# Towards Understanding Driver Acceptance of C-ITS Services--A Multi-Use Case Field Study Approach
## 2 Methodology
### Literature Research  
The results of the test drives and the online questionnaire in the presented field studies are combined with results from the literature to form an overall picture of user acceptance of C-ITS services, as illustrated in Figure 1. The literature review is an important component \begin{table}
\begin{tabular}{c c} \hline \hline
**Before Test Drive** & **After Test Drive** \\ \hline Demographic data (EV) & - \\ Profile (EV) & - \\ Accidents (EV) & - \\ Previous Knowledge (EV) & - \\ Desired Driving Information (EV, BI) & Traffic sign recognition of C-ITS services (E) \\ C-ITS Services (U, BI) & C-ITS services (U, BI) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Interview, key aspects evaluated before and after test drive. Figure 3: Test drivers. as it provides a comprehensive overview of existing studies and findings relevant to the research topic of the paper. This section forms the basis for further analysis and discussion of the results of the field-level studies in Section 4. The structured literature analysis was conducted to find out about users' trust in traffic information through various information channels, user acceptance of in-vehicle traffic information, and compliance with traffic regulations and instructions. For this purpose, the four-phase model from the \"PRISMA Statement\" by [PERSON] et al. was chosen. The model suggests structuring the information flow within an identification, screening, selection, and inclusion phase to improve the reporting of systematic reviews [27]. For the literature, the following databases were used: ACM, EBSCO, IEEE, Scopus, Springer Link, and Wiley. The titles of the search were downloaded on 21 August 2024, and the review was conducted between September 2024 and March 2025. To structure the search for appropriate literature, three main categories were defined: In-Vehicle Information, Technology Acceptance, Compliance, Trust, and Transportation Context. These categories were selected to capture different aspects of in-vehicle information systems, their acceptance by drivers, and their impact on behaviour and road safety (see Table 5). In Table 6, the corresponding keywords are presented that were used to create various search strings. The key challenge in creating the search strings was the limited number of papers specifically addressing driver acceptance of in-vehicle information provided by C-ITS services. In contrast, broader topics such as user acceptance or in-vehicle information alone yielded an overwhelming volume of literature. Consequently, to systematically analyse the literature, Boolean operators were used to combine these categories, specifically the AND operator and within the category to link the keywords, the OR operator. This ensures that the review focuses on studies that examine the relationships between these aspects rather than considering them in isolation. In Table 6, the keywords corresponding to the categories can be found. After defining the search string, a total of 426 studies were retrieved. Following the removal of duplicates (27 papers), a stepwise screening process, starting with titles, followed by abstracts, was conducted. During this process, 273 studies were excluded due to irrelevance, and 2 due to unavailability. As a result, 32 papers remained and underwent a full-text analysis. Six of these studies were excluded because they lacked contextual connections to the research topic. Ultimately, 26 studies were identified as relevant for further thematic analysis. The process is illustrated in Figure 4.