Leveraging Smartphone Sensors to Detect Distracted Driving Activities

• Published in: IEEE transactions on intelligent transportation systems Vol. 20; no. 9; pp. 3303 - 3312
• Main Authors: Ben Ahmed, Kaoutar, Goel, Bharti, Bharti, Pratool, Chellappan, Sriram, Bouhorma, Mohammed
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accelerometers; Automobiles; Braking; Data logging; Distracted driving; Driver behavior; Environmental testing; Feature extraction; Gyroscopes; intelligent transportation systems; Machine learning; Pedals; Sensors; Short message service; Simulation; Smart sensing; Smartphones; Steering; Wheels; Wide screen
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2018.2873972

In this paper, we explore the feasibility of leveraging the accelerometer and gyroscope sensors in modern smartphones to detect instances of distracted driving activities (e.g., calling, texting, and reading while driving). To do so, we conducted an experiment with 16 subjects on a realistic driving simulator. As discussed later, the simulator is equipped with a realistic steering wheel, acceleration/braking pedals, and a wide screen to visualize background vehicular traffic. It is also programmed to simulate multiple environmental conditions like daytime, nighttime, fog, and rain/snow. The subjects were instructed to drive the simulator while performing a randomized sequence of activities that included texting, calling, and reading from a phone while they were driving, during which the accelerometer and gyroscope in the phone were logging sensory data. By extracting features from this sensory data, we then implemented a machine learning technique based on random forests to detect distracted driving. Our technique achieves very good precision, recall, and <inline-formula> <tex-math notation="LaTeX">F </tex-math></inline-formula>-measure across all environmental conditions we tested. We believe that our contributions in this paper can have a significant impact on enhancing road safety.