Drowsy Driver Detection System Using Matlab Code

Drowsy Driver Detection System Using Matlab Code




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Drowsy Driver Detection System Using Matlab Code


perclos is a measure of drowsiness that is defined as the proportion of time in a minute that eyes are at least 80 percent closed 33 . for higher perclos values, where the eyes are mostly closed for longer periods of time than for lower perclos values, subjects exhibit strong correlation with a common sign of drowsiness in driving which is lane deviation in the road 33, 40 . to calculate this measure, a one-minute sliding window with a 30 seconds overlap between every two consecutive windows has been applied to the eyelid signal. the perclos of four different driving modes of the same driver is shown in figure 3. in this figure, perclos increases up to 0.9 in the fatigued-automated test and goes up to 1 (completely closed) in the fatigued-manual test. this range of perclos suggests that the driver is extremely drowsy in the fatigued mode tests while perclos is barely higher than 0.3 in the rested tests.

introduction:car accident is the major cause of death in which around 1.3 million people die every year. majority of these accidents are caused because of distraction or the drowsiness of driver. construction of high-speed highway roads had diminished the margin of error for the driver. the countless number of people drives for long distance every day and night on the highway. lack of sleep or distractions like the phone call, talking with the passenger, etc may lead to an accident. to prevent such accidents we propose a system which alerts the driver if the driver gets distracted or feels drowsy. facial landmarks detection is used with help of image processing of images of the face captured using the camera, for detection of distraction or drowsiness. this whole system is deployed on portable hardware which can be easily installed in the car for use.




once the drowsiness is detected the system checks if the blink rate has crossed 16 blinks per minute. if it has crossed the limit the ir sensor will be turned off and the motor speed will be reduced. the system will monitor the driver for a certain period of time and check if the driver’s head is constantly moving. if yes the system will alarm the driver. face detection algorithm is used to find the driver’s face in the driver’s profile. for this the driver’s face is detected first. the face location in the driver’s profile is stored in a database. once a new driver’s face is detected, the face tracker is used to find the location of the face. the system compares the location of the current driver with the database. if the location is not found it draws the conclusion that the driver is falling asleep. this paper presents a prototype to detect fatigue in drivers and helps in avoiding accidents. one of the reasons that accidents occur commonly is due to sleepiness during driving. this sleepiness or fatigue results in 30 to 40 % accident that usually occurs. it is estimated that the probability of meeting with an accident increases four to six times when the driver feels drowsy. detection of fatigue is important to avoid accidents and thereby saving many lives everyday. this paper proposes a better fatigue or drowsiness detection system to that of existing system today. this method of drowsiness involves a minimum intrusive method of detection. hence, the driver would experiences very less inconvenience. once the detection is completed this prototype also alerts the driver, regulates the speed of the vehicle if fatigue is detected. thus, avoiding the accidents due to fatigue and saving many lives. 5ec8ef588b


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