Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style

The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Lu, Yufeng [verfasserIn] Yi, Binlin [verfasserIn] Song, Xiaolin [verfasserIn] Zhao, Song [verfasserIn] Wang, Jianqiang [verfasserIn] Cao, Haotian [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation

Übergeordnetes Werk:	Enthalten in: Transportation research / F - Amsterdam [u.a.] : Elsevier Science, 1998, 90, Seite 269-286
Übergeordnetes Werk:	volume:90 ; pages:269-286

DOI / URN:	10.1016/j.trf.2022.08.011

Katalog-ID:	ELV008571333

Internformat


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245	1	0	\|a Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style
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520			\|a The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance.
650		4	\|a Highly automated driving
650		4	\|a Automated driving style
650		4	\|a Trust
650		4	\|a Situational awareness
650		4	\|a State anxiety
650		4	\|a Role adaptation
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700	1		\|a Wang, Jianqiang \|e verfasserin \|4 aut
700	1		\|a Cao, Haotian \|e verfasserin \|4 aut
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Indexfelder

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publishDate	2022
allfields	10.1016/j.trf.2022.08.011 doi (DE-627)ELV008571333 (ELSEVIER)S1369-8478(22)00183-8 DE-627 ger DE-627 rda eng 380 DE-600 Lu, Yufeng verfasserin aut Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance. Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation Yi, Binlin verfasserin aut Song, Xiaolin verfasserin aut Zhao, Song verfasserin aut Wang, Jianqiang verfasserin aut Cao, Haotian verfasserin aut Enthalten in Transportation research / F Amsterdam [u.a.] : Elsevier Science, 1998 90, Seite 269-286 Online-Ressource (DE-627)320599191 (DE-600)2019959-4 (DE-576)259485136 1873-5517 nnns volume:90 pages:269-286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 90 269-286
spelling	10.1016/j.trf.2022.08.011 doi (DE-627)ELV008571333 (ELSEVIER)S1369-8478(22)00183-8 DE-627 ger DE-627 rda eng 380 DE-600 Lu, Yufeng verfasserin aut Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance. Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation Yi, Binlin verfasserin aut Song, Xiaolin verfasserin aut Zhao, Song verfasserin aut Wang, Jianqiang verfasserin aut Cao, Haotian verfasserin aut Enthalten in Transportation research / F Amsterdam [u.a.] : Elsevier Science, 1998 90, Seite 269-286 Online-Ressource (DE-627)320599191 (DE-600)2019959-4 (DE-576)259485136 1873-5517 nnns volume:90 pages:269-286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 90 269-286
allfields_unstemmed	10.1016/j.trf.2022.08.011 doi (DE-627)ELV008571333 (ELSEVIER)S1369-8478(22)00183-8 DE-627 ger DE-627 rda eng 380 DE-600 Lu, Yufeng verfasserin aut Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance. Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation Yi, Binlin verfasserin aut Song, Xiaolin verfasserin aut Zhao, Song verfasserin aut Wang, Jianqiang verfasserin aut Cao, Haotian verfasserin aut Enthalten in Transportation research / F Amsterdam [u.a.] : Elsevier Science, 1998 90, Seite 269-286 Online-Ressource (DE-627)320599191 (DE-600)2019959-4 (DE-576)259485136 1873-5517 nnns volume:90 pages:269-286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 90 269-286
allfieldsGer	10.1016/j.trf.2022.08.011 doi (DE-627)ELV008571333 (ELSEVIER)S1369-8478(22)00183-8 DE-627 ger DE-627 rda eng 380 DE-600 Lu, Yufeng verfasserin aut Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance. Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation Yi, Binlin verfasserin aut Song, Xiaolin verfasserin aut Zhao, Song verfasserin aut Wang, Jianqiang verfasserin aut Cao, Haotian verfasserin aut Enthalten in Transportation research / F Amsterdam [u.a.] : Elsevier Science, 1998 90, Seite 269-286 Online-Ressource (DE-627)320599191 (DE-600)2019959-4 (DE-576)259485136 1873-5517 nnns volume:90 pages:269-286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 90 269-286
allfieldsSound	10.1016/j.trf.2022.08.011 doi (DE-627)ELV008571333 (ELSEVIER)S1369-8478(22)00183-8 DE-627 ger DE-627 rda eng 380 DE-600 Lu, Yufeng verfasserin aut Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style 2022 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance. Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation Yi, Binlin verfasserin aut Song, Xiaolin verfasserin aut Zhao, Song verfasserin aut Wang, Jianqiang verfasserin aut Cao, Haotian verfasserin aut Enthalten in Transportation research / F Amsterdam [u.a.] : Elsevier Science, 1998 90, Seite 269-286 Online-Ressource (DE-627)320599191 (DE-600)2019959-4 (DE-576)259485136 1873-5517 nnns volume:90 pages:269-286 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 AR 90 269-286
