Abstract: Aspects of the disclosure relate to using vehicle telematics data to assess parameters associated with vehicle operation. In some instances, a driving assessment system may include a first computing device associated with a user in a vehicle and a second computing located remotely from the first computing device. The first computing device may collect, by way of one or more of an accelerometer and global positioning system (GPS), vehicle operational data and vehicle locational information associated with the vehicle and corresponding to a trip of the vehicle and may transmit such information to the second computing device. The second computing device may identify actionable and second order actionable trip data from the vehicle operational data and vehicle locational information and may calculate a behavior score for the trip.

Abstract: Systems and methods are disclosed for determining whether or not an apparatus, such as a mobile device, is being handled or otherwise used within a vehicle. The apparatus may comprise an accelerometer configured to measure acceleration and a gyroscope configured to measure orientation. The apparatus may determine an axis of gravity of the apparatus based on acceleration measurements made by the accelerometer over a period of time. The apparatus may also determine a rotation vector of the apparatus based on orientation measurements made by the gyroscope. Using the axis of gravity of the apparatus and the rotation vector of the apparatus, the apparatus may determine a rate of rotation of the apparatus perpendicular to the axis of gravity. If the rate of rotation of the apparatus perpendicular to the axis of gravity exceeds a threshold, the apparatus may determine that it is being handled or otherwise used within the vehicle.

Abstract: Systems and methods are disclosed for determining whether or not an apparatus, such as a mobile device, is being handled or otherwise used within a vehicle. The apparatus may comprise an accelerometer configured to measure acceleration and a gyroscope configured to measure orientation. The apparatus may determine an axis of gravity of the apparatus based on acceleration measurements made by the accelerometer over a period of time. The apparatus may also determine a rotation vector of the apparatus based on orientation measurements made by the gyroscope. Using the axis of gravity of the apparatus and the rotation vector of the apparatus, the apparatus may determine a rate of rotation of the apparatus perpendicular to the axis of gravity. If the rate of rotation of the apparatus perpendicular to the axis of gravity exceeds a threshold, the apparatus may determine that it is being handled or otherwise used within the vehicle.

Abstract: One or more braking event detection computing devices and methods are disclosed herein based on fused sensor data collected during a window of time from various sensors of a mobile device found within an interior of a vehicle. The various sensors of the mobile device may include a GPS receiver, an accelerometer, a gyroscope, a microphone, a camera, and a magnetometer. Data from vehicle sensors and other external systems may also be used. The braking event detection computing devices may adjust the polling frequency of the GPS receiver of the mobile device to capture non-consecutive data points based on the speed of the vehicle, the battery status of the mobile device, traffic-related information, and weather-related information. The braking event detection computing devices may use classification machine learning algorithms on the fused sensor data to determine whether or not to classify a window of time as a braking event.

Abstract: An turn detection system is configured to determine headings or a course of a vehicle over a period of time and evaluate whether the vehicle has registered a turn based on these headings/course. In some arrangements, upon detecting a turn, sensor data may be collected to determine one or more characteristics or attributes of the turn. Such data may indicate a loss event associated with the turn and be used to calculate a probability or risk of loss given the various characteristics of the turn. These probabilities may further be applied to determine various costs and premiums.

Abstract: Systems and methods are disclosed for receiving and transmitting accelerometer data and/or usage data, and analyzing the data to detect movement or usage of the device within a vehicle. A device, such as a mobile device, may detect a device movement event or a device usage event associated with the device. Based on the detection of the device movement event or the device usage event, a time associated with the event may be stored. The device may determine whether another event associated with the device occurs within a threshold amount of time from the time associated with the event. Based on a determination of whether the other event occurs within the threshold amount of time, the device may determine an event session associated with the device. The event session may comprise an instantaneous event or a continuous event. Data indicative of the event session may be transmitted to a server.

Abstract: An turn detection system is configured to determine headings or a course of a vehicle over a period of time and evaluate whether the vehicle has registered a turn based on these headings/course. In some arrangements, upon detecting a turn, sensor data may be collected to determine one or more characteristics or attributes of the turn. Such data may indicate a loss event associated with the turn and be used to calculate a probability or risk of loss given the various characteristics of the turn. These probabilities may further be applied to determine various costs and premiums.

