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In this work, we address a fundamental and critical task of detecting thebehavior of driving and texting using smartphones carried by users. We propose,design, and implement TEXIVE that leverages various sensors integrated in thesmartphone and realizes our goal of distinguishing drivers and passengers anddetecting texting using rich user micro-movements and irregularities that canbe detected by sensors in the phone before and during driving and texting.Without relying on external infrastructure, TEXIVE has an advantage of beingreadily implemented and adopted, while at the same time raising a number ofchallenges that need to be carefully addressed for achieving a successfuldetection with good sensitivity, specificity, accuracy, and precision. Oursystem distinguishes the driver and passengers by detecting whether a user isentering a vehicle or not, inferring which side of the vehicle s/he isentering, reasoning whether the user is siting in front or rear seats, anddiscovering if a user is texting by fusing multiple evidences collected fromaccelerometer, magnetometer, and gyroscope sensors. To validate our approach,we conduct extensive experiments with several users on various vehicles andsmartphones. Our evaluation results show that TEXIVE has a classificationaccuracy of 87.18%, and precision of 96.67%.

TEXIVE: Detecting Drivers Using Personal Smart Phones by Leveraging Inertial Sensors