Wakeup: Designing Multimodal Alerts for Drowsy Drivers with SmartPhones

This paper aims to improve warning signals of the existing drowsiness detection systems in terms of efficiency and effectiveness. For this purpose, firstly, we exploit visual, audio and tactile modalities to discover the most suitable signal for alerting the car drivers in drowsiness detection systems. Secondly, the resultant signals are merged into various combinations to form multimodal warnings. From this, we got four different combinations. Furthermore, we have done an experimental evaluation in order to identify the most effective and efficient multimodal warnings for drowsiness detection systems. Results from our observational studies showed that the most suitable unimodal signals are as follows: (1) 40 ms on and 50 ms off the flashlight of smartphone for visual warning, (2) Apple iOS Ringtones-Alarm for the audio warning, and (3) 1 pulse in a second with 500 ms inter-stimulus interval for the vibrotactile warning. From the experimental study, we found that the most efficient and preferable warning for alerting the drowsy driver is multimodal signal consisting of visual, audio, and tactile modalities. This paper is helpful for the car industries to develop the effective warnings of drowsiness detection systems, furthermore, it helps in adopting these systems and in preventing accidents.