Abstract:
Among other things, information generated by sensors of a mobile phone and indicative of motion of the mobile phone and state information indicative of a state of operation of the mobile phone are monitored. Based on the monitoring, distraction by a user of the mobile phone who is a driver of a vehicle is determined.
Abstract:
Data processing techniques and systems for processing telematics data associated with a vehicle, such as an automobile, to classify how the vehicle is being operated by a driver. The telematics data can include the use of image data captured by a camera of the vehicle. The image data is processed in conjunction with vehicular telematics data such as position, speed, and acceleration data of the vehicle obtained from, for example, smartphone sensors. The image data is processed and used by a processing system to provide a context for the telematics data. The image data and the telematics data are classified by the processing system to identify driving behavior of the driver, determine driving maneuvers that have occurred, scoring driving quality of the driver, or a combination of them.
Abstract:
Accurate longitudinal acceleration, lateral acceleration (perpendicular to the principal direction of motion, and velocity, is inferred by processing raw data from a commodity three-axis accelerometer that may be oriented arbitrarily in a moving vehicle (or carried by a moving user), and whose orientation and position may change arbitrarily during the motion. The approach is applicable to a range of applications, including insurance telematics, driver behavior and risk assessment, and road surface quality assessment.
Abstract:
An approach to telematics using mobile devices provides battery-efficient trajectory and mileage inference from inaccurate and intermittent location data. Accurate trajectories of how users or vehicles move in the physical world are formed by processing raw position estimates obtained from noisy, inaccurate, and error-prone position sensors on mobile devices, where the position data may also arrive intermittently with long time gaps. The trajectory is formed using the process of map matching, which determines the trajectory on a map that best explains the sequence of position observations.
Abstract:
Accurate longitudinal acceleration, lateral acceleration (perpendicular to the principal direction of motion, and velocity, is inferred by processing raw data from a commodity three-axis accelerometer that may be oriented arbitrarily in a moving vehicle (or carried by a moving user), and whose orientation and position may change arbitrarily during the motion. The approach is applicable to a range of applications, including insurance telematics, driver behavior and risk assessment, and road surface quality assessment.