<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>401</id>
    <completedYear/>
    <publishedYear>2019</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IARIA - International Conference on Advances in Vehicular Systems, Technologies and Applications</publisherName>
    <publisherPlace>Wilmington, DE, USA</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2019-07-04</completedDate>
    <publishedDate>2019-07-04</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Trust in Automation: An On-Road Study of Trust in Advanced Driver Assistance Systems</title>
    <abstract language="eng">Appropriate user trust is critical in ensuring the acceptance and safe use of Advanced Driver Assistance Systems (ADAS). Despite the prevalence of ADAS on-road today, there is a limited understanding of how trust is affected by a user’s first contact with the system on-road. Ten participants without prior experience were introduced to a level 2 system and completed an on-road test drive session. Utilizing a mixed- methods approach including the Trust in Automation (TiA) questionnaire, verbal trust scores, and Facial Emotion Recognition (FER), trust in the system was measured at key milestones. TiA scores increased in a majority of participants, and a significant shift in the factor Reliability/Competence (p&lt;0.05) was observed post-drive. According to FER scores, participants with a gain in TiA post-drive and those with a loss in TiA post-drive, more frequently displayed the emotions happy and angry, respectively. Results indicate that trust increases after a user’s first experience with ADAS and further that FER may be predictive of user trust in automation.</abstract>
    <identifier type="urn">urn:nbn:de:hbz:1383-opus4-4017</identifier>
    <licence>CC BY 4.0 International - Namensnennung</licence>
    <author>Liza Dixon</author>
    <author>William M. Megill</author>
    <author>Karsten Nebe</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Advanced Driver Assistance Systems (ADAS)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Trust</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Human-Machine interaction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Human-Automation interaction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Autonomous vehicles</value>
    </subject>
    <collection role="institutes" number="">Fakultät Kommunikation und Umwelt</collection>
    <thesisPublisher>Hochschule Rhein-Waal</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-rhein-waal/files/401/dixon_megill_nebe_vehicular_2019_tia.pdf</file>
  </doc>
</export-example>
