This paper presents a methodology and mobile application for driver monitoring, analysis, and recommendations based on detected unsafe driving behavior for accident prevention using a personal smartphone. For the driver behavior monitoring, the smartphone’s cameras and built-in sensors (accelerometer, gyroscope, GPS, and microphone) are used. A developed methodology includes dangerous state classification, dangerous state detection, and a reference model. The methodology supports the following driver’s online dangerous states: distraction and drowsiness as well as an offline dangerous state related to a high pulse rate. We implemented the system for Android smartphones and evaluated it with ten volunteers.
Methodology and Mobile Application for Driver Behavior Analysis and Accident Prevention
IEEE Transactions on Intelligent Transportation Systems ; 21 , 6 ; 2427-2436
2020-06-01
3431264 byte
Article (Journal)
Electronic Resource
English
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