The persuasive automobile: Design and evaluation of a persuasive lane-specific advice human machine interface

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Abstract

Traffic congestion is a major societal challenge. By advising drivers on the optimal lane to drive, traffic flow can be improved, and congestion reduced. In this paper we describe the development of a lane-specific advice Human Machine Interface (HMI). Persuading drivers to follow an advice that is beneficial to the traffic situation, but may not be immediately beneficial to the drivers themselves, is challenging. In this paper we define persuasive elements to encourage drivers to follow the lane-specific advices. We then describe the interface design process, followed by its evaluation using a driving simulator study. In the simulator study, the effect of two types of persuasion are evaluated: A competitive variant where drivers could earn points and compete with others, and a cooperative variant where real-time information on the number of compliant drivers was available. Participants drove in the simulator on two days. Between days, the treatment groups viewed a Web-portal showing their performance and encouragement from an avatar. Those in the competitive and cooperative groups followed significantly more advices (117 and 111) than those in the control group (89). No significant differences were visible between competitive and cooperative groups. The differences between groups only emerged on the second day.

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Van Gent, P., Farah, H., Van Nes, N., & Van Arem, B. (2020). The persuasive automobile: Design and evaluation of a persuasive lane-specific advice human machine interface. IEEE Open Journal of Intelligent Transportation Systems, 1(1), 93–108. https://doi.org/10.1109/OJITS.2020.3005528

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