AR HUD Interface Optimization Model for Balancing Driver's Visual Sensitivity and Fatigue

With the wide application of intelligent driving assistance system, the augmented reality head-up display (AR HUD) interface plays an increasingly important role in drivers' real-time perception of traffic environment. As the AR HUD is vulnerable to be affected by changed ambient light, it weakens the legibility of the virtual interface and driver's visual comfort to a certain extent. The content color, as one of interface visual design elements, directly affects the performance of driver, which include the visual sensitivity and fatigue and further influences the vehicle safety. The selection between luminance contrast (affects sensitive and number of applicable environments) and driver performance (affects fatigue) are contradictory issues. In order to solve this contradictory problem in the design of AR HUD interface, and balance the cognitive load and situation awareness of driver, an extended analysis and optimization method of interface element was proposed. This method quantifies the discrete interface elements and makes the opposition problem consistent. The content color selection models under two conditions are constructed, which describe the distance from the chosen color to the optimal interval. It has been proved to be effective in finding the best answer for driver performance in interface design. Other interface elements in AR HUD can also be further optimized based on this method.