Drunk Driving

Drunk driving, or officially driving under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. A report of Ministry of Road Transport & Highways, Government of India says during the year 2011, there were around 4.98 lakh road accidents, which killed 1.42 lakh people and injured more than 5 lakh persons, many of them are disabled for rest of their lives. Crashes due to drunk driving are serious danger not only to the drivers themselves but also to the public present on the road. Drivers under the influence of alcohol show a marked decline of perception, recognition, and controlling of vehicle, so they tend to make certain types of dangerous moves. We propose a highly efficient system aimed at early detection

and to cooperatively pass their data through the network to main location. the more modern networks are bidirectional, also enabling control of sensor activity.

WSN technology can also applied to create a new concept and wide development for smart vehicle to provide intelligence, comfort, and security and to improve the performance of driver.

Here, three-axis accelerometers are used to measure the acceleration variation of vehicle body in X ,Y and Z-axis. The presented system detects the dangerous driving behavior presented in this paper are from the recognition of driving states. Current driving states including lane-departure, turning, acceleration, braking, and bumping are derived from the measurements.

The researchers have found that there are some patterns of driving behaviors for these drivers who are under influence of alcohol. Based on this research we can conclude that there are some categories related to drunken driving behaviors. All these driving behaviors are related to the vehicle movement. Also depends on the driver’s vigilance & judgment. The hints to solve this problem can be classified as

STUDIES AND FINDINGS

Some researches have already done in the field of driving monitoring tools. Some of them are knows as driver vigilance monitoring. It works on detecting and preventing fatigue of the driver. Other researchers focus on real-time driving pattern recognition. In detail, they worked with various methodologies and techniques mentioned as follows.

These methods all required one or more cameras to be installed in the vehicle and just in front of the driver. It will cause some potential safety issues to the driver. Besides visual methods, the interaction at the vehicle-human interface also gives clues to driving information monitoring. It is assumed that the time derivative of force exerted by the driver at the vehicle-human interface, such as pressure on the accelerator pedal, can help to decide the level of alertness of the driver. Practically, a force sensor on the accelerator pedal to capture the exerted force to predict driver fatigue used [6]. Saab, automobile manufacturer has designed an experimental product AlcoKey, which used the breath sample of drivers. It collects the breath sample before they start the vehicle. Then the AlcoKey's radio transmitter sends a signal to the vehicle's electronic control unit. Now the control unit will decide wither the vehicle to be started or not based on the level of alcohol present in the breath sample. These researches worked based on the interactions between human and vehicle to determine drunk driving. It also