What drives people to accept automated vehicles? Findings from a field experiment

By Zhigang Xu, Kaifan Zhang, Haigen Min, Zhen Wang, Xiangmo Zhao, Peng Liu. Transportation Research Part C: Emerging Technologies, 2018

568 citations recorded by the source corpus.

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.

Subfields: Automotive Engineering, Social Psychology

View Paper: https://www.semanticscholar.org/paper/7ab5048042f9ff9130be3a3f4fa3033359234571

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Riender Happee
2. Sina Nordhoff

In Social Psychology

1. Tyron Louw
2. Sina Nordhoff
3. Natasha Merat
4. Riender Happee

Citations in the corpus

• Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries (2020, methodology): “In fact, the examination of the acceptance of conditional automation has been underrepresented by literature on automated vehicle acceptance, with only 3 out of 124 studies (Buckley et al., 2018; Xu et al., 2018; Zhang et al., 2019) being devoted to the study of conditional automation (Nordhoff et a”