<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>3957</id>
    <completedYear/>
    <publishedYear>2013</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1764</pageFirst>
    <pageLast>1772</pageLast>
    <pageNumber/>
    <edition/>
    <issue>4</issue>
    <volume>14</volume>
    <type>article</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Statistical Behavior Modeling for Driver-Adaptive Precrash Systems</title>
    <abstract language="eng">Precrash systems have the potential for preventing or mitigating the results of an accident. However, optimal precrash activation can be only achieved by a driver-individual parameterization of the activation function. In this paper, an adaptation model is proposed, which calculates a driver-adapted activation threshold for the considered precrash algorithm. The model analyzes past situations to calculate a driver-individual activation threshold that achieves a desired activation frequency. The advantage of the proposed model is that the distribution is estimated using a distribution model. This has the result that an activation threshold can be already determined using a small data set. In addition, the confidence interval that has to be considered is decreased. The proposed model was applied in a study with test subjects. Results of this paper confirm the usability of the model. In comparison with an empirical approach, the proposed model achieves a significantly lower threshold and, thus, a higher safety effect of the system.</abstract>
    <parentTitle language="eng">IEEE Transactions on Intelligent Transportation Systems</parentTitle>
    <identifier type="doi">10.1109/TITS.2013.2267799</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Florian Mühlfeld</author>
    <author>Igor Doric</author>
    <author>Rudolf Ertlmeier</author>
    <author>Thomas Brandmeier</author>
  </doc>
  <doc>
    <id>3958</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>417</pageFirst>
    <pageLast>426</pageLast>
    <pageNumber/>
    <edition/>
    <issue>7</issue>
    <volume>60</volume>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Verbesserung modellbasierter Überschlagserkennung mittels Schätzung relevanter Fahrzeugparameter</title>
    <abstract language="deu">Passive   Rückhaltemittel   wie   Airbags können Fahrzeuginsassen während eines Überschlags vor Verletzungen  schützen.  Der  Beladungszustand  eines  Pkws  ist  jedoch  entscheidend  für  dessen  Kippverhalten,  wodurch  auch die  Detektion  eines  Überschlags  beeinflusst  wird.  Dieser  Beitrag  zeigt  eine  Schätzung  relevanter  Fahrzeugkennwerte  und die  damit  mögliche  Optimierung  eines  modellbasierten  Überschlagserkennungssystems</abstract>
    <abstract language="eng">Passive  safety systems like airbags are able to protect vehicle occupantsfrom injuries during a rollover. The loading condition of a car has  a  crucial  impact  on  its  roll  behavior  as  well  as  on  the rollover detection  algorithm. This  paper depicts  a method  forestimating relevant vehicle parameters and the possibility of optimizing a model-based rollover detection system.</abstract>
    <parentTitle language="deu">at - Automatisierungstechnik Methoden und Anwendungen der Steuerungs-, Regelungs- und Informationstechnik</parentTitle>
    <identifier type="doi">10.1524/auto.2012.1010</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Rudolf Ertlmeier</author>
    <author>Florian Mühlfeld</author>
    <author>Holger Faisst</author>
    <author>Ulrich Jumar</author>
    <author>Thomas Brandmeier</author>
  </doc>
  <doc>
    <id>3959</id>
    <completedYear/>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1211</pageFirst>
    <pageLast>1216</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Criticality Estimation of Pre-Crash Scenarios</title>
    <abstract language="eng">The activation of Pre-Crash systems like a reversible seat belt pretensioner can reduce the injury level of an occupant during a collision. The time-to-collision is a common criterion for discriminating between critical and non-critical situations. This paper investigates the driver's behavior as well as his/her criticality estimation of Pre-Crash scenarios and models the criticality estimation to a classification with features of the situation. Experimental data is analyzed regarding its possibility to model the subjective driver estimation by measured features. A situation model is developed that predicts a classification criterion, which can be used for Pre-Crash activation functions.</abstract>
    <parentTitle language="eng">14th International IEEE Conference on Intelligent Transportation Systems&#13;
(ITSC)</parentTitle>
    <identifier type="doi">10.1109/ITSC.2011.6082950</identifier>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Florian Mühlfeld</author>
    <author>Rudolf Ertlmeier</author>
    <author>Johannes Happe</author>
    <author>Thomas Brandmeier</author>
  </doc>
  <doc>
    <id>3960</id>
    <completedYear/>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation>Otto-von-Guericke-Universität Magdeburg</contributingCorporation>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Prädiktionsmodell der Fahrzeugtrajektorie für vorausschauende Sicherheitssysteme</title>
    <parentTitle language="deu">10. Magdeburger Maschinenbau-Tage</parentTitle>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Florian Mühlfeld</author>
    <author>Rudolf Ertlmeier</author>
    <author>Thomas Brandmeier</author>
  </doc>
  <doc>
    <id>3962</id>
    <completedYear/>
    <publishedYear>2008</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>34</pageFirst>
    <pageLast>35</pageLast>
    <pageNumber>2</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation>Hochschule Ingolstadt</contributingCorporation>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Integration von Aktiver und Passiver Sicherheit zur Erhöhung des Fahrzeuginsassenschutzes (APS)</title>
    <parentTitle language="deu">Forschungsbericht 2008</parentTitle>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <author>Florian Mühlfeld</author>
    <author>Rudolf Ertlmeier</author>
    <author>Thomas Brandmeier</author>
  </doc>
</export-example>
