate>2022-08-24</completedDate>
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    <title language="eng">VIRTOOAIR: Virtual Reality TOOlbox for Avatar Intelligent Reconstruction</title>
    <parentTitle language="eng">2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)</parentTitle>
    <subTitle language="eng">System for VR motion reconstruction based on a VR tracking system and a single RGB camera</subTitle>
    <identifier type="isbn">978-1-5386-7592-2</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1109/ISMAR-Adjunct.2018.00085</enrichment>
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    <enrichment key="THI_conferenceName">2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct), Munich (Germany), 16.-20.10.2018</enrichment>
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      <last_name>Axenie</last_name>
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    <author>
      <first_name>Thomas</first_name>
      <last_name>Grauschopf</last_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>supervised learning by regression</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>virtual reality</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>motion capture</value>
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    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
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    <id>2756</id>
    <completedYear/>
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    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1318</pageFirst>
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    <completedDate>2022-08-24</completedDate>
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    <title language="eng">A Virtual Reality based Approach for Researching Pedestrian to Vehicle Collisions</title>
    <parentTitle language="eng">2018 IEEE Intelligent Vehicles Symposium (IV)</parentTitle>
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      <last_name>Holdgrün</last_name>
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    <author>
      <first_name>Igor</first_name>
      <last_name>Doric</last_name>
    </author>
    <author>
      <first_name>Thomas</first_name>
      <last_name>Brandmeier</last_name>
    </author>
    <author>
      <first_name>Therese</first_name>
      <last_name>Fuchs</last_name>
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    <author>
      <first_name>Julia</first_name>
      <last_name>Mühlbauer</last_name>
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    <author>
      <first_name>Philipp</first_name>
      <last_name>Steinert</last_name>
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    <author>
      <first_name>Steffen</first_name>
      <last_name>Peldschus</last_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>FEM simulation</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>pedestrian behavior</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>pedestrian simulator</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>pedestrian to vehicle interaction</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>vR testing</value>
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    <id>2754</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
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    <pageFirst/>
    <pageLast/>
    <pageNumber>6</pageNumber>
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    <completedDate>2022-08-23</completedDate>
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      <first_name>Raffaella</first_name>
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    <author>
      <first_name>Danilo</first_name>
      <last_name>Pedron</last_name>
    </author>
    <author>
      <first_name>Fosca</first_name>
      <last_name>Conti</last_name>
    </author>
    <author>
      <first_name>Alexander</first_name>
      <last_name>Hanss</last_name>
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    <author>
      <first_name>Sri Krishna</first_name>
      <last_name>Bhogaraju</last_name>
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    <author>
      <first_name>Gordon</first_name>
      <last_name>Elger</last_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Stress</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Light emitting diodes</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Gallium nitride</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Phonons</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Substrates</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Temperature measurement</value>
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    <subject>
      <language>eng</language>
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      <value>Silicon</value>
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    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
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    <id>2686</id>
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    <language>eng</language>
    <pageFirst>859</pageFirst>
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    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-08-18</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Automotive Radar Multipath Propagation in Uncertain Environments</title>
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    <identifier type="isbn">978-1-7281-0323-5</identifier>
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    <author>
      <first_name>Alexander</first_name>
      <last_name>Kamann</last_name>
    </author>
    <author>
      <first_name>Patrick</first_name>
      <last_name>Held</last_name>
    </author>
    <author>
      <first_name>Florian</first_name>
      <last_name>Perras</last_name>
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    <author>
      <first_name>Patrick</first_name>
      <last_name>Zaumseil</last_name>
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    <author>
      <first_name>Thomas</first_name>
      <last_name>Brandmeier</last_name>
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    <author>
      <first_name>Ulrich</first_name>
