4th International ICST Conference on Pervasive Computing Technologies for Healthcare

Research Article

Mobile phone based drunk driving detection

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  • @INPROCEEDINGS{10.4108/ICST.PERVASIVEHEALTH2010.8901,
        author={Jiangpeng Dai and Jin Teng and Xiaole Bai and Zhaohui Shen and Dong Xuan},
        title={Mobile phone based drunk driving detection},
        proceedings={4th International ICST Conference on Pervasive Computing Technologies for Healthcare},
        proceedings_a={PERVASIVEHEALTH},
        year={2010},
        month={6},
        keywords={Drunk Driving Detection Mobile Phones Acceleration Sensors},
        doi={10.4108/ICST.PERVASIVEHEALTH2010.8901}
    }
    
  • Jiangpeng Dai
    Jin Teng
    Xiaole Bai
    Zhaohui Shen
    Dong Xuan
    Year: 2010
    Mobile phone based drunk driving detection
    PERVASIVEHEALTH
    ICST
    DOI: 10.4108/ICST.PERVASIVEHEALTH2010.8901
Jiangpeng Dai1,2,*, Jin Teng2,*, Xiaole Bai2,*, Zhaohui Shen3,*, Dong Xuan2,*
  • 1: School of Computer Sci. & Engr., Southeast University, Nanjing, Jiangsu, China
  • 2: Dept. of Computer Sci. and Engr., The Ohio State University, Columbus, Ohio, USA
  • 3: Division of Physical Therapy, The Ohio State University, Columbus, Ohio, USA
*Contact email: jpdai@seu.edu.cn, tengj@cse.ohio-state.edu, baixia@cse.ohio-state.edu, shen.119@osu.edu, xuan@cse.ohio-state.edu

Abstract

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.