# Towards Understanding Driver Acceptance of C-ITS Services--A Multi-Use Case Field Study Approach
## 4 Discussion
### Attention and Distraction  
The field studies also examined _attention_ to and _distraction_ from C-ITS in-vehicle information. Eye movement assessments were conducted on 10 truck drivers and 8 car drivers during their test drives. For truck drivers, fixation durations ranged from a minimum of 66 milliseconds to a maximum of 1.56 s, with an average of 468 milliseconds. In contrast,  
Figure 16: Results of the willingness to pay feedback. car drivers exhibited significantly longer fixation durations, with a minimum of 2.2 s, an average of 7.45 s, and a maximum of 19.95 s. These findings indicate that car drivers spend more time looking at their smartphones than truck drivers. A possible explanation is that truck drivers only needed to focus on two types of information, while car drivers had to process four types. Additionally, in the ASFINAG study also 25% of the drivers were young and inexperienced drivers. Fixation-based parameters indicate that both truck and car drivers fixated (i.e., looked for more than 100 milliseconds) on the tablet or smartphone. These values strongly suggest that the signs attract the attention of both groups. This finding was further supported by post-test drive interviews, where 7 out of 8 car drivers agreed that the in-vehicle information did not distract them from driving. Finally, as shown in Figure 17, only around 20% of the participants of the online questionnaires agreed that C-ITS services would distract them from driving. Additionally, heat maps of truck and car drivers' gaze points and fixations were generated as part of the analysis. The heat maps confirm that drivers primarily focus on the vehicles in front of them. This further supports the conclusion that in-vehicle information does not distract drivers from the road. IVIS aims to serve as helpful advisors for navigation-specific information; however, they risk distracting the driver with excessive information. One approach to mitigating this issue is to share information during low-workload situations, such as at traffic lights or when the driver's workload can be directly estimated using user context information (through additional sensors). Another strategy would be to generally reduce the amount of information provided. Recommender systems, for instance, could achieve this through personalization and context adaptivity [37]. To limit distraction, it has been found that voice-based interactions with IVIS may reduce driver distraction compared to visual interfaces. Screen-based interaction requires the driver to divert their eyes and attention from the road to the screen [36]. Navigation system designers must consider not only the challenges of distraction and excessive cognitive workload [35] but also additional factors such as routing efficiency and its impact on safety and comfort. Findings suggest that these aspects may be of greater concern to drivers than distraction alone [35]. IVIS has the potential to elevate cognitive workload, which may consequently result in riskier driving behaviour [39]. While IVIS  
Figure 17: Results of online questionnaires in terms of distraction. can improve driver awareness, poorly designed auditory alerts may increase cognitive workload and cause attentional narrowing, impacting driving performance [39]. Research has shown that in tests where IVI was displayed within the central line of sight, participants only needed to briefly glance at the mobile phone display. This task was easy for participants, as they did not have to spend extended periods looking at the display to perceive symbols or information. Visual attention does not necessarily require individuals to directly fixate on a target--this ability, known as covert attention, allows individuals to focus on an object within their visual field without making eye movements. Both field studies confirmed this effect, particularly among experts. Similarly, [PERSON], [PERSON] suggests that this ability can improve with experience, such as through familiarity with GPS or traffic navigation apps [31].