      <last_name>Schwarz</last_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>sensors</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>radar</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>receiving antennas</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>surface waves</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>transmitting antennas</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rough surfaces</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>surface roughness</value>
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    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
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    <id>2685</id>
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    <pageFirst>787</pageFirst>
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    <completedDate>2022-08-18</completedDate>
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    <title language="eng">Radar-Based Analysis of Pedestrian Micro-Doppler Signatures Using Motion Capture Sensors</title>
    <parentTitle language="eng">2018 IEEE Intelligent Vehicles Symposium (IV)</parentTitle>
    <identifier type="isbn">978-1-5386-4452-2</identifier>
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    <author>
      <first_name>Patrick</first_name>
      <last_name>Held</last_name>
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    <author>
      <first_name>Dagmar</first_name>
      <last_name>Steinhauser</last_name>
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      <first_name>Clemens</first_name>
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    <subject>
      <language>eng</language>
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  <doc>
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    <title language="eng">Intra-Task Parallelism in Automotive Real-Time Systems</title>
    <parentTitle language="eng">PMAM 2018: Proceedings of the Ninth International Workshop on Programming Models and Applications for Multicores and Manycores</parentTitle>
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      <last_name>Chen</last_name>
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    <author>
      <first_name>Tobias</first_name>
      <last_name>Wägemann</last_name>
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      <first_name>Zhiyi</first_name>
      <last_name>Huang</last_name>
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    <author>
      <first_name>Niklas</first_name>
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      <first_name>Ralph</first_name>
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      <first_name>Laura</first_name>
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      <last_name>Wintersberger</last_name>
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    <author>
      <first_name>Andreas</first_name>
      <last_name>Riener</last_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
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      <language>eng</language>
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  <doc>
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    <title language="eng">Evaluation of Driving Performance and User Experience of Different Types of Speedometer</title>
    <parentTitle language="eng">Adjunct Proceedings: 10th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications</parentTitle>
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    <author>
      <first_name>Paul</first_name>
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      <first_name>Andreas</first_name>
      <last_name>Riener</last_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Speedometer variants</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Freely programmable instrument</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Driving performance</value>
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    <subject>
      <language>eng</language>
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    <title language="eng">Driving Hotzenplotz: A Hybrid Interface for Vehicle Control Aiming to Maximize Pleasure in Highway Driving</title>
    <parentTitle language="eng">Proceedings: 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications</parentTitle>
    <identifier type="isbn">978-1-4503-5150-8</identifier>
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    <author>
      <first_name>Anna-Katharina</first_name>
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      <first_name>Philipp</first_name>
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      <first_name>Andreas</first_name>
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      <first_name>Clemens</first_name>
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      <language>eng</language>
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      <value>automated driving</value>
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      <value>user acceptance</value>
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      <language>eng</language>
      <type>uncontrolled</type>
      <value>joy of driving</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>user studies</value>
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      <language>eng</language>
      <type>uncontrolled</type>
      <value>need scale</value>
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      <type>uncontrolled</type>
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  <doc>
    <id>2481</id>
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    <title language="eng">Let Me Finish before I Take Over: Towards Attention Aware Device Integration in Highly Automated Vehicles</title>
    <parentTitle language="eng">Proceedings: 10th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications</parentTitle>
    <identifier type="isbn">978-1-4503-5946-7</identifier>
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      <language>eng</language>
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      <value>automated driving</value>
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      <value>take-over request</value>
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      <value>attentive user interfaces</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>non-driving related tasks</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>device integration</value>
