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Automatic Identification of Driver's Smartphone Exploiting Common Vehicle-riding Actions
- Automatic Identification of Driver's Smartphone Exploiting Common Vehicle-riding Actions
- Park, Homin; Ahn, DaeHan; Park, Taejoon; Shin, Kang G.
- DGIST Authors
- Park, Homin; Ahn, DaeHan
- Issue Date
- IEEE Transactions on Mobile Computing
- Article Type
- Article in Press
- Accidents; Automatic Identification; Automatic Vehicle Identification; Automation; Automobile Safety Devices; Distracted Driving; Electromagnetic Fields; Energy Utilization; Engines; Feature Extraction
- Texting or browsing web on a smartphone while driving is one of the most distracting activities that significantly increase the risk of car accidents. There have been a number of proposals for the prevention of distracted driving, but none of them has addressed its important challenges completely and effectively. To remedy this deficiency, we present an event-driven solution, called Automatic Identification of Driver's Smartphone (AIDS), which identifies a driver's smartphone by analyzing and fusing the phone's sensory information related to common vehicle-riding activities. AIDS extracts features useful for identification of the driver's phone from diverse sensors available in commodity smartphones. It identifies the driver's phone before the vehicle leaves its parked spot, and differentiates seated (front or rear) rows in a vehicle by analyzing the subtle electromagnetic field spikes caused by the starting of the engine. To evaluate the feasibility and adaptability, we have conducted extensive experiments: a prototype of AIDS was distributed to 12 participants, who have driven 7 different vehicles for 3 days in real-world environments. Our evaluation results show that AIDS identified the driver's phone with an 83.3-93.3% true positive rate while achieving a 90.1-91.2% true negative rate at a marginal increase of the phone's energy consumption. IEEE
- Institute of Electrical and Electronics Engineers Inc.
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