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    <responseDate>2026-10-15T08:29:52Z</responseDate>
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            <header>
                <identifier>oai:data.mendeley.com/xsg7n4233n.1</identifier>
                <datestamp>2025-07-03T15:25:09Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>agbozo, reuben</dc:creator>
    <dc:title>Data_Driver_ Engagement_and_Workload_ Assessment_in_ Automated_Driving_Systems</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This dataset comprises survey responses collected via Microsoft Forms, focusing on drivers&apos; subjective experience and workload across four distinct driving automation modes. The primary objective of this study was to assess both visual and physical workload perceptions under varying levels of automation.

The four driving modes investigated are defined as follows:

Mode 1: Steering: Human, Speed/Brake: Human (Fully Manual)

Mode 2: Steering: Human, Speed/Brake: Automated (Partial Automation - Longitudinal Control)

Mode 3: Steering: Automated, Speed/Brake: Human (Partial Automation - Lateral Control)

Mode 4: Steering: Automated, Speed/Brake: Automated (Full Automation)</dc:description>
    <dc:subject>Human Subject</dc:subject>
    <dc:contributor id="https://orcid.org/0000-0001-8147-7609">Agbozo, Reuben</dc:contributor>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/xsg7n4233n.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/xsg7n4233n.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:relation>https://data.mendeley.com/datasets/xsg7n4233n</dc:relation>
    <dc:date>2025-07-03T15:25:09Z</dc:date>
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