Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training
Objective The current study examined whether differences in the branding and description or mode of training materials influence drivers’ understanding and expectations of a partial driving automation system. Background How technology is described might influence consumers’ understanding and expecta...
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Veröffentlicht in: | Human factors 2024-05, Vol.66 (5), p.1531-1544 |
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creator | Singer, Jeremiah Tefft, Brian C Benson, Aaron Jenness, James W Horrey, William J |
description | Objective
The current study examined whether differences in the branding and description or mode of training materials influence drivers’ understanding and expectations of a partial driving automation system.
Background
How technology is described might influence consumers’ understanding and expectations, even if all information is accurate.
Method
Ninety drivers received training about a real partial driving automation system with a fictitious name. Participants were randomly assigned to a branding condition (system named AutonoDrive, training emphasized capabilities; or system named DriveAssist, training emphasized limitations) and training mode (quick-start brochure; video; or in-person demonstration). No safety-critical information was withheld nor deliberately misleading information provided. After training, participants drove a vehicle equipped with the system. Associations of drivers’ expectations with branding condition and training mode were assessed using between-subjects comparisons of questionnaire responses obtained pre- and post-drive.
Results
Immediately after training, those who received information emphasizing the system’s capabilities had greater expectations of the system’s function and crash avoidance capability in a variety of driving scenarios, including many in which the system would not work, as well as greater willingness to utilize the system’s workload reduction benefits to take more risks. Most but not all differences persisted after driving the vehicle. Expectations about collision avoidance differed by training mode pre-drive but not post-drive.
Conclusion
Training that emphasizes a partial driving automation system’s capabilities and downplays its limitations can foster overconfidence.
Application
Accuracy of technical information does not guarantee understanding; training should provide a balanced view of a system’s limitations as well as capabilities. |
doi_str_mv | 10.1177/00187208221143024 |
format | Article |
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The current study examined whether differences in the branding and description or mode of training materials influence drivers’ understanding and expectations of a partial driving automation system.
Background
How technology is described might influence consumers’ understanding and expectations, even if all information is accurate.
Method
Ninety drivers received training about a real partial driving automation system with a fictitious name. Participants were randomly assigned to a branding condition (system named AutonoDrive, training emphasized capabilities; or system named DriveAssist, training emphasized limitations) and training mode (quick-start brochure; video; or in-person demonstration). No safety-critical information was withheld nor deliberately misleading information provided. After training, participants drove a vehicle equipped with the system. Associations of drivers’ expectations with branding condition and training mode were assessed using between-subjects comparisons of questionnaire responses obtained pre- and post-drive.
Results
Immediately after training, those who received information emphasizing the system’s capabilities had greater expectations of the system’s function and crash avoidance capability in a variety of driving scenarios, including many in which the system would not work, as well as greater willingness to utilize the system’s workload reduction benefits to take more risks. Most but not all differences persisted after driving the vehicle. Expectations about collision avoidance differed by training mode pre-drive but not post-drive.
Conclusion
Training that emphasizes a partial driving automation system’s capabilities and downplays its limitations can foster overconfidence.
Application
Accuracy of technical information does not guarantee understanding; training should provide a balanced view of a system’s limitations as well as capabilities.</description><identifier>ISSN: 0018-7208</identifier><identifier>ISSN: 1547-8181</identifier><identifier>EISSN: 1547-8181</identifier><identifier>DOI: 10.1177/00187208221143024</identifier><identifier>PMID: 36530124</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Accidents, Traffic - prevention & control ; Automation ; Automobile Driving ; Collision avoidance ; Humans ; Motivation ; Reaction Time ; Safety critical ; Surface Transportation ; Technical information ; Training</subject><ispartof>Human factors, 2024-05, Vol.66 (5), p.1531-1544</ispartof><rights>2022, The Author(s).</rights><rights>2022, The Author(s). 2022 Human Factors and Ergonomics Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c467t-7b844be875d9c7dcafa9afbd10041e0757b85da8b9aec5816d3bef87168fa4863</citedby><cites>FETCH-LOGICAL-c467t-7b844be875d9c7dcafa9afbd10041e0757b85da8b9aec5816d3bef87168fa4863</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/00187208221143024$$EPDF$$P50$$Gsage$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/00187208221143024$$EHTML$$P50$$Gsage$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,21798,27901,27902,43597,43598</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36530124$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Singer, Jeremiah</creatorcontrib><creatorcontrib>Tefft, Brian C</creatorcontrib><creatorcontrib>Benson, Aaron</creatorcontrib><creatorcontrib>Jenness, James W</creatorcontrib><creatorcontrib>Horrey, William J</creatorcontrib><title>Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training</title><title>Human factors</title><addtitle>Hum Factors</addtitle><description>Objective
The current study examined whether differences in the branding and description or mode of training materials influence drivers’ understanding and expectations of a partial driving automation system.
Background
How technology is described might influence consumers’ understanding and expectations, even if all information is accurate.
Method
Ninety drivers received training about a real partial driving automation system with a fictitious name. Participants were randomly assigned to a branding condition (system named AutonoDrive, training emphasized capabilities; or system named DriveAssist, training emphasized limitations) and training mode (quick-start brochure; video; or in-person demonstration). No safety-critical information was withheld nor deliberately misleading information provided. After training, participants drove a vehicle equipped with the system. Associations of drivers’ expectations with branding condition and training mode were assessed using between-subjects comparisons of questionnaire responses obtained pre- and post-drive.
