# HMD-Based VR Tool for Traffic Psychological Examination: Conceptualization and Design Proposition
## 2 Cognitive Measures Crucial for Driving
### Drivers Measures Using Eye-Tracking  
Testing complex constructs such as SA is hard for implementation and there is no simple method to study individual SA abilities during a traditional driving assessment. Standard methods (such as [PERSON]'s ATAVT) do not correspond to the definition of SA as a dynamic process changing with time. Other SA measurement methods like the Situation Present Assessment Method [66] or the Situation Awareness Global Assessment Technique [53] might be potentially used in virtual environments, but due to the continuous development within technology, now the driver's level of SA can be researched with the precise eye movements analysis. Eye-tracking, a technology for capturing and recording eye movements [67], is currently compatible with HMD-based virtual technologies and even relatively sophisticated and precise eye-trackers are already embedded in commercially available HMDs (e.g., HTC VIVE pro eye with Tobii ET). Eye-tracking technology can help capture important measures, which are barely measurable by standard TPE [50]. The human sensorimotor activity including pupillometry, blink rates or fixations on specific objects in the environment (areas of interest) were within the ranges found in previous studies, that reliably indicate different states of a driver's arousal, fatigue, deception, attention change or loss, hazard perception or complete loss of control [68; 69; 70; 71]. The eye-tracking technology was also proved to have the capacity to predict neurocognitive illnesses [72], which might speed up the decline of driving skills and hence it may promote prevention in road safety. Based on sensorimotor activity, several cognitive and emotional phenomena can be induced. Eye fixation on relevant objects in the visual field was found to be related to driver's situation awareness [69; 70]. The way drivers look differs according to their experience--experienced drivers fixate more on higher positions and for a shorter time than the more inexperienced drivers [73]. Additionally, older drivers focus their attention on potential hazards around them, while younger drivers are focused on other vehicles [68]. Usage of eye trackers in virtual reality has an advantage to its usage compared to real traffic, because in a real environment there might be problems with uncontrollable visual noise [74; 75], which affects perception and subsequently other cognitive processes. Situational awareness is a complex construct where the majority of measured cognitive functions are involved, applied and demonstrated. Researchers should acknowledge that SA is influenced by the driver's working memory capacity [76], divided attention capacity [77], spatial perceptual ability, fatigue [52], emotional state [78], level of understanding of the car's driving system [79], monotonous task [80], conversation [81; 82], hearing cell phone notifications [83], parallel driving of more vehicles in the virtual environment [84], complexity of the driving interface [85], integration of ear cons to the virtual environment [86] and availability of vestibular or somatosensory feedback [87]. Additionally, situation awareness might increase after seeing a hazardous event [88]. SA in virtual environments is also better when subjects have a lot of experience with 3D computer games [89; 90] and might be dependent on cultural differences in cognition like Western analytical and Eastern holistic thinking [57]. With the use of the combination of VR and ET, SA might be measured as the number of eye collisions with other objects in the visual field [91] or differences between real positions of objects and places where subjects think these objects are on the map [92]. However, measurement of situation awareness with eye tracking is criticized for being unable to judge how a subject evaluates information [93]. This objection can be partially resolved by using various logging systems to obtain data triangulation [47].