Abstract
In the 21st century, with the development of society and the economy, people are paying more and more attention to the special needs of special groups of people, for example, pregnant women’s problem of transportation. As we could imagine, FAV (Fully Automated Vehicles) has the potential to become the measurement of this problem, by improving the safety and flexibility of traffic for pregnant women. However, FAV can only help when women can accept FAV while pregnancy.
According to the existed research, Chinese women have less trust in smart driving technology than men. We need to question: why?
This article will study on factors affecting pregnant women’s acceptance of fully automated vehicles, by showing the participants fully automated driving videos and playing semi-immersive video simulations.
After our work, these theories can counteract the FAV design for pregnant women groups, so that pregnant women’s travel problems can be optimally solved, thereby improving the quality of their life and increasing their employment of FAV and the willingness to buy fully autonomous vehicles. The research in this article aims to explore the relationship between pregnant women’s acceptance of fully automated vehicles, individual internal factors, and weather conditions in the driving environment.
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Ma, X.: The design and analysis of pregnant women’s transportation. North China Electric Power University (2017)
You, F., Chu, X.: Research on investigation of consumer market acceptance for intelligent vehicles in China: case study in Guangzhou. J. Guangxi Univ. (Nat. Sci. Ed.) 44(02), 534–545 (2019)
Yang, W.: Depression status and group mindfulness intervention study of pregnant women. Southern Medical University (2019)
Haghzare, S., Bak, K., Campos, J., Mihailidis, A.: Factors influencing older adults’ acceptance of fully automated vehicles, pp. 135–139 (2019). https://doi.org/10.1145/3349263.3351520
Auriault, F., et al.: Pregnant women in vehicles: driving habits, position and risk of injury. Accid. Anal. Prev. 89, 57–61 (2016)
Politis, I., Langdon, P., Bradley, M., Skrypchuk, L., Alexander Mouzakitis, P., Clarkson, J.: Designing autonomy in cars: a survey and two focus groups on driving habits of an inclusive user group, and group attitudes towards autonomous cars. In: Di Bucchianico, G., Kercher, P.F. (eds.) AHFE 2017. AISC, vol. 587, pp. 161–173. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-60597-5_15
Grove, R., Prapavessis, H.: Abbreviated POMS Questionnaire (items and scoring key) (2016)
Nasreddine, Z.S., et al.: The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J. Am. Geriatr. Soc. 53(4), 695–699 (2005)
Hewitt, C., Politis, I., Amanatidis, T., Sarkar, A.: Assessing public perception of selfdriving cars: the autonomous vehicle acceptance model. In: Conference on Intelligent User Interfaces (IUI 2019), March 2019
Jensen, T., Khan, M.M.H., Albayram, Y., Al Fahim, M.A., Buck, R.: Anticipated emotions in initial trust evaluations of a drone system based on performance and process information. Int. J. Hum.–Comput. Interact. https://doi.org/10.1080/10447318.2019.1642616
SAE International: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles (2016). https://www.sae.org/standards/content/j3016_201609/
Acknowledgement
The paper is supported by Hunan Key Research and Development Project (Grant No. 2020SK2094) and the National Key Technologies R&D Program of China (Grant No. 2015BAH22F01).
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Liu, X., He, S., Zhao, X., Tan, H. (2021). What Will Influence Pregnant Women’s Acceptance of Fully Automated Vehicles?. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Posters. HCII 2021. Communications in Computer and Information Science, vol 1421. Springer, Cham. https://doi.org/10.1007/978-3-030-78645-8_33
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DOI: https://doi.org/10.1007/978-3-030-78645-8_33
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