AN INTELLIGENT ONLINE DRUNK DRIVING DETECTION SYSTEM BASED ON MULTI-SENSOR FUSION TECHNOLOGY

Abstract

Since drunk driving poses a significant threat to road traffic safety, there is an
increasing demand for the performance and dependability of online drunk driving detection
devices for automobiles. However, the majority of current detection devices only contain a
single sensor, resulting in a low degree of detection accuracy, erroneous judgments, and car
locking. In order to solve the problem, this study firstly designed a sensor array based on the
gas diffusion model and the characteristics of a car steering wheel. Secondly, the data fusion
algorithm is proposed according to the data characteristics of the sensor array on the steering
wheel. The support matrix is used to improve the data consistency of the single sensor data,
and then the adaptive weighted fusion algorithm is used for multiple sensors. Finally, in order
to verify the reliability of the system, an online intelligent detection device for drunk driving
based on multi-sensor fusion was developed, and three people using different combinations
of drunk driving simulation experiments were conducted. According to the test results, a
drunk person in the passenger seat will not cause the system to make a drunk driving
determination. When more than 50 mL of alcohol is consumed and the driver is seated in the
driver’s seat, the online intelligent detection of drunk driving can accurately identify drunk
driving, and the car will lock itself as soon as a real-time online voice prompt is heard. This
study enhances and complements theories relating to data fusion for online automobile drunk
driving detection, allowing for the online identification of drivers who have been drinking
and the locking of their vehicles to prevent drunk driving. It provides technical support for
enhancing the accuracy of online systems that detect drunk driving in automobiles.