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    <subject>
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      <type>uncontrolled</type>
      <value>pervasive computing</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SAE J3016</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SAE J3114</value>
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    <title language="eng">Man vs. Machine: Comparing a Fully Automated Bus Shuttle with a Manually Driven Group Taxi in a Field Study</title>
    <parentTitle language="eng">Adjunct Proceedings: 10th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications</parentTitle>
    <identifier type="isbn">978-1-4503-5947-4</identifier>
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      <first_name>Philipp</first_name>
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      <first_name>Andreas</first_name>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>automated driving</value>
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    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>SAE J3016</value>
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      <language>eng</language>
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      <value>field studies</value>
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    <id>2477</id>
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    <title language="eng">Traffic Augmentation as a Means to Increase Trust in Automated Driving Systems</title>
    <parentTitle language="eng">CHItaly '17: Proceedings of the 12th Biannual Conference on Italian SIGCHI Chapter</parentTitle>
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    <author>
      <first_name>Philipp</first_name>
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      <language>eng</language>
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      <value>trust in automation</value>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Automated Driving: Acceptance and Chances for Elderly People</title>
    <parentTitle language="eng">Adjunct Proceedings: 9th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications</parentTitle>
    <identifier type="isbn">978-1-4503-5151-5</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1145/3131726.3131738</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">nein</enrichment>
    <enrichment key="THI_conferenceName">AutomotiveUI '17: ACM 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Oldenburg (Germay), 24.-27.09.2017</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <author>
      <first_name>Katharina</first_name>
      <last_name>Diepold</last_name>
    </author>
    <author>
      <first_name>Kerstin</first_name>
      <last_name>Götzl</last_name>
    </author>
    <author>
      <first_name>Andreas</first_name>
      <last_name>Riener</last_name>
    </author>
    <author>
      <first_name>Anna-Katharina</first_name>
      <last_name>Frison</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>automated driving</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>elderly people</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>user needs</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>user study</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>semi-structured interviews</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>role play</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="26627">Riener, Andreas</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
    <collection role="institutes" number="19588">Human-Computer Interaction Group (HCIG)</collection>
  </doc>
  <doc>
    <id>2469</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>2036</pageFirst>
    <pageLast>2043</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <articleNumber/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Real-Time Crash Severity Estimation with Machine Learning and 2D Mass-Spring-Damper Model</title>
    <parentTitle language="eng">2018 IEEE Intelligent Transportation Systems Conference</parentTitle>
    <identifier type="isbn">978-1-7281-0323-5</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1109/ITSC.2018.8569471</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">nein</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_conferenceName">2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui (USA), 04.-07.11.2018</enrichment>
    <author>
      <first_name>Marcus</first_name>
      <last_name>Müller</last_name>
    </author>
    <author>
      <first_name>Xing</first_name>
      <last_name>Long</last_name>
    </author>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <author>
      <first_name>Dennis</first_name>
      <last_name>Böhmländer</last_name>
    </author>
    <author>
      <first_name>Wolfgang</first_name>
      <last_name>Utschick</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>computer crashes</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>vehicle crash testing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>two dimensional displays</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>forestry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>accidents</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>acceleration</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
  </doc>
  <doc>
    <id>2467</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>423</pageFirst>
    <pageLast>434</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <articleNumber/>
    <type>conferenceobject</type>
    <publisherName>Springer</publisherName>
    <publisherPlace>Cham</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Generation of Reference Trajectories for Safe Trajectory Planning</title>
    <parentTitle language="eng">Artificial Neural Networks and Machine Learning – ICANN 2018 : 27th International Conference on Artificial Neural Networks,Rhodes, Greece, October 4–7, 2018 : Proceedings, Part I</parentTitle>
    <identifier type="isbn">978-3-030-01418-6</identifier>
    <identifier type="isbn">978-3-030-01417-9</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1007/978-3-030-01418-6_42</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">nein</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_conferenceName">27th International Conference on Artificial Neural Networks, Rhodes (Greece), 04.-07.10.2018</enrichment>