language	English
source	Enthalten in Transportation research / F 90, Seite 269-286 volume:90 pages:269-286
sourceStr	Enthalten in Transportation research / F 90, Seite 269-286 volume:90 pages:269-286
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation
dewey-raw	380
isfreeaccess_bool	false
container_title	Transportation research / F
authorswithroles_txt_mv	Lu, Yufeng @@aut@@ Yi, Binlin @@aut@@ Song, Xiaolin @@aut@@ Zhao, Song @@aut@@ Wang, Jianqiang @@aut@@ Cao, Haotian @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	320599191
dewey-sort	3380
id	ELV008571333
language_de	englisch
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author	Lu, Yufeng
spellingShingle	Lu, Yufeng ddc 380 misc Highly automated driving misc Automated driving style misc Trust misc Situational awareness misc State anxiety misc Role adaptation Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style
authorStr	Lu, Yufeng
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topic_title	380 DE-600 Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style Highly automated driving Automated driving style Trust Situational awareness State anxiety Role adaptation
topic	ddc 380 misc Highly automated driving misc Automated driving style misc Trust misc Situational awareness misc State anxiety misc Role adaptation
topic_unstemmed	ddc 380 misc Highly automated driving misc Automated driving style misc Trust misc Situational awareness misc State anxiety misc Role adaptation
topic_browse	ddc 380 misc Highly automated driving misc Automated driving style misc Trust misc Situational awareness misc State anxiety misc Role adaptation
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title	Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style
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title_full	Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style
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author_browse	Lu, Yufeng Yi, Binlin Song, Xiaolin Zhao, Song Wang, Jianqiang Cao, Haotian
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title_sort	can we adapt to highly automated vehicles as passengers? the mediating effect of trust and situational awareness on role adaption moderated by automated driving style
title_auth	Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style
abstract	The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance.
abstractGer	The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance.
abstract_unstemmed	The emergence of highly automated driving technology provides safe and convenient travel while also causing user inadaptation. Therefore, based on human factors engineering, it is necessary to study highly automated vehicles (HAVs) that meet different user needs. Thus, this study aims to investigate the relationships between state anxiety, situational awareness, trust, and role adaptation. The adaptation model is constructed to conduct a study on the adaptation of HAVs with different automated styles when user roles change from driver to passenger. Simulated riding was conducted in the HAV experiment (N = 117), collecting scale data after each participant had experienced each automated driving style. A structural equation modeling approach was applied to analyze the adaptation model based on scale data. The results showed that there was a significant correlation between state anxiety, situational awareness, trust, and role adaptation. State anxiety has a significant negative predictive effect on trust, situational awareness, and role adaptation. In addition to its direct impact on role adaptation, state anxiety also has an indirect effect on role adaptation through situational awareness and trust. Furthermore, the automated driving style has been confirmed to have a moderating role in the relationship between the direct and indirect effects of state anxiety and role adaptation. Our findings contribute to multiple streams of the literature and have important implications for designing personalized automated driving to improve user acceptance.
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title_short	Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style
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author2	Yi, Binlin Song, Xiaolin Zhao, Song Wang, Jianqiang Cao, Haotian
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doi_str	10.1016/j.trf.2022.08.011
up_date	2024-07-06T20:09:29.487Z
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Can we adapt to highly automated vehicles as passengers? The mediating effect of trust and situational awareness on role adaption moderated by automated driving style

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