Abstract
Young people aged 18ā24 are the main force of consumption in China, are more inclined to buy self-driving cars and are willing to pay higher prices, which makes them an important potential user of autonomous vehicles. Automated vehicles seem to provide more possibilities in terms of independence and safety. In order to explore the user needs of the young people, we set up a study based on semi-structured interviews and a role play. Our results demonstrated that 90% of the young people (nā=ā20.) are pleased to drive the automated vehicles, they are looking forward to the aging of automated driving. The remaining 10% of young people were unwilling to try out automated driving systems owing to the nondeterminacy and suspicion (fear of mechanical failures), and they are deeply worried about safety. In the exploration of demand, regardless of the level of acceptance, young people have shown a high demand for safety and security facilities. In addition, we have explored the needs of young people for entertainment and human-computer interaction. This will likely provide arising opportunities for young people.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Deloitte. 2019 Deloitte Global Automotive Consumer Study (2019). https://www2.deloitte.com/cn/zh/pages/consumer-industrial-products/articles/2019-global-auto-consumer-study.htm
Ellis, B., Douglas, N., Frost, T.: Willingness to pay for driverless cars. In: Australasian Transport Research Forum (ATRF). Elsevier, Melbourne, Australia (2016)
Zhang, Q., Jiang, Z., Zheng, D., Man, D., Xu, X.: Chinese carless young driversā self-reported driving behavior and simulated driving performance. Traffic Inj. Prev. 14(8), 853ā860 (2013)
McDonald, C.C., Curry, A.E., Kandadai, V., Sommers, M.S., Winston, F.K.: Comparison of teen and adult driver crash scenarios in a nationally representative sample of serious crashes. Accid. Anal. Prev. 72, 302ā308 (2014)
Poczter, S.L., Jankovic, L.M.: The google car: driving toward a better future? J. Bus. Case Stud. (JBCS) 10(1), 7ā14 (2013)
Sovie, D., Curran, J., Schoelwer, M., Bjƶrnsjƶ, A.: 2019 Deloitte Global Automotive Consumer Study (2019)
Kƶnig, M., Neumayr, L.: Usersā resistance towards radical innovations: the case of the self-driving car. Transp. Res. Part F Traffic Psychol. Behav. 44, 42ā52 (2017)
Joshi, S., Bellet, T., Bodard, V., Amditis, A.: Perceptions of risk and control: understanding acceptance of advanced driver assistance systems. In: Gross, T., Gulliksen, J., KotzĆ©, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M. (eds.) INTERACT 2009. LNCS, vol. 5726, pp. 524ā527. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03655-2_58
Hƶltl, A., Trommer, S.: Driver assistance systems for transport system efficiency: influencing factors on user acceptance. J. Intell. Transp. Syst. 17(3), 245ā254 (2013)
Piao, J., McDonald, M., Henry, A., Vaa, T., Tveit, O.: An assessment of user acceptance of intelligent speed adaptation systems. In: Proceedings 2005 IEEE Intelligent Transportation Systems 2005, pp. 1045ā1049. IEEE (2005)
Haboucha, C.J., Ishaq, R., Shiftan, Y.: User preferences regarding autonomous vehicles. Transp. Res. Part C Emerg. Technol. 78, 37ā49 (2017)
Kun, A.L., Boll, S., Schmidt, A.: Shifting gears: user interfaces in the age of autonomous driving. IEEE Pervasive Comput. 15(1), 32ā38 (2016)
Mohr, D., et al.: Competing for the connected customer. Technical report. McKinsey & Company (2015). https://www.mckinsey.de/sites/mck_files/files/competing_for_the_connected_customer.pdf
Pfleging, B., Rang, M., Broy, N.: Investigating user needs for non-driving-related activities during automated driving. In: Proceedings of the 15th International Conference on Mobile and Ubiquitous Multimedia, pp. 91ā99 (2016)
Rƶdel, C., Stadler, S., Meschtscherjakov, A., Tscheligi, M.: Towards autonomous cars: the effect of autonomy levels on acceptance and user experience. In: Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, pp. 1ā8 (2014)
Guion, L.A., Diehl, D.C., McDonald, D.: Conducting an in-depth interview. McCarty Hall, FL: University of Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, EDIS (2001)
Chen, Z.Y., Zeng, Y.: Classification of product requirements based on product environment. Concurrent Eng. 14(3), 219ā230 (2006)
Ritchie, J., Spencer, L.: Qualitative data analysis for applied policy research. In: Bryman, A., Burgess, B. (Eds.) Analyzing Qualitative Data, p. 173
Acknowledgement
TheĀ paperĀ isĀ supportedĀ byĀ HunanĀ KeyĀ ResearchĀ andĀ DevelopmentĀ ProjectĀ (GrantĀ No.Ā 2020SK2094)Ā andĀ theĀ NationalĀ KeyĀ TechnologiesĀ R&DĀ ProgramĀ ofĀ ChinaĀ (GrantĀ No.Ā 2015BAH22F01).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Cheng, S., Dong, H., Yue, Y., Tan, H. (2021). Automated Driving: Acceptance and Chances for Young People. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Cultural Heritage, Tourism, Autonomous Vehicles, and Intelligent Agents. HCII 2021. Lecture Notes in Computer Science(), vol 12773. Springer, Cham. https://doi.org/10.1007/978-3-030-77080-8_16
Download citation
DOI: https://doi.org/10.1007/978-3-030-77080-8_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77079-2
Online ISBN: 978-3-030-77080-8
eBook Packages: Computer ScienceComputer Science (R0)