Mobile Phone Based Drunk Driving Detection Jiangpeng Dai, Jin Teng, XiaoleBai, ZhaohuiShen, and Dong Xuan Presented by Li Li
Outline Problem Definition Acceleration-Based Drunk Driving Cues System Design & Implementation Evaluation Related Work Discussion
Problem definition What is drunk driving? Why do we need to use smart phone to detect it? Requirements of drunk driving monitoring system
Acceleration-Based Drunk Driving Cues Lateral Acceleration and Lane Position Maintenance
Acceleration-Based Drunk Driving Cues (cont’d) Longitudinal Acceleration and Speed Control in Driving Abrupt acceleration or deceleration Erratic braking Jerky stop
System Design & Implementation System Overview
Design of Algorithm Reading accelerations and angles by using accelerometer and orientation sensor
Design of Algorithm (cont’d) Lateral acceleration and longitudinal acceleration detection
Lateral Acceleration Pattern Matching The pattern matching is to check the variation between the maximum value and the minimum value of Alat within a pattern checking time window WINlat.
Longitudinal Acceleration Pattern Matching When the vehicle acts abnormally in either accelerating or decelerating direction, result in a large absolute value of Alon, making a salient convex or concave shape in its graph of curves. Set different thresholds for positive Alon and negative Alon.
Multiple Round Pattern Matching Multiple round means that the matching process continues round after round, and the trigger condition is satisfied when several numbers of pattern are recognized. Multiple round pattern matching will increase the accuracy of drunk driving detection.
Implementation Drunk driving detection system on Android G1 phone. Java, with Eclipse and Android 1.6 SDK Five major components: User interface System configuration Monitoring daemon Data processing Alert notification
Related Work GPS Expensive Localization error Energy consuming Camera High position requirements Complicated Energy consuming for image processing
Discussion Create another threshold Normal Alert Non-drunk Drunk FP Normal Alert
REFERENCES Jiangpeng Dai, Jin Teng, XiaoleBai, ZhaohuiShen and Dong Xuan, Mobile Phone based Drunk Driving Detection, in Proc. of International ICST Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health), March 2010.