# Modeling User Acceptance of In-Vehicle Applications for Safer Road Environment
## 2 Related Works
### Unified Theory of Acceptance and Use of Technology (UTAUT)  
The UTAUT model was created primarily to explain technology acceptance. The model integrates 32 constructs in accordance with eight well-known adoption theories, including the Theory of Reasoned Action (TRA), the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), the combined form of the TAM and TPB (C-TAM-TPB), the Model of PC Utilization (MPCU), the Innovation Diffusion Theory (IDT), the Motivational Model (MM) and the Social Cognitive Theory (SCT) [14]. The model highlighted that the actual behavior is highly influenced by user intentions. If a user has a positive intention toward a technology, the user will eventually use or adopt the technology [4; 23; 24]. The core constructs are performance expectancy, effort expectancy, social influence, facilitating conditions and motivational controls. Users are assumed to have control of their behavior and decisions over the use of technologies [20]. The research on in-vehicle applications that applied the UTAUT includes [20; 25; 26]. Moreover, in-vehicle applications can be grouped based on the three driving automation standards described by the Society of Automotive Engineers (SAE), the NHTSA in the U.S. and the BASt in Germany [27], as in Table 3. The three main challenges for in-vehicle applications are the user acceptance, safety and security and the development time and cost. In this study, we focused on in-vehicle applications that support driver's driving experience, i.e., level 0 to level 2 to address the user acceptance. Recognizing drivers' expectations and acceptability of in-vehicle applications would thus help to pave the path for future development, allowing elements that influence drivers' acceptance or rejection of the technology to be addressed. A driver's decision or performance on the road may be influenced by the use of in-vehicle applications [21]. A quantitative study was conducted in Czech Republic to investigate the influence of subjective factors, including the feeling of increased safety, ease of use, increased comfort, trust in the system, previous experience with the system and other aspects such as price, good references, system reliability and functions of the driver-assistance systems [28]. A similar study among Finnish people is presented by [29]. Both studies did not provide any theoretical models for the research design. We believe that applying a theoretical model is necessary to limit the scope of our study. Even though existing models and frameworks may be considered to explain the drivers' adoption and introduce factors that may affect the drivers' acceptance, these available models and frameworks were not specifically developed to address in-vehicle applications. Previous research by [20] compared the TAM, TPB and UTAUT to assess the validity of these theories in modeling the user acceptance of in-vehicle applications, i.e., a fatigue monitoring system or an adaptive cruise control system combined with a lane-keeping system among users in Boston, MA. The authors concluded that, among the three models, the original TAM performance is the best. Moreover, a few studies apply the TAM to investigate user technology acceptance factors [30], demonstrating that this model can be used to investigate in-vehicle technology adoption. Because the applications are pre-installed in manufactured vehicles, assessing whether drivers accept the applications or not is a relatively new research area [1; 31]. In addition, these studies use a few extra study-specific elements (e.g., trust) to better understand the adoption process [30] and investigate public opinion and the willingness to use in-vehicle applications. There are also studies which are limited to a specific age group or criteria [32]. In this study, our respondents are not focused on driver characteristics. Instead, users from various sociodemographic characteristics were included in this study.