# Can ADAS Distract Driver's Attention? An RGB-D Camera and Deep Learning-Based Analysis
## 2 Materials and Methods  
The driving simulator used in this study (Figure 1) is property of the _iDrive_ laboratory of Polytechnic University of Milan and is composed by the following elements: a steering wheel with force feedback, gear shifter with automatic transmission, gas and brake pedals, and adjustable driving seat. Furthermore, three 32\" size monitors display the driving scene; their pixel resolution is 1920 \(\times\) 1080, 36 degrees of vertical field of view (FoV) and 165 degrees of horizontal FoV. Vibrations and force feedbacks are provided on the steering wheel to improve the realism of the user experience. Unity game engine has been used to build the virtual driving environment and to interface between vehicle controls and multi-modality displays (visual, auditory, and haptic feedback) in simulator system. Data are recorded 10 times per second. The Intel RealSense SR300 camera has been used to record drivers' facial expressions during their driving experiences. This device is an RGB-D camera, which allows to retrieve both the color (RGB) and the depth (D) information about a scene. The camera recorded at 30 FPS with a 640 \(\times\) 480 resolution (Figure 2). Eleven participants among men and women between the ages of 22 and 45 joined the experiment. They held a driver's license and at least 3 years of driving experience. The designed experiment consists of three driving experiences (Figure 3), each of them lasting three minutes: the first one is the training phase, whilst the other two experiences are the testing phase. Figure 1: View of the iDrive driving simulator. Figure 2: Intel RealSense SR300. During the training phase the driver is asked to drive on a traffic-free highway. This step is mandatory to become familiar with the highway layout and to improve the sensitivity in being responsive to the pedals and to the wheel feedback. The aim is to minimize the learning effect during the testing phase [27] and the emotional response to other elements not belonging to the experiment [28]. During the second and the third driving experiences, the driver is asked to drive on the same highway in moderate traffic conditions. The scenarios have been specifically designed to have a particularly arduous driving experience, through the implementation of a dynamic and unpredictable behavior of other vehicles, such as sudden lane change and screeching halt; hence, the drivers drove in a context where the number of hazards was well above average. In both the scenarios the following ADAS are activated: the speed warning, above 130 km/h and the forward collision warning [29], with two time-to-collision thresholds: 4 s (preliminary alert) and 2 s (possible collision). The difference between the two scenarios is that in one of them the feedback provided by the ADAS is haptic, whilst in the other the feedback is by auditory. A Latin square design has been used for the testing phase to minimize sequencing effects. An FER analysis has been carried out to monitor driver's mood during the whole experiment. As mentioned in the previous Section, in order to identify the concentration through a FER methodology, some works ([22; 26]) suggest to identify the neutral expression. Furthermore, the present work also considered the assumption that emotion detection can reveal driver's distraction with particular criticality in the presence of anger, sadness, and emotional agitation, as stated by [PERSON] et al. [30] in their work about crash risk factors, and, on the contrary, the concentration can be associated with the neutral expression. Furthermore, in regard to the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS), the crash dataset used in that work is highly significative for our experiment for a twofold reason. Firstly, all the stated considerations arise from observations in a naturalistic context, providing a solid foundation for the evaluation of drivers' emotions; secondly, the scenario referred to in the SHRP 2 NDS is the highway, which is the same environment designed for our experiment.