A Two-Step E-Nose System for Vehicle Drunk Driving Rapid Detection

Abstract

With the rapid development of shared cars, to reduce the phenomenon of drunk driving in shared cars, we have studied the onboard drunk driving rapid detection electronic nose system suitable for shared cars. To accurately judge whether the driver is drunk while driving in the presence of interfering gases such as passenger exhalation and the volatile smell containing alcohol, this paper proposes a two-step drunk driving detection frame for shared cars that first judges whether someone in the car is drunk and then judges whether the driver is drunk. To reduce the cost and volume of the electronic nose, the sensor array was optimized based on the random forest algorithm. To find the optimal sampling time, we processed the original data by time slicing. Finally, using the two-step framework proposed by us, the accuracy of the first step and the second step of driver drunk driving detection reached 99.44% and 100%, respectively, with a sampling time of 5 s. After algorithm optimization, only 9 of the 21 sensors were left. This paper presents a practical electronic nose system for the detection of drunk driving in shared cars.