Abstract
This paper represents a synthesis of existing empirical acceptance studies on automated driving and scientific literature on technology acceptance. The objective of this paper is to study user acceptance of driverless vehicles that fall into SAE level 4, as they operate within the constraints of dedicated infrastructure. The review indicates that previous acceptance studies on automated driving are skewed towards car users, creating a need for targeted acceptance studies, including users of public transport. For obvious reasons previous studies targeted respondents who had not experienced driverless vehicles. As driverless vehicle are currently being demonstrated in pilot projects, we can now start to investigate their acceptance by users inside and outside of such vehicles. Addressing the multidimensional nature of acceptance, we develop a conceptual model that integrates a holistic and comprehensive set of variables to explain, predict and improve user acceptance of driverless vehicles. It links two dominant models from the technology acceptance management literature, the Unified Theory of Acceptance and Technology Use (UTAUT) and the Pleasure-Arousal-Dominance-Framework (PAD), with a number of external variables that are divided into system-specific, user and contextual characteristics.
Original language | English |
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Title of host publication | 2016 TRB 95th Annual Meeting Compendium of Papers |
Place of Publication | Washington, DC, USA |
Publisher | Transportation Research Board (TRB) |
Number of pages | 18 |
Publication status | Published - 2016 |
Event | Transportation Research Board 95th annual meeting - Washington, United States Duration: 10 Jan 2016 → 14 Jan 2016 Conference number: 95 |
Conference
Conference | Transportation Research Board 95th annual meeting |
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Abbreviated title | TRB 95 |
Country/Territory | United States |
City | Washington |
Period | 10/01/16 → 14/01/16 |
Bibliographical note
Accepted Author ManuscriptKeywords
- acceptance
- driverless vehicles
- human factors
- full automation
- real scenarios
- test rides