VEHand: an in-vehicle information system to improve driving performance in an unfamiliar traffic regulation

Driving under unfamiliar traffic regulations (UFTR) is associated with an increased number of traffic accidents. To drive safely in such conditions, drivers need to adapt their prior knowledge to a new driving situation. This ability is called cognitive flexibility (CF). CF is influenced by the degree of handedness of the performer. The goal of this research was to develop a driving-assistance system that adapts the information it provides based on the handedness degree of drivers under UFTR. Two empirical studies were conducted in a driving simulator. The results of the first study indicated that left/mixed-handed drivers made significantly fewer errors that could be attributed to CF impairment than did strong right-handed drivers. Accordingly, we developed a driving-assistance system ('VEHand'), which provides drivers with useful feedback based on their handedness degree. The results of the second study indicated that VEHand significantly assisted strong-right handed drivers to correctly enter roundabouts and intersections.