Introduction
The rapid development of Connected, Cooperative, and Automated Mobility (CCAM) systems is reshaping the future of urban transportation. These innovations aim to improve transport efficiency, enhance road safety, and reduce environmental impact through advancements in automation, digitalization, and vehicle connectivity. CCAM is designed to benefit all user groups, particularly individuals facing mobility challenges, such as those with physical or cognitive impairments.
However, the successful implementation of CCAM depends heavily on public acceptance—a factor that remains a significant barrier. Research in indicates that certain populations, including residents of rural areas, older adults, individuals with mobility impairments, and those with limited digital literacy, often exhibit resistance toward these types of emerging technologies. Therefore, understanding the psychosocial factors underlying this reluctance is essential to foster inclusive and equitable adoption of CCAM systems.
Purpose and methods
Grounded in the Theory of Planned Behavior, the study examined how users' characteristics (i.e., increasing age, mobility impairment, low-tech savviness, rural living), personality traits (i.e., propensity to trust), and psychosocial factors (attitudes, subjective norms and perceived behavioral control) affect the intention to use CCAM. An online survey was developed as part of the EU project SINFONICA, and a sample of 4,331 individuals from different European countries completed the questionnaire.
Results
The results confirm the role of the variables in predicting the intention to use CCAM. Remarkably, propensity to trust emerged as a critical mediator, exerting substantial effects on the TPB dimensions, which in turn influenced the intention to use CCAM. Interesting effects emerged in relation to the users' characteristics.
Conclusions
The results highlight that to fully realize the benefits of CCAM public transport systems, it is essential to understand the psychosocial needs of potential users. This understanding can support more inclusive and effective strategies to foster acceptance and adoption of CCAM technologies.