Journal of Transportation Research

Journal of Transportation Research

Prediction of Drivers' Attitudes towards Autonomous Vehicles Based on Personality Using Structural Equations

Document Type : Original Article

Authors
1 Professor, Department of Transportation Planning, Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran.
2 Associate Professor, Department of Transportation Planning, Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran.
3 Ph.D. Student, Department of Transportation Planning, Faculty of Engineering, Imam Khomeini International University, Qazvin, Iran.
Abstract
Autonomous vehicles promise a significant potential to maintain the mobility of various individuals even as their driving abilities decline. However, attitudes can act as a significant barrier to their acceptance, as shown for other technologies. This study examined how personality traits predict attitudes in a sample of 108 individuals aged 18 to 72. 21 personality questions identified introversion and extroversion, and 15 attitude questionnaire items were identified. Concerns about autonomous vehicles, eagerness to adopt autonomous vehicles, and willingness to relinquish driving control were assessed. Structural equation modeling shows that lack of concern has a significant impact coefficient of 0.576 (more introverted than extroverted) on the willingness to accept technology. Also, lack of concern has a significant impact coefficient of 0.486 (more extroverted than introverted) on the willingness to relinquish driving control. The eagerness to adopt autonomous vehicles on the willingness to relinquish driving control did not show a significant difference in intensity between extroverted and introverted samples. Furthermore, the mediating role of the eagerness to adopt autonomous vehicles in the relationship between lack of concern about autonomous vehicles and the willingness to relinquish driving control was significantly greater in introverted samples than in extroverted samples. These results indicate that in order to convince consumers to accept self-driving car technology, there is a need for various information dissemination campaigns based on a precise understanding of individuals' personalities.
Keywords
Subjects

-پروین، لارنس، جان، الیور بی. (1381). شخصیت؛ نظریه و پژوهش. ترجمه محمد جعفر جوادی و پروین کدیور. تهران. نشر آییژ.
-فریدی اقدم، امین. 1402. تحلیل ارتباط پارامترهای شخصیتی و شناختی رانندگان با رفتارهای رانندگی در محیط شبیه‌ساز رانندگی با استفاده از مدل معادلات ساختاری. پایان‌نامه کارشناسی ارشد. دانشگاه بین‌المللی امام خمینی (ره).
-Aiswarya, G. S., Mariah, M., Katragadda, R., & Makam, R. (2023). Control of Self-Driving Cars using Reinforcement Learning. 2023 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 1-6.
-Charness, N., Yoon, J. S., Souders, D., Stothart, C., & Yehnert, C. (2018). Predictors of attitudes toward autonomous vehicles: The roles of age, gender, prior knowledge, and personality. Frontiers in Psychology, 9, 2589.
-Hőgye-Nagy, Á., Kovács, G., & Kurucz, G. (2022). Acceptance of Self-Driving Cars Among University Citizens: Do Attitudes or Previous Experience Matter More? SSRN Electronic Journal.
-Hőgye-Nagy, Á., Kovács, G., & Kurucz, G. (2023). Acceptance of self-driving cars among the university community: Effects of gender, previous experience, technology adoption propensity, and attitudes toward autonomous vehicles. Transportation Research Part F: Traffic Psychology and Behaviour.
-Jackson, D. L. (2003). Revisiting sample size and number of parameter estimates: Some support for the N: q hypothesis. Structural Equation Modeling, 10(1), 128-141.
-Luger-Bazinger, C., Hollauf, E.-M., Atasayar, H., Zankl, C., & Hornung-Prähauser, V. (2023). Perceptions and attitudes of bicyclists towards self-driving cars: a mixed methods approach. Frontiers in Future Transportation.
-McQuitty, S. (2004). Statistical power and structural equation models in business research. Journal of Business Research, 57(2), 175-183.
-Qu, W., Sun, H., & Ge, Y. (2020). The effects of trait anxiety and the big five personality traits on self-driving car acceptance. Transportation, 48, 2663-2679.
-Reimer, B. (2014). Driver assistance systems and the transition to automated vehicles: A path to increase older adult safety and mobility? Public Policy & Aging Report, 24(1), 27-31.
-Schoettle, B., & Sivak, M. (2014). A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia.
-Schoettle, B., & Sivak, M. (2016). Motorists’ preferences for different levels of vehicle automation: 2016. University of Michigan Sustainable Worldwide Transportation.
-Sestino, A., Peluso, A. M., Amatulli, C., & Guido, G. (2022). Let me drive you! The effect of change seeking and behavioral control in the Artificial Intelligence-based self-driving cars. Technology in Society.
-Smith, A., & Anderson, M. (2017). Automation in everyday life.
-Tenenhaus, M., Amato, S., & Esposito Vinzi, V. (2004). A global goodness-of-fit index for PLS structural equation modelling. Proceedings of the XLII SIS scientific meeting,
-Wang, Y.-M., Chiu, W. C., Wei, C. L., Wang, H. H., Yang, J. H., & Wang, Y.-S. (2024). What drives consumers' intention to purchase self‐driving cars. Managerial and Decision Economics.
-Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009).Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 177-195.