Mobile phone based drunk driving detection

By Jiangpeng Dai, Jin Teng, Xiaole Bai, Zhaohui Shen, Dong Xuan. International Conference on Pervasive Computing Technologies for Healthcare, 2010

375 citations recorded by the source corpus.

Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone and have it tested with different kinds of driving behaviors. The results show that the system achieves high accuracy and energy efficiency.

Subfields: Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/e744b662232040c948b92c178766dcbdbeb30b50

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In Computer Vision and Pattern Recognition

In Experimental and Cognitive Psychology

Citations in the corpus

Driving style recognition using a smartphone as a sensor platform (2011, background): “Labeling large numbers of samples for training, for example when using Hidden Markov Models, is unnecessary for the limited set of movements.”
Safe Driving Using Mobile Phones (2012, background): “Dai et al. [2] focused on a driver’s ability to perform on the road.”