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Smartphone usage while driving is unanimously considered to be a really dangerous habit due to strong correlation with road accidents. In this paper, the problem of detecting whether the driver is using the phone during a trip is addressed. To do this, high-frequency data from the triaxial inertial measurement unit (IMU) integrated in almost all modern phone is processed without relying on external inputs so as to provide a self-contained approach. By resorting to a frequency-domain analysis, it is possible to extract from the raw signals the useful information needed to detect when the driver is using the phone, without being affected by the effects that vehicle motion has on the same signals. The selected features are used to train a Support Vector Machine (SVM) algorithm. The performance of the proposed approach are analyzed and tested on experimental data collected during mixed naturalistic driving scenarios, proving the effectiveness of the proposed approach.

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In this paper an algorithm for the estimation of the three mounting angles (roll, pitch, and yaw) of accelerometers and gyroscopes within Inertial Measurement Units (IMUs) is presented. Such a self-calibration method is focused for telematic boxes (e-Boxes) installed on two-wheeled vehicles, whose IMUs' axes often result not to be aligned with the vehicle reference system. Previous methods for axes calibration commonly use satellite-based radionavigation data to determine the unknown mounting angles. In this paper we propose an energy-efficient alignment procedure which limits the use of geolocation data. The aspects of data selection and real-time implementation of our method are taken particularly into account. The proposed approach is validated and performance are analyzed on experimental data collected with tests performed with a motorcycle equipped with three e-Boxes mounted in different positions and orientations. The analysis of the real measured driving data proves the effectiveness of the approach in aligning the sensors' axes in all three directions.

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