HUD Interface Design For Overall Usefulness In Semi-autonomous Driving Scenario

The full realization of autonomous driving will bring great convenience to people.However,due to the limitations of network,machine learning technology and policies,human-machine co-driving is a necessary path for the full realization of autonomous driving.In the transition process from manual driving to semi-autonomous driving,the driver gradually transitions from a single operation to both regulation and operation.In this process,the reduction of cognitive load and boredom caused by passive supervision can lead to a decrease in driver alertness,which can lead to a series of safety problems.A properly designed HUD can improve these problems.However,incorrectly designed HUDs may cause cognitive tunneling and interfere with visual search behavior,thereby increasing the risk of accidents.Thus,with this as a starting point and with the goal of improving the safety of semi-autonomous driving,this study conducted a three-part study using the principles of usefulness,utility,and usability as guidelines:HUD functional utility research: collect and organize the existing interaction information related to human-machine cooperation in commercial autonomous driving vehicles,and combine the literature research method to screen the content of practical HUD information in semi-autonomous driving situations;implement HUD for utility experimental verification based on eye-tracking,interview method and quantification of driving takeover performance,and after experimental results analysis,propose that the design of elements should be changed for HUDs with controversial utility Suggestions for changing the design of elements for HUDs with controversial utility.HUD display form usability study: The relationship between the number of HUDs and the trust level was deduced through the trust level questionnaire and the EEG test;different display forms of HUDs were designed with reference to existing commercial vehicles and expert opinions;quantitative usability data of different display forms of HUDs were obtained through eye gaze distribution quantification,driver takeover performance test,automated mode perception capability measurement and situational awareness capability measurement.HUD design element selection and interface solution demonstration based on overall usefulness: Based on the above-mentioned HUD utility and usability study,we use AHP to rank and select HUD design elements for two types of experienced drivers and two types of traffic flow driving environments,and demonstrate a new HUD interface solution based on HUD design element selection.The study provides a preliminary basis and guidance for information selection and display form design for HUD interface design in semi-autonomous driving situations,which has practical application value for promoting human-autonomous vehicle communication,improving driving safety and enhancing interaction experience.