Abstract: One or more braking event detection computing devices and methods are disclosed herein based on fused sensor data collected during a window of time from various sensors of a mobile device found within an interior of a vehicle. The various sensors of the mobile device may include a GPS receiver, an accelerometer, a gyroscope, a microphone, a camera, and a magnetometer. Data from vehicle sensors and other external systems may also be used. The braking event detection computing devices may adjust the polling frequency of the GPS receiver of the mobile device to capture non-consecutive data points based on the speed of the vehicle, the battery status of the mobile device, traffic-related information, and weather-related information. The braking event detection computing devices may use classification machine learning algorithms on the fused sensor data to determine whether or not to classify a window of time as a braking event.

Abstract: One or more location analysis computing devices, methods, and computer-readable media are disclosed herein for determining the position of a mobile device (smartphone, tablet computer) within an interior of a vehicle. The position of the mobile device may be calculated by detecting changes in accelerometer data. The accelerometer data may first need to be translated to determine corresponding axes, since the device may not be right side up (e.g., in a pocket). The vehicle may travel over road discontinuities such as bumps, and calculating the position of the mobile device may be based on the different magnitude and angle resulting from a first tire and a second tire hitting the bump. Data from vehicle sensors or other mobile device sensors may also be used in the calculating. Once the position is determined, commands may be sent to the mobile device to deactivate certain functionality, or to a remote server for further processing.

Abstract: Systems and methods are disclosed for receiving and transmitting accelerometer data and/or usage data, and analyzing the data to detect movement or usage of the device within a vehicle. A device, such as a mobile device, may detect a device movement event or a device usage event associated with the device. Based on the detection of the device movement event or the device usage event, a time associated with the event may be stored. The device may determine whether another event associated with the device occurs within a threshold amount of time from the time associated with the event. Based on a determination of whether the other event occurs within the threshold amount of time, the device may determine an event session associated with the device. The event session may comprise an instantaneous event or a continuous event. Data indicative of the event session may be transmitted to a server.

Abstract: Aspects of the disclosure relate to using vehicle telematics data to assess parameters associated with vehicle operation. In some instances, a driving assessment system may include a first computing device associated with a user in a vehicle and a second computing located remotely from the first computing device. The first computing device may collect, by way of one or more of an accelerometer and global positioning system (GPS), vehicle operational data and vehicle locational information associated with the vehicle and corresponding to a trip of the vehicle and may transmit such information to the second computing device. The second computing device may identify actionable and second order actionable trip data from the vehicle operational data and vehicle locational information and may calculate a behavior score for the trip.

Abstract: Aspects of the disclosure relate to using vehicle telematics data to assess parameters associated with vehicle operation. In some instances, a driving assessment system may include a first computing device associated with a user in a vehicle and a second computing located remotely from the first computing device. The first computing device may collect, by way of one or more of an accelerometer and global positioning system (GPS), vehicle operational data and vehicle locational information associated with the vehicle and corresponding to a trip of the vehicle and may transmit such information to the second computing device. The second computing device may identify actionable and second order actionable trip data from the vehicle operational data and vehicle locational information and may calculate a behavior score for the trip.

Abstract: One or more location analysis computing devices, methods, and computer-readable media are disclosed herein for determining the position of a mobile device (smartphone, tablet computer) within an interior of a vehicle. The position of the mobile device may be calculated by detecting changes in accelerometer data. The accelerometer data may first need to be translated to determine corresponding axes, since the device may not be right side up (e.g., in a pocket). The vehicle may travel over road discontinuities such as bumps, and calculating the position of the mobile device may be based on the different magnitude and angle resulting from a first tire and a second tire hitting the bump. Data from vehicle sensors or other mobile device sensors may also be used in the calculating. Once the position is determined, commands may be sent to the mobile device to deactivate certain functionality, or to a remote server for further processing.

Abstract: Systems and methods are disclosed for determining whether or not a crash involving a vehicle has occurred. The acceleration of the vehicle may be measured using, for example, an accelerometer of a mobile device, which may be located inside the vehicle. The system may determine the magnitude of each accelerometer measurement and whether the magnitude exceeds one or more acceleration magnitude thresholds. The system may also determine the number of accelerometer events within a time window and whether the number exceeds one or more count thresholds. The system may determine whether a crash involving the vehicle has occurred based on the magnitudes of acceleration, number of acceleration events, and various thresholds. In some examples, the system may confirm that a crash has occurred based on, for example, the location of the mobile device.

