Abstract
The driving experience provided by autonomous vehicles is a crucial factor in determining the level of acceptance and trust that drivers have in the technology. In order to enhance this experience, it is necessary to understand drivers’ preferences and attitudes towards the automated driving style. In this study, 32 drivers with 4 manual driving styles were recruited for simulation experiment under 2 driving scenarios. During each scenario, the drivers were presented with 3 different automated driving styles, and their preferences for automated driving style, trust and acceptance for the autonomous vehicle were recorded. The results showed that there were no significant statistical differences between the preferred automated driving styles of different drivers under each scenario. However, the driving style preferences of Risky and Careful drivers differed from those of other drivers. Additionally, driver preferences varied between passive and active driving scenarios. The study found that driver acceptance of autonomous vehicles was more stable and less influenced by the scenario, compared to trust. The findings from this study can be used to improve the design of autonomous driving systems and enhance the overall driving experience. This, in turn, is hoped to drive the widespread adoption of autonomous vehicles and bring us one step closer to realizing the full potential of this transformative technology.
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References
Asgari, H., Jin, X.: Incorporating attitudinal factors to examine adoption of and willingness to pay for autonomous vehicles. Transp. Res. Rec. 2673(8), 418–429 (2019). https://doi.org/10.1177/0361198119839987
Baccarella, C.V., Wagner, T.F., Scheiner, C.W., Maier, L., Voigt, K.I.: Investigating consumer acceptance of autonomous technologies: the case of self-driving automobiles. Eur. J. Innov. Manag. (2020). https://doi.org/10.1108/EJIM-09-2019-0245
Beiker, S.A.: Legal aspects of autonomous driving. Santa Clara L. Rev. 52(4), 1145 (2012)
Bellem, H., Schönenberg, T., Krems, J.F., Schrauf, M.: Objective metrics of comfort: developing a driving style for highly automated vehicles. Transp. Res. F: Traffic Psychol. Behav. 41, 45–54 (2016). https://doi.org/10.1016/j.trf.2016.05.005
Bellem, H., Thiel, B., Schrauf, M., Krems, J.F.: Comfort in automated driving: an analysis of preferences for different automated driving styles and their dependence on personality traits. Transp. Res. F: Traffic Psychol. Behav. 55, 90–100 (2018). https://doi.org/10.1016/j.trf.2018.02.036
Berliner, R.M., Hardman, S., Tal, G.: Uncovering early adopter’s perceptions and purchase intentions of automated vehicles: insights from early adopters of electric vehicles in California. Transp. Res. F: Traffic Psychol. Behav. 60, 712–722 (2019). https://doi.org/10.1016/j.trf.2018.11.010
Gurumurthy, K.M., Kockelman, K.M.: Modeling Americans’ autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices. Technol. Forecast. Social Change, 150(November 2019), 119792 (2020). https://doi.org/10.1016/j.techfore.2019.119792
Haghzare, S., Campos, J.L., Bak, K., Mihailidis, A.: Older adults’ acceptance of fully automated vehicles: Effects of exposure, driving style, age, and driving conditions. Accid. Anal. Prev. 150, 105919 (2021). https://doi.org/10.1016/j.aap.2020.105919
Jian, J.-Y., Bisantz, A.M., Drury, C.G.: Foundations for an empirically determined scale of trust in automated systems. Int. J. Cogn. Ergon. 4(1), 53–71 (2000). https://doi.org/10.1207/S15327566IJCE0401_04
Lee, J.D., Liu, S.Y., Domeyer, J., DinparastDjadid, A.: Assessing drivers’ trust of automated vehicle driving styles with a two-part mixed model of intervention tendency and magnitude. Hum. Factors 63(2), 197–209 (2021). https://doi.org/10.1177/0018720819880363
Ma, Z., Zhang, Y.: Drivers trust, acceptance, and takeover behaviors in fully automated vehicles: effects of automated driving styles and driver’s driving styles. Accid. Anal. Prev. 159, 106238 (2021). https://doi.org/10.1016/j.aap.2021.106238
Molnar, L.J., Ryan, L.H., Pradhan, A.K., Eby, D.W., St. Louis, R.M., Zakrajsek, J.S.: Understanding trust and acceptance of automated vehicles: an exploratory simulator study of transfer of control between automated and manual driving. Transp. Res. F: Traffic Psychol. Behav. 58, 319–328 (2018). https://doi.org/10.1016/j.trf.2018.06.004
Poó, F.M., Ledesma, R.D.: A Study on the relationship between personality and driving styles. Traffic Inj. Prev. 14(4), 346–352 (2013). https://doi.org/10.1080/15389588.2012.717729
Price, M.A., Venkatraman, V., Gibson, M., Lee, J., Mutlu, B.: April 5). Psychophys. Trust Veh. Contr. Alg. (2016). https://doi.org/10.4271/2016-01-0144
Rahimi, A., Azimi, G., Asgari, H., Jin, X.: Adoption and willingness to pay for autonomous vehicles: Attitudes and latent classes. Transp. Res. Part D: Transp. Environ. 89(November), 102611 (2020). https://doi.org/10.1016/j.trd.2020.102611
Sagberg, F., Selpi, Piccinini, G.F., Engström, J.: A review of research on driving styles and road safety. Human Factors: J. Human Factors Ergonom. Society 57(7), 1248–1275 (2015). https://doi.org/10.1177/0018720815591313
Van Der Laan, J.D., Heino, A., De Waard, D.: A simple procedure for the assessment of acceptance of advanced transport telematics. Transp. Res. Part C: Emerg. Technol. 5(1), 1 (1997). https://doi.org/10.1016/S0968-090X(96)00025-3
van Huysduynen, H.H., Terken, J., Martens, J.-B., Eggen, B.: Measuring driving styles. In: Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, pp. 257–264 (2015). https://doi.org/10.1145/2799250.2799266
Wang, X., Wong, Y.D., Li, K.X., Yuen, K.F.: This is not me! technology-identity concerns in consumers’ acceptance of autonomous vehicle technology. Transp. Res. F: Traffic Psychol. Behav. 74, 345–360 (2020). https://doi.org/10.1016/j.trf.2020.06.005
Wang, Y., Qu, W., Ge, Y., Sun, X., Zhang, K.: Effect of personality traits on driving style: psychometric adaption of the multidimensional driving style inventory in a Chinese sample. PLoS ONE 13(9), e0202126 (2018). https://doi.org/10.1371/journal.pone.0202126
Zhang, T., Tao, D., Qu, X., Zhang, X., Lin, R., Zhang, W.: The roles of initial trust and perceived risk in public’s acceptance of automated vehicles. Transp. Res. Part C: Emerg. Technol. 98(December 2018), 207–220 (2019). https://doi.org/10.1016/j.trc.2018.11.018
Acknowledgement
This study was supported by Changan Automobile Co., Ltd and the National Natural Science Foundation of China (72192824, and 71942005). We would like to show our thanks to Changan Automobile for providing the experimental site and equipment, as well as for providing us with great help in the recruitment of participants.
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Zhang, Q., Wang, Y., He, G., Pongrac, D., Cheng, Z., Ma, L. (2023). Do Drivers Vary in Preferences for Automated Driving Styles Across Different Scenarios? Evidence from a Simulation Experiment. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2023. Lecture Notes in Computer Science, vol 14049. Springer, Cham. https://doi.org/10.1007/978-3-031-35908-8_6
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