User Impressions and Using Contexts for Autonomous Shuttle Services: Analyzed by a LDA Based Topic Modelling Approach

The integration of autonomous shuttles holds promise for enhancing transportation sustainability and efficiency. While existing research predominantly employs quantitative methodologies, focusing on classical acceptance and intention-to-use models like TAM and UTAUT, this study adopts a qualitative approach. Leveraging semantic topic extraction from open-ended questions conducted among users of autonomous shuttle services in Germany, this research identifies distinct themes pertaining to general perception and real-world application contexts. Overall, respondents exhibit a favorable perception of the mobility offering, especially for short journeys within urban settings (e.g., commutes or shopping trips). However, attempts to establish empirical connections through logistic regression between these themes and quantitatively measured variables, namely, attitude towards autonomous shuttles (ATT) and behavioral intention to use them (BI), do not yield substantial evidence. This dearth of support is potentially attributed to the limited availability of qualitative data currently obtainable for the analyses. This study underscores the significance of qualitative insights in comprehending user attitudes and intentions within the realm of autonomous shuttle adoption.