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“I’m Your Personal Co-Driver—How Can I Assist You?” Assessing the Potential of Personal Assistants for Truck Drivers

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Intelligent Human Systems Integration 2019 (IHSI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 903))

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Abstract

User acceptance is widely recognized as a major factor for predicting the intention to use a technical device. As such, personal assistants for truck drivers pose significant design and function challenges. Long, solitary hours and comprehensive interaction with the vehicle open various possibilities for an assistant’s service. Including drivers’ requirements early in development is hence beneficial. This paper describes the result of an online survey intended to assess truck drivers’ attitudes toward personal assistants in the truck cabin. Its authors investigate the potential and the predicted acceptance of personal conversation, virtual, or robotic agents as interaction partners. They furthermore analyze how hedonic and pragmatic attributes affect the intention to use these personal assistants.

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Notes

  1. 1.

    Local transport: up to 50 km/day; regional transport: 50 to 150 km/day; long haul transport: more than 150 km/day.

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Acknowledgements

As first author, Jana Fank initiated this article’s research idea, and contributed to the study design and data analysis. Markus Lienkamp made an essential contribution to the conception of the research project. He critically revised the paper with regard to important content and gave final approval of the version to be published. Special thanks goes to Ramon Tengel, who contributed to the study’s design. The research was conducted with basic research funds from the Institute of Automotive Technology, Technical University of Munich.

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Correspondence to Jana Fank .

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Fank, J., Lienkamp, M. (2019). “I’m Your Personal Co-Driver—How Can I Assist You?” Assessing the Potential of Personal Assistants for Truck Drivers. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration 2019. IHSI 2019. Advances in Intelligent Systems and Computing, vol 903. Springer, Cham. https://doi.org/10.1007/978-3-030-11051-2_121

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