Effects of Audio-visual Warning Patterns on Identification Responses of Drivers Under Noisy Environments
To investigate the impact of different audio-visual warning patterns in vehicle-mounted intelligent early warning systems on driver recognition response in hazardous driving scenarios,this study conducted audio-visual bimodal warning experiments using a driving simulator platform,focusing on assessing the effectiveness of different audio-visual warning patterns under varying noise environments.The experimental design incorporated three factors:two noise environments(high and low)crossed with three visual warning patterns(0,1,2 Hz flashing)and three auditory warning patterns(non-speech,male speech,and female speech).Participants'performance data and subjective evaluation scores were collected,and a significance analysis was conducted to evaluate the effects.The results indicate that 1 Hz and 2 Hz flashing are more aligned with drivers'cognitive states and more acceptable than 0 Hz no flashing,with 1 Hz flashing significantly reducing reaction time.Male and female voice alarms are easier to understand and accept than non-verbal alarms,significantly decreasing recognition reaction time and improving accuracy.In high-noise environments,drivers'comprehension of alarm information decreases significantly compared to low-noise environments.Across both high and low noise environments,the"flashing-voice"warning pattern yields the best warning effect,with"1 Hz flashing-male voice"achieving superior recognition performance,the highest perceptual matching,and comfort scores among the tested"visual-audible"warning patterns.
intelligent transportationaudio-visual warning patternsmulti-factor ANOVAidentification responses of driversnoisy environmentwarning effects
万方数据
维普
