Implementation of Driver Drowsiness Detection and Accident Avoidance in Vehicles- A Review | Abstract

ISSN ONLINE(2320-9801) PRINT (2320-9798)

Research Article Open Access

Implementation of Driver Drowsiness Detection and Accident Avoidance in Vehicles- A Review

Abstract

Drivers when driving long distances without regular breaks run a high risk of becoming drowsy, a state where even the experts fail to recognize it early enough. Survey tells that around one quarter of all serious motorway accidents occur due to sleepy drivers in need of a rest (drowsiness) which causes more road accidents than drinkdriving. Attention assist can warn of inattentiveness and drowsiness in an extended speed range and notify drivers of their current state of fatigue and the driving time since the last break, offers adjustable sensitivity and, if a warning is emitted, indicates nearby service areas in the COMAND navigation system. A low cost system is developed which provides solution to the existing automotive control issues. This system has two main principle components namely Vehicle to Vehicle Collision Avoidance Unit (VVCAU) is used to avoid crashing between vehicles and Black Box (BB) records the relevant details about a vehicle such as Engine Temperature, Distance from obstacle, Speed of vehicle, Brake status, CO2 Content, Alcohol content, Accident Direction, trip Time and Date. There are several works regarding pre-crash detection & avoidance system from obstacle at present. To priorities crash with human or animals compared to obstacles is lacking. Human lives can be saved from an accident by detecting an accident before it occurs. To solve this problem in this work we need advance accurate human or animal detection and also accident detection capabilities and then priorities human or animal first to obstacles. Car will avoid human or animal first then if possible it will try to avoid obstacles also. The system has accident detection technique with pin point location tracking using GSM if the system is unable to avoid accident

Dimpu Sagar N, Neelu L

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