Abstract: A computing system may be configured to receive and analyze movement data. A stopping point within the movement data may be determined. Additional data related to the determined stopping point may be received from one or more roadway infrastructure devices. A time interval of data may be determined and analyzed based on the additional data. A driving pattern may be determined based on the analyzed determined time interval of data. A driver of a driving trip may be determined based on the driving pattern. Data corresponding to the driver and the driving trip may be outputted. Drivers associated with driving trips may be identified based on the movement data. In some cases, a driving pattern may be determined based on the movement data.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze acceleration data corresponding to driving data, analyze the acceleration data, and determine driving patterns and associated drivers based on the data. Acceleration data may be collected by one or more mobile devices, such as smartphones, tablet computers, and/or on-board vehicle systems. Drivers associated with driving trips may be identified based on the acceleration data collected by the mobile devices. In some cases, driving patterns may be determined based on the acceleration data before and after stopping points during driving trips, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze acceleration data corresponding to driving data, analyze the acceleration data, and determine driving patterns and associated drivers based on the data. Acceleration data may be collected by one or more mobile devices, such as smartphones, tablet computers, and/or on-board vehicle systems. Drivers associated with driving trips may be identified based on the acceleration data collected by the mobile devices. In some cases, driving patterns may be determined based on the acceleration data before and after stopping points during driving trips, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.

Abstract: A computing system may be configured to receive and analyze movement data. A stopping point within the movement data may be determined. Additional data related to the determined stopping point may be received from one or more roadway infrastructure devices. A time interval of data may be determined and analyzed based on the additional data. A driving pattern may be determined based on the analyzed determined time interval of data. A driver of a driving trip may be determined based on the driving pattern. Data corresponding to the driver and the driving trip may be outputted. Drivers associated with driving trips may be identified based on the movement data. In some cases, a driving pattern may be determined based on the movement data.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze movement data and driving data, and determine driving trips and associated drivers based on the received data. Movement data may be collected by one or more mobile devices, such as smartphones, tablet computers, and on-board vehicle systems. Drivers associated with driving trips may be identified based on the movement data collected by the mobile devices, such as speed data, acceleration data, or distance/location data. In some cases, driving patterns may be determined based on the movement data before and after stopping points, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze acceleration data corresponding to driving data, analyze the acceleration data, and determine driving patterns and associated drivers based on the data. Acceleration data may be collected by one or more mobile devices, such as smartphones, tablet computers, and/or on-board vehicle systems. Drivers associated with driving trips may be identified based on the acceleration data collected by the mobile devices. In some cases, driving patterns may be determined based on the acceleration data before and after stopping points during driving trips, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze movement data and driving data, and determine driving trips and associated drivers based on the received data. Movement data may be collected by one or more mobile devices, such as smartphones, tablet computers, and on-board vehicle systems. Drivers associated with driving trips may be identified based on the movement data collected by the mobile devices, such as speed data, acceleration data, or distance/location data. In some cases, driving patterns may be determined based on the movement data before and after stopping points, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze acceleration data corresponding to driving data, analyze the acceleration data, and determine driving patterns and associated drivers based on the data. Acceleration data may be collected by one or more mobile devices, such as smartphones, tablet computers, and/or on-board vehicle systems. Drivers associated with driving trips may be identified based on the acceleration data collected by the mobile devices. In some cases, driving patterns may be determined based on the acceleration data before and after stopping points during driving trips, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.