Results
Immediately after training, those who received information emphasizing the system’s capabilities had greater expectations of the system’s function and crash avoidance capability in a variety of driving scenarios, including many in which the system would not work, as well as greater willingness to utilize the system’s workload reduction benefits to take more risks. Most but not all differences persisted after driving the vehicle. Expectations about collision avoidance differed by training mode pre-drive but not post-drive.
Conclusion
Training that emphasizes a partial driving automation system’s capabilities and downplays its limitations can foster overconfidence.
Application
Accuracy of technical information does not guarantee understanding; training should provide a balanced view of a system’s limitations as well as capabilities.</description><subject>Accidents, Traffic - prevention & control</subject><subject>Automation</subject><subject>Automobile Driving</subject><subject>Collision avoidance</subject><subject>Humans</subject><subject>Motivation</subject><subject>Reaction Time</subject><subject>Safety critical</subject><subject>Surface Transportation</subject><subject>Technical information</subject><subject>Training</subject><issn>0018-7208</issn><issn>1547-8181</issn><issn>1547-8181</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>EIF</sourceid><recordid>eNp1kU2P0zAQhi0EYkvhB3BBlrjsJYsnsWPnhHZL2UVaCQTlbE0Sp3iV2MV2VvTfk9BSvsRpNDPPvDOjl5DnwC4ApHzFGCiZM5XnALxgOX9AFiC4zBQoeEgWcz-bgTPyJMY7xlhZFeIxOStKUTDI-YLoN8Hem0DX33amSZisd5H6jiL9gCFZ7OkMWLell2Pyww-AftrHZAZqHf1o-kMpeXoV0LUzOQW6CWjdlDwljzrso3l2jEvy-e16s7rJbt9fv1td3mYNL2XKZK04r42Soq0a2TbYYYVd3QJjHAyTYgJEi6qu0DRCQdkWtemUhFJ1yFVZLMnrg-5urAfTNsalgL3eBTtg2GuPVv_ZcfaL3vp7DaziRQlsUjg_KgT_dTQx6cHGxvQ9OuPHqHMphGKiADWhL_9C7_wY3PSfzishJeSimk-CA9UEH2Mw3ekaYHr2T__j3zTz4vc3ThM_DZuAiwMQcWt-rf2_4ndIeKN4</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Singer, Jeremiah</creator><creator>Tefft, Brian C</creator><creator>Benson, Aaron</creator><creator>Jenness, James W</creator><creator>Horrey, William J</creator><general>SAGE Publications</general><general>Human Factors and Ergonomics Society</general><scope>AFRWT</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T2</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20240501</creationdate><title>Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training</title><author>Singer, Jeremiah ; Tefft, Brian C ; Benson, Aaron ; Jenness, James W ; Horrey, William J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c467t-7b844be875d9c7dcafa9afbd10041e0757b85da8b9aec5816d3bef87168fa4863</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Accidents, Traffic - prevention & control</topic><topic>Automation</topic><topic>Automobile Driving</topic><topic>Collision avoidance</topic><topic>Humans</topic><topic>Motivation</topic><topic>Reaction Time</topic><topic>Safety critical</topic><topic>Surface Transportation</topic><topic>Technical information</topic><topic>Training</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Singer, Jeremiah</creatorcontrib><creatorcontrib>Tefft, Brian C</creatorcontrib><creatorcontrib>Benson, Aaron</creatorcontrib><creatorcontrib>Jenness, James W</creatorcontrib><creatorcontrib>Horrey, William J</creatorcontrib><collection>Sage Journals GOLD Open Access 2024</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Human factors</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Singer, Jeremiah</au><au>Tefft, Brian C</au><au>Benson, Aaron</au><au>Jenness, James W</au><au>Horrey, William J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training</atitle><jtitle>Human factors</jtitle><addtitle>Hum Factors</addtitle><date>2024-05-01</date><risdate>2024</risdate><volume>66</volume><issue>5</issue><spage>1531</spage><epage>1544</epage><pages>1531-1544</pages><issn>0018-7208</issn><issn>1547-8181</issn><eissn>1547-8181</eissn><abstract>Objective
The current study examined whether differences in the branding and description or mode of training materials influence drivers’ understanding and expectations of a partial driving automation system.
Background
How technology is described might influence consumers’ understanding and expectations, even if all information is accurate.
Method
Ninety drivers received training about a real partial driving automation system with a fictitious name. Participants were randomly assigned to a branding condition (system named AutonoDrive, training emphasized capabilities; or system named DriveAssist, training emphasized limitations) and training mode (quick-start brochure; video; or in-person demonstration). No safety-critical information was withheld nor deliberately misleading information provided. After training, participants drove a vehicle equipped with the system. Associations of drivers’ expectations with branding condition and training mode were assessed using between-subjects comparisons of questionnaire responses obtained pre- and post-drive.
Results
Immediately after training, those who received information emphasizing the system’s capabilities had greater expectations of the system’s function and crash avoidance capability in a variety of driving scenarios, including many in which the system would not work, as well as greater willingness to utilize the system’s workload reduction benefits to take more risks. Most but not all differences persisted after driving the vehicle. Expectations about collision avoidance differed by training mode pre-drive but not post-drive.
Conclusion
Training that emphasizes a partial driving automation system’s capabilities and downplays its limitations can foster overconfidence.
Application
Accuracy of technical information does not guarantee understanding; training should provide a balanced view of a system’s limitations as well as capabilities.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>36530124</pmid><doi>10.1177/00187208221143024</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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source | SAGE Complete A-Z List; MEDLINE |
subjects | Accidents, Traffic - prevention & control Automation Automobile Driving Collision avoidance Humans Motivation Reaction Time Safety critical Surface Transportation Technical information Training |
title | Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training |
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