    <author>
      <first_name>Amit</first_name>
      <last_name>Chaulwar</last_name>
    </author>
    <editor>
      <first_name>Vera</first_name>
      <last_name>Kurková</last_name>
    </editor>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <editor>
      <first_name>Yannis</first_name>
      <last_name>Manolopoulos</last_name>
    </editor>
    <author>
      <first_name>Wolfgang</first_name>
      <last_name>Utschick</last_name>
    </author>
    <editor>
      <first_name>Barbara</first_name>
      <last_name>Hammer</last_name>
    </editor>
    <editor>
      <first_name>Lazaros</first_name>
      <last_name>Iliadis</last_name>
    </editor>
    <editor>
      <first_name>Ilias</first_name>
      <last_name>Maglogiannis</last_name>
    </editor>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Safe trajectory planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Hybrid machine learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Variational autoencoder</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
  </doc>
  <doc>
    <id>2466</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <articleNumber/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Wireless Communication System for the Validation of Autonomous Driving Functions on Full-Scale Vehicles</title>
    <parentTitle language="eng">2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES)</parentTitle>
    <identifier type="isbn">978-1-5386-3543-8</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1109/ICVES.2018.8519492</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">nein</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_conferenceName">2018 IEEE International Conference on Vehicular Electronics and Safety (ICVES), Madrid (Spain), 12.-14.09.2018</enrichment>
    <author>
      <first_name>Valentin</first_name>
      <last_name>Cañas</last_name>
    </author>
    <author>
      <first_name>Eduardo</first_name>
      <last_name>Sánchez Morales</last_name>
    </author>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <author>
      <first_name>Andres</first_name>
      <last_name>García Higuera</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Vehicle safety</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>wireless communication</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>autonomous driving</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Intelligent Transport Systems</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
  </doc>
  <doc>
    <id>2465</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>9</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>9</volume>
    <articleNumber/>
    <type>article</type>
    <publisherName>Engineering and Technology Publishing</publisherName>
    <publisherPlace>Rowland Heights</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Machine Learning Architectures for the Estimation of Predicted Occupancy Grids in Road Traffic</title>
    <abstract language="eng">This paper introduces a novel machine learning architecture for an efficient estimation of the probabilistic space-time representation of complex traffic scenarios. A detailed representation of the future traffic scenario is of significant importance for autonomous driving and for all active safety systems. In order to predict the future spacetime representation of the traffic scenario, first the type of traffic scenario is identified and then the machine learning algorithm maps the current state of the scenario to possible future states. The input to the machine learning algorithms is the current state representation of a traffic scenario, termed as the Augmented Occupancy Grid (AOG). The output is the probabilistic space-time representation which includes uncertainties regarding the behaviour of the traffic participants and is termed as the Predicted Occupancy Grid (POG). The novel architecture consists of two Stacked Denoising Autoencoders (SDAs) and a set of Random Forests. It is then compared with the other two existing architectures that comprise of SDAs and DeconvNet. The architectures are validated with the help of simulations and the comparisons are made both in terms of accuracy and computational time. Also, a brief overview on the applications of POGs in the field of active safety is presented.</abstract>
    <parentTitle language="eng">Journal of Advances in Information Technology</parentTitle>
    <identifier type="issn">1798-2340</identifier>
    <identifier type="urn">urn:nbn:de:bvb:573-24653</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.12720/jait.9.1.1-9</enrichment>
    <enrichment key="THI_articleversion">published</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_furtherversion">https://opus4.kobv.de/opus4-haw/frontdoor/index/index/docId/6699</enrichment>
    <licence>Creative Commons BY-NC-ND 4.0</licence>
    <author>
      <first_name>Parthasarathy</first_name>
      <last_name>Nadarajan</last_name>
    </author>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <author>
      <first_name>Sebastian</first_name>
      <last_name>Sardina</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Predicted Occupancy Grid</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Active vehicle safety</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Autoencoders</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Random Forest</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>DeconvNet</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
    <thesisPublisher>Technische Hochschule Ingolstadt</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-haw/files/2465/20180207115934827.pdf</file>
  </doc>
  <doc>
    <id>2464</id>
    <completedYear/>
    <publishedYear>2018</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>15</pageFirst>
    <pageLast>24</pageLast>
    <pageNumber/>
    <edition/>
    <issue>1</issue>
    <volume>9 (2018)</volume>
    <articleNumber/>
    <type>article</type>
    <publisherName>Engineering and Technology Publishing</publisherName>
    <publisherPlace>Rowland Heights (CA)</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-25</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Machine Learning Based Prediction of Crash Severity Distributions for Mitigation Strategies</title>
