Abstract: Embodiments of the present disclosure present systems, devices, methods, and computer readable medium for contextual driver evaluation and feedback. The disclosed techniques allow for a graphical user interface to collect and annotate trip data from various sensors integrated in a mobile device for a user. The techniques presented describe the segmentation of the data into one or more populations and the identification of event and behavior features for each segment in order to evaluate a driver's ability. The techniques described present this information to the user through a graphical user interface that includes a driver score and coaching tips to improve the driver's future behavior.

Abstract: Embodiments of the present disclosure present systems, devices, methods, and computer readable medium for contextual driver evaluation. The disclosed techniques allow for collecting trip data from various sensors integrated in a mobile device for a user. The techniques include segregating the trip motion data into one or more segments associated with one or more populations with distinct features and characteristics. The trip data can be processed to identify event and behavior features that can be used to evaluate a driver's abilities in a contextually appropriate way. The information for a plurality of drivers can be compared to score the driver's ability amount a plurality of drivers.

Abstract: A method of computing an orientation of a mobile device in a vehicle includes collecting accelerometer data from the mobile device. The accelerometer data are subdivided into frames, each frame being a quantity of time in which a sample data point is taken. Statistics are calculated for each frame, including (i) a mean and (ii) a standard deviation of the magnitude of the acceleration vectors. Device usage delimiters, marking start and end points of a coherent block, are computed, the coherent block being consecutive frames in which the mobile device stays in the same orientation relative to the vehicle. A gravity vector is estimated using the statistics in coherent blocks. A nullspace is computed from the gravity vector, the nullspace being a plane orthogonal to the gravity vector. The accelerometer data is projected onto the nullspace, resulting in an estimated orientation of the mobile device in the vehicle.

Abstract: A method of analyzing audio signals, such as for a drive monitoring system, includes recording an audio signal from a mobile device, the audio signal including a background audio stream and a residual audio signal. Communication with an audio database is performed to obtain a reference signal. If a match between the background audio stream and the reference signal is determined, a time alignment between the background audio stream and the reference is computed. At least a portion of the recorded audio signal is aligned with the reference signal using the time alignment. The background audio stream is canceled from the recorded audio signal, to result in the residual audio stream. A computer processor is used to determine a driving behavior factor from the residual audio stream.