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Detecting Driver Phone Use Leveraging Car Speakers Jie Yang†, Simon Sidhom†, Gayathri Chandrasekaran* , Tam Vu*, Hongbo Liu†, Nicolae Cecan*, Yingying Chen†, Marco Gruteser*, Richard P. Martin* †Stevens Institute of Technology, Hoboken, NJ 07030, USA †{jyang, ssidhom, hliu3, yingying.chen}@stevens.edu *Rutgers University, North Brunswick, NJ 08902, USA *{chandrga, tamvu, gruteser, rmartin}@winlab.rutgers.edu, [email protected] ABSTRACT This work addresses the fundamental problem of distinguish- ing between a driver and passenger using a mobile phone, which is the critical input to enable numerous safety and interface enhancements. Our detection system leverages the existing car stereo infrastructure, in particular, the speak- ers and Bluetooth network. Our acoustic approach has the phone send a series of customized high frequency beeps via the car stereo. The beeps are spaced in time across the left, right, and if available, front and rear speakers. Af- ter sampling the beeps, we use a sequential change-point detection scheme to time their arrival, and then use a dif- ferential approach to estimate the phone’s distance from the car’s center. From these differences a passenger or driver classification can be made. To validate our approach, we experimented with two kinds of phones and in two differ- ent cars. We found that our customized beeps were imper- ceptible to most users, yet still playable and recordable in both cars. Our customized beeps were also robust to back- ground sounds such as music and wind, and we found the signal processing did not require excessive computational re- sources. In spite of the cars’ heavy multi-path environment, our approach had a classification accuracy of over 90%, and around 95% with some calibrations. We also found we have a low false positive rate, on the order of a few percent. Categories and Subject Descriptors C.2.4 [Computer-Communication Networks]: Distributed Systems—Distributed Applications; C.3 [Special-Purpose and…