    <abstract language="eng">In road traffic, critical situations pass by as quickly as they appear. Within the blink of an eye, one has to come to a decision, which can make the difference between a low severity, high severity or fatal crash. Because time is important, a machine learning driven Crash Severity Predictor (CSP) is presented which provides the estimated crash severity distribution of an imminent crash in less than 0.2ms. This is 63⋅ 103 times faster compared to predicting the same distribution through computationally expensive numerical simulations. With the proposed method, even very complex crash data, like the results of Finite Element Method (FEM) simulations, can be made available ahead of a collision. Knowledge, which can be used to prepare occupants and vehicle to an imminent crash, activate and adjust safety measures like airbags or belt tensioners before of a collision or let self-driving vehicles go for the maneuver with the lowest crash severity. Using a real-world crash test it is shown that significant safety potential is left unused if instead of the CSP-proposed driving maneuver, no or the wrong actions are taken.</abstract>
    <parentTitle language="eng">Journal of Advances in Information Technology</parentTitle>
    <identifier type="issn">1798-2340</identifier>
    <identifier type="urn">urn:nbn:de:bvb:573-24644</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.12720/jait.9.1.15-24</enrichment>
    <enrichment key="THI_articleversion">published</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">ja</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons BY-NC-ND 4.0</licence>
    <author>
      <first_name>Marcus</first_name>
      <last_name>Müller</last_name>
    </author>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <author>
      <first_name>Dennis</first_name>
      <last_name>Böhmländer</last_name>
    </author>
    <author>
      <first_name>Wolfgang</first_name>
      <last_name>Utschick</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>crash severity</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>vehicle safety</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>reliable prediction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>machine learning</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
    <thesisPublisher>Technische Hochschule Ingolstadt</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-haw/files/2464/20180207120739305.pdf</file>
  </doc>
  <doc>
    <id>2461</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>297</pageFirst>
    <pageLast>303</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <articleNumber/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios</title>
    <parentTitle language="eng">2017 IEEE Intelligent Vehicles Symposium (IV)</parentTitle>
    <identifier type="isbn">978-1-5090-4804-5</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1109/IVS.2017.7995735</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">nein</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_conferenceName">2017 IEEE Intelligent Vehicles Symposium (IV), Redondo Beach (USA), 11.-14.06.2017</enrichment>
    <author>
      <first_name>Amit</first_name>
      <last_name>Chaulwar</last_name>
    </author>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <author>
      <first_name>Wolfgang</first_name>
      <last_name>Utschick</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Acceleration</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Trajectory</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Heuristic algorithms</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Vehicle dynamics</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Prediction algorithms</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Roads</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
  </doc>
  <doc>
    <id>2460</id>
    <completedYear/>
    <publishedYear>2017</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1244</pageFirst>
    <pageLast>1251</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <articleNumber/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace>Piscataway</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-06-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Predicted-occupancy grids for vehicle safety applications based on autoencoders and the Random Forest algorithm</title>
    <parentTitle language="eng">2017 International Joint Conference on Neural Networks (IJCNN)</parentTitle>
    <identifier type="isbn">978-1-5090-6182-2</identifier>
    <identifier type="issn">2161-4407</identifier>
    <enrichment key="THI_relatedIdentifier">https://doi.org/10.1109/IJCNN.2017.7965995</enrichment>
    <enrichment key="THI_review">peer-review</enrichment>
    <enrichment key="THI_openaccess">nein</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="THI_conferenceName">2017 International Joint Conference on Neural Networks (IJCNN), Anchorage (USA), 14.-19.05.2017</enrichment>
    <enrichment key="THI_furtherversion">https://opus4.kobv.de/opus4-haw/frontdoor/index/index/docId/6698</enrichment>
    <author>
      <first_name>Parthasarathy</first_name>
      <last_name>Nadarajan</last_name>
    </author>
    <author>
      <first_name>Michael</first_name>
      <last_name>Botsch</last_name>
    </author>
    <author>
      <first_name>Sebastian</first_name>
      <last_name>Sardina</last_name>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Roads</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Feature extraction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Radio frequency</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Geometry</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computational modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Prediction algorithms</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine learning algorithms</value>
    </subject>
    <collection role="institutes" number="15984">Fakultät Elektrotechnik und Informatik</collection>
    <collection role="persons" number="26835">Botsch, Michael</collection>
    <collection role="institutes" number="19574">CARISSMA</collection>
  </doc>
</export-example>
