<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>2163</id>
    <completedYear>2018</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-12-01</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Situation Awareness and Early Recognition of Traffic Maneuvers</title>
    <abstract language="eng">We outline the challenges of situation awareness with early and accurate recognition of traffic maneuvers and how to assess them. This includes also an overview of the available data and derived situation features,handling of data uncertainties, modelling and the approach for maneuver recognition. An efficient and effective solution, meeting the automotive requirements, is successfully deployed and tested on a prototype car. Test driving results show that earlier recognition of intended maneuver is feasible on average 1 second (and up to 6.72 s) before the actual lane-marking crossing. The even earlier maneuver recognition is dependent on the earlier recognition of surrounding vehicles.</abstract>
    <parentTitle language="eng">Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016</parentTitle>
    <identifier type="url">https://www.researchgate.net/publication/329785176_Situation_Awareness_and_Early_Recognition_of_Traffic_Maneuvers#fullTextFileContent</identifier>
    <identifier type="doi">10.3384/ecp171428</identifier>
    <enrichment key="copyright">1</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Galia Weidl</author>
    <author>Anders L. Madsen</author>
    <author>Viacheslav Tereshchenko</author>
    <author>Wei Zhang</author>
    <author>Wang Stevens Ruixi</author>
    <author>Dietmar Kasper</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>ITS (Intelligent Transportation Systems)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Artificial Intelligence</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Fahrerassistenzsystem</value>
    </subject>
    <collection role="institutes" number="">Kompetenzzentrum Künstliche Intelligenz</collection>
    <collection role="forschungsschwerpunkte" number="">Artifical Intelligence and Data Science</collection>
  </doc>
</export-example>
