Research On Interface Optimization Design Of Vehicle Head-up-display System

Augmented Reality Head-up Display integrates augmented reality technology and head up display technology into the vehicle information system.The system superimposes various driving related information into the driver’s driving field of vision through projection,improves the driver’s perception efficiency of the driving surrounding environment through various prompt information,reduces the time for the driver to look down at various information panels,and improves the driving safety.At the same time,due to the complex and changeable driving environment,the amount of information displayed by on-board AR-HUD in different situations also changes.When the amount of information displayed is too large,it is easy to lead to cognitive overload of drivers and reduce their judgment and response efficiency to the dangerous environment.Therefore,it is of great significance to study how to prevent the overload of interface information of on-board AR-HUD driving aid system,effectively manage the information displayed on the interface in complex situations,improve driving safety and the development of on-board AR-HUD driving aid system.Through the research on the development status of AR-HUD and the cognitive load of digital interface,it is found that the driver’s visual cognitive resources are limited in the process of driving.Due to the complex and changeable driving environment,the information display of on-board AR-HUD interface is also different.There will be too much information on the interface,and the classification of prompt information is not clear,which may cause cognitive overload and reduce the judgment efficiency of drivers,thus affecting the driving safety.This paper constructs a cognitive load model of vehicle AR-HUD interface from the perspective of limited attention cognitive resources and working memory cognitive capacity.Through the deconstruction and analysis of the information classification,priority,content and layout of the interface,the design optimization of vehicle ARinterface is completed according to the principle of information weight classification and the principle of information interface quantity.Based on eye tracking technology,the cognitive load evaluation model and information processing evaluation model of vehicle AR-HUD interactive interface are introduced.Through the cognitive performance evaluation experiment between the optimized interface and the existing interface,eye tracking experiment and dangerous situation response experiment,it is concluded that the optimized interface has better driver cognitive performance and can significantly reduce the driver’s awareness of dangerous driving The perception time of the situation is shorter,and the response to the dangerous situation is faster.The innovation of this research is to optimize and evaluate the design of on-board AR-HUD interface from the perspective of managing the information content of on-board AR-HUD interface in complex situations and proposing the evaluation system of on-board AR-HUD based on eye movement tracking,so as to improve the driving safety and solve the cognitive problems caused by the complex information classification and uneven information content of on-board AR-HUD assistant driving system.It provides a new idea for the design and optimization of AR-HUD assistant driving system.