A TAM-Based Comparative Analysis of Autonomous Public Transportation Use Intentions Among the Elderly in Chongqing

Objective: This study compares and analyzes the acceptance intentions of elderly people in Chongqing toward autonomous buses and autonomous taxis, based on the Technology Acceptance Model (TAM).<br/>Background: With the expansion of Mobility as a Service (MaaS), autonomous public transportation has emerged as a key means to enhance the mobility and social participation of the elderly. However, differences in functional needs, digital literacy, and safety perceptions may influence their acceptance of different autonomous transportation modes.<br/>Method: Survey data were collected from 284 elderly individuals aged 65 and above in Chongqing who had actual experience with autonomous buses and robotaxis. Structural equation modeling (SEM) and one-way ANOVA were applied to examine the effects of perceived usefulness (PU), perceived ease of use (PEOU), perceived risk (PR), and social influence (SI) on behavioral intention (BI).<br/>Results: The results revealed significant differences among three user groups. The Dual-Use Group reported the highest scores for PU, PEOU, SI, and BI, indicating that diverse travel experiences enhance overall acceptance. The Bus Group showed higher perceived risk, while the Taxi Group emphasized usefulness and efficiency. Bootstrap analysis further confirmed that SI partially mediates the relationships between PU, PEOU, PR, and BI.<br/>Conclusion: The findings confirm that the TAM core pathways remain valid in explaining elderly acceptance of autonomous transportation and highlight the mediating role of social influence. Differences between service types demonstrate that specific design attributes significantly shape user acceptance.<br/>Application: This study provides practical implications for age-friendly MaaS design. Autonomous taxis should enhance accessibility through voice interfaces and telephone reservations, while autonomous buses should strengthen safety demonstrations and risk management to improve elderly users' trust and willingness to adopt autonomous transportation.