What drives people to accept automated vehicles? Findings from a field experiment |
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| Institution: | 1. School of Information Engineering, Chang’an University, Xi’an, Shaanxi 710064, PR China;2. College of Management and Economics, Tianjin University, Tianjin 300072, PR China;1. Institute for Transport Studies, University of Leeds, LS2 9JT, United Kingdom;2. DLR German Aerospace, 38108 Braunschweig, Germany;1. Department of Planning and Environmental Management, School of Environment, Education and Development, University of Manchester, M13 9PL, Oxford Road, UK;2. Department of Geography, Trinity College Dublin, The University of Dublin, Museum Building, Dublin 2, Ireland;1. School of Information Engineering, Chang’an University, Xi’an, Shaanxi 710064, PR China;2. The Joint Laboratory for Internet of Vehicles, Ministry of Education – China Mobile Communications Corporation, Xi’an, Shaanxi 710064, PR China;3. College of Management and Economics, Tianjin University, Tianjin 300072, PR China;4. Department of Industrial Engineering, Tsinghua University, Beijing, 100084, PR China;5. Department of Industrial Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 100044, PR China;6. Center for Psychological Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, PR China |
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| Abstract: | This field study aims at understanding the influence of direct experience of an automated vehicle (AV, Level 3) and explaining and predicting public acceptance of AVs through a psychological model. The model includes behavioral intention (BI) to use self-driving vehicles (SDVs, Level 5), willingness to re-ride (WTR) in our AV (Level 3), and their four potential determinants, namely perceived usefulness (PU), perceived ease of use (PEU), trust related to SDVs, and perceived safety (PS) while riding in our AV. The last two determinants are largely ignored, but we consider them critical in the context of AVs. Three-hundred students were invited as participants (passengers) to experience the AV. The trust, PU, PEU, and BI of the participants were recorded prior to their experiencing the AV; after this experience, all the constructs of the psychological model were recorded. The participants’ experience with the AV was found to increase their trust, PU and PEU (but not BI), the consistency between PU/PEU and BI, and the explanatory power of BI. The model explained 55% of the variance in BI and 40% in WTR. PU, trust, and PS were found to be steady and direct predictors of both the acceptance measures; PEU predicted BI only after the participants’ AV experience. Mediation analysis showed that trust also can indirectly affect AV acceptance through other determinants. Out-of-sample prediction confirmed the model’s predictive capability for AV acceptance. The theoretical contributions and practical implications of the findings are discussed. |
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| Keywords: | Automated vehicles Technology acceptance Trust in AVs Perceived safety Perceived usefulness Perceived ease of use |
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