Transactions on Transport Sciences X:X
Impact of Socio-demographic Factors and Public Perception towards Different Levels of Autonomous Vehicles: A Case Study of Seoul, South Korea
- a. Department of Civil Engineering, East West University, Aftabnagar, Dhaka-1212, Bangladesh
- b. Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah, United States
- c. Department of Urban Planning & Engineering, Yonsei University, Seoul, Republic of Korea, 03722
- d. Department of Civil and Environmental Engineering, Yonsei University, Seoul, Republic of Korea, 03722
- e. Department of Civil Engineering, IUBAT – International University of Business Agriculture and Technology, Uttara, Dhaka, Bangladesh
The adoption of autonomous vehicles (AVs) promises significant benefits, yet public acceptance varies across different automation levels. This study examines factors influencing public concern over using Level 3 (conditional automation), Level 4 (high automation), and Level 5 (full automation) AVs among Seoul citizens. Analyzing survey data from 209 participants with a Seemingly Unrelated Ordered Logit regression model, the study identifies key socio-demographic and perceptual factors affecting AV acceptance. Findings reveal that younger individuals (aged 20–29) are significantly less concerned about Level 5 AVs compared to older age groups, indicating age influences openness to full automation. Those with a bachelor’s degree show higher concern over Level 3 AVs but lower concern over Level 4 AVs, suggesting the education level affects perceptions differently across automation levels. Frequent drivers (30–40 hours per week) exhibit more apprehension toward Level 3 AVs, possibly due to attachment to manual driving. Concerns about system safety, security threats from hackers, and skepticism about AVs’ ability to reduce accidents or emissions significantly increase apprehension across all levels. Notably, individuals willing to pay for self-driving technology are less concerned about Level 5 AVs, reflecting that investment willingness correlates with acceptance. These findings provide valuable insights for planners and policymakers to develop targeted strategies that address specific public concerns, inform policy decisions, and promote effective adoption of AV technology.
Keywords: Autonomous Vehicles (AVs); Public Perception; Seemingly Unrelated Ordered Logit (SUOL) Regression; Socio-economic factors; Demographic factors.
Received: June 28, 2025; Revised: October 24, 2025; Accepted: December 4, 2025; Prepublished online: February 23, 2026
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