Abstract: One or more braking event detection computing devices and methods are disclosed herein based on fused sensor data collected during a window of time from various sensors of a mobile device found within an interior of a vehicle. The various sensors of the mobile device may include a GPS receiver, an accelerometer, a gyroscope, a microphone, a camera, and a magnetometer. Data from vehicle sensors and other external systems may also be used. The braking event detection computing devices may adjust the polling frequency of the GPS receiver of the mobile device to capture non-consecutive data points based on the speed of the vehicle, the battery status of the mobile device, traffic-related information, and weather-related information. The braking event detection computing devices may use classification machine learning algorithms on the fused sensor data to determine whether or not to classify a window of time as a braking event.

Abstract: One or more braking event detection computing devices and methods are disclosed herein based on fused sensor data collected during a window of time from various sensors of a mobile device found within an interior of a vehicle. The various sensors of the mobile device may include a GPS receiver, an accelerometer, a gyroscope, a microphone, a camera, and a magnetometer. Data from vehicle sensors and other external systems may also be used. The braking event detection computing devices may adjust the polling frequency of the GPS receiver of the mobile device to capture non-consecutive data points based on the speed of the vehicle, the battery status of the mobile device, traffic-related information, and weather-related information. The braking event detection computing devices may use classification machine learning algorithms on the fused sensor data to determine whether or not to classify a window of time as a braking event.

Abstract: Systems and methods are disclosed for determining whether or not an apparatus, such as a mobile device, is being handled or otherwise used within a vehicle. The apparatus may comprise an accelerometer configured to measure acceleration and a gyroscope configured to measure orientation. The apparatus may determine an axis of gravity of the apparatus based on acceleration measurements made by the accelerometer over a period of time. The apparatus may also determine a rotation vector of the apparatus based on orientation measurements made by the gyroscope. Using the axis of gravity of the apparatus and the rotation vector of the apparatus, the apparatus may determine a rate of rotation of the apparatus perpendicular to the axis of gravity. If the rate of rotation of the apparatus perpendicular to the axis of gravity exceeds a threshold, the apparatus may determine that it is being handled or otherwise used within the vehicle.

Abstract: One or more braking event detection computing devices and methods are disclosed herein based on fused sensor data collected during a window of time from various sensors of a mobile device found within an interior of a vehicle. The various sensors of the mobile device may include a GPS receiver, an accelerometer, a gyroscope, a microphone, a camera, and a magnetometer. Data from vehicle sensors and other external systems may also be used. The braking event detection computing devices may adjust the polling frequency of the GPS receiver of the mobile device to capture non-consecutive data points based on the speed of the vehicle, the battery status of the mobile device, traffic-related information, and weather-related information. The braking event detection computing devices may use classification machine learning algorithms on the fused sensor data to determine whether or not to classify a window of time as a braking event.

Abstract: One or more location analysis computing devices, methods, and computer-readable media are disclosed herein for determining the position of a mobile device (smartphone, tablet computer) within an interior of a vehicle. The position of the mobile device may be calculated by detecting changes in accelerometer data. The accelerometer data may first need to be translated to determine corresponding axes, since the device may not be right side up (e.g., in a pocket). The vehicle may travel over road discontinuities such as bumps, and calculating the position of the mobile device may be based on the different magnitude and angle resulting from a first tire and a second tire hitting the bump. Data from vehicle sensors or other mobile device sensors may also be used in the calculating. Once the position is determined, commands may be sent to the mobile device to deactivate certain functionality, or to a remote server for further processing.

Abstract: An turn detection system is configured to determine headings or a course of a vehicle over a period of time and evaluate whether the vehicle has registered a turn based on these headings/course. In some arrangements, upon detecting a turn, sensor data may be collected to determine one or more characteristics or attributes of the turn. Such data may indicate a loss event associated with the turn and be used to calculate a probability or risk of loss given the various characteristics of the turn. These probabilities may further be applied to determine various costs and premiums.