# Can ADAS Distract Driver's Attention? An RGB-D Camera and Deep Learning-Based Analysis
## 5 Conclusions  
A study to monitor driver's attention through 3D cameras has been successfully pursued. The designed experiment aimed to evaluate the presence of ADAS as a possible source of distraction for the driver using RGB-D images and FER. After a training phase necessary for the drivers to become familiar with the simulator, two driving experiences have been presented to the participants according to a Latin square design. In one of the driving experiences the feedback provided by the ADAS was haptic, whilst in the other one it was auditory. In both cases the users had to drive in a virtual scenario on a highway with moderate traffic. Users have been monitored with an Intel RealSense SR300, an RGB-Dcamera, and images have been used to identify concentration and inattention with a deep learning-based methodology to fulfill FER.  
Results highlighted that drivers have been distracted in case of events, mostly accidents, whilst ADAS did not affect their attention except from a single user in a single scenario; anyway, the linear correlation between ADAS activation and inattentive facial expression for this outlier resulted to be also weak.  
RGB-D images coupled with a deep learning-based method has proved to be an effective tool to monitor concentration without being invasive, a particularly useful advantage to preserve the experimental validity, but also for not being a disturbing element for the driver in a naturalistic environment, i.e., on a real car.  
ADAS resulted not to be correlated with facial expressions. Future works could investigate whether it is possible to establish the ADAS effectiveness, intended as how much the ADAS feedback is perceived by the user. To this aim, facial micromovements could be studied as possible indicators, possibly integrated with physiological data for increasing the sensitivity, and it should be considered to adapt the deep learning methodology to assess the temporal correlation between facial expressions in different times. Furthermore, the extension of the driving experience sessions could provide more data regarding drivers' concentration; nonetheless, such a study should take place in a naturalistic context or should require an even more complex scenario to preserve experimental validity not influencing participants' driving style due to possible recognition of patterns in the unpredictable behavior of the other vehicles.  
Conceptualization, L.U., F.M., F.N., G.C. and E.V.; methodology, L.U., F.N., F.M. and S.M.; software, L.U., F.N. and Y.S.; validation, L.U. and F.N.; formal analysis, L.U., F.N. and S.M.; investigation, L.U., S.M.; resources, G.C. and E.V.; data curation, L.U., F.N. and Y.S.; writing--original draft preparation, L.U. and F.N.; writing--review and editing, S.M., F.M. and G.C.; visualization, L.U., F.N. and Y.S.; supervision, E.V.; project administration, E.V. and G.C.; funding acquisition, E.V. and G.C. All authors have read and agreed to the published version of the manuscript. This research received no external funding.  
The study was conducted according to the guidelines of the Declaration of Helsinki.  
Informed consent was obtained from all subjects involved in the study.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the large size of the acquired dataset.  
The authors declare no conflict of interest.