Abstract: Methods, computer-readable media, systems and apparatuses for determining and implementing risk unit usage-based insurance policies. In some arrangements, sensor data associated with vehicle operation data, driving data, and the like, may be received and analyzed to determine a consumption rate of risk units in the risk unit usage-based insurance policy. In some examples, one or more driving behaviors may also be identified (e.g., from the sensor data, historical data, and the like). In some examples, one or more user interfaces may be generated displaying the determined consumption rate and/or driving behaviors. In some arrangements, additional information, such as one or more recommendations for improving (e.g., reducing) consumption rate may be generated and provided via the generated user interface.

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: Methods, computer-readable media, systems and apparatuses for determining and implementing risk unit usage-based insurance policies. In some arrangements, sensor data associated with vehicle operation data, driving data, and the like, may be received and analyzed to determine a consumption rate of risk units in the risk unit usage-based insurance policy. In some examples, one or more driving behaviors may also be identified (e.g., from the sensor data, historical data, and the like). In some examples, one or more user interfaces may be generated displaying the determined consumption rate and/or driving behaviors. In some arrangements, additional information, such as one or more recommendations for improving (e.g., reducing) consumption rate may be generated and provided via the generated user interface.

Abstract: A driving analysis server may be configured to receive vehicle operation data from mobile devices respectively disposed within the vehicles, and may use the data to group the vehicles into multiple groups. A driving pattern for each vehicle may be established and compared against a group driving pattern of its corresponding group to identify outliers. A driver score the outliers may be adjusted positively or negatively based on whether the outlier behaved in a manner more or less safe than its group. Further, unsafe driving events performed by the outlier that were the result of another vehicle's unsafe driving event may be ignored or positively accounted for in determining or adjusting the outlier's driver score.

Abstract: Systems and methods of analyzing a target vehicle based on other vehicles are disclosed. One or more computing devices may receive monitoring vehicle driving data collected from vehicle operation sensors within at least one monitoring vehicle by a telematics device. The one or more computing devices may further receive target vehicle driving data from the telematics device of the at least one monitoring vehicle. The one or more computing devices may determine a driving behavior associated with the target vehicle based on an analysis of the monitoring vehicle driving data and the target vehicle driving data. The one or more computing devices may calculate one or more driver scores based on the driving behavior.

Abstract: Methods, computer-readable media, systems, and apparatuses for determining a safest road segment for traveling between two locations are provided. In some cases, a road segment safety rating may be determined for a plurality of road segments between the two locations based on historical data associated with the road segments and/or based on driving behavior data of an operator of the vehicle. An indication of the road segment determined as being the safest may be provided to the operator of the vehicle. An actual route of travel of the vehicle may be compared to the safest route. If the actual route of travel is different from the determined safest route, the operator may be notified that an award may be earned when the determined safest route is traveled. If the actual route of travel is determined to be safer than the determined safest route, an award may be earned.

Abstract: Methods, computer-readable media, systems, and apparatuses for determining a safest road segment for traveling between two locations are provided. In some cases, a road segment safety rating may be determined for a plurality of road segments between the two locations based on historical data associated with the road segments and/or based on driving behavior data of an operator of the vehicle. An indication of the road segment determined as being the safest may be provided to the operator of the vehicle. An actual route of travel of the vehicle may be compared to the safest route. If the actual route of travel is different from the determined safest route, the operator may be notified that an award may be earned when the determined safest route is traveled. If the actual route of travel is determined to be safer than the determined safest route, an award may be earned.

Abstract: A driving analysis server may be configured to receive vehicle operation data from mobile devices respectively disposed within the vehicles, and may use the data to group the vehicles into multiple groups. A driving pattern for each vehicle may be established and compared against a group driving pattern of its corresponding group to identify outliers. A driver score the outliers may be adjusted positively or negatively based on whether the outlier behaved in a manner more or less safe than its group. Further, unsafe driving events performed by the outlier that were the result of another vehicle’s unsafe driving event may be ignored or positively accounted for in determining or adjusting the outlier’s driver score.

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 provided for designing a preferred route for a vehicle. The route designing system receives a request from the vehicle for a preferred route from a first geographical point to a second geographical point. The route designing system analyzes the request and obtains driving scores associated with drivers of other vehicles. The route designing unit may identify a set of preferred and non-preferred vehicles based on the driving scores. The route designing system then determines a preferred route based, at least in part, on the driving scores associated with drivers of the other vehicles. The preferred route is designed to minimize the likelihood of proximity to non-preferred vehicles and maximize the likelihood of proximity to preferred vehicles.

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 video analysis computing system driving analysis may include a camera associated with a first vehicle and having a viewing angle capable of capturing a video of one or more other vehicles in proximity to the first vehicle, a first memory location communicatively coupled to the camera, wherein the first memory location stores video data captured by the camera, and an evaluation module including a processor executing instructions that cause the processor to: evaluate the captured video stored in the first memory location to determine whether a driving event performed by a second vehicle has occurred, assign, in response to an identified driving event performed by the second vehicle, a driving event rating to a video showing the identified driving event, wherein the driving event rating may be calculated, at least in part, using a crowd-sourced driving event rating obtained after posting the video to a social network.

Abstract: Methods, computer-readable media, systems and apparatuses for determining and implementing dynamic usage-based insurance policies are presented. A cost per day and a cost per mile associated with the dynamic usage-based insurance policy may be determined. The cost per mile may be computed independently for each of a plurality of road segments comprising a trip based on a time of day that the vehicle traveled each road segment, a road type associated with each road segment. The cost per mile of each road segment of the driving trip may further include whether or not hard braking or hard cornering events were encountered during a specified cumulative driving distance that may include, at least a portion, of a plurality of driving trips. The cost per mile for each of the plurality of driving trips may be adjusted once a threshold distance has been traveled by the vehicle based on the number of hard braking events and hard cornering events occurred during that distance.

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: A driving analysis server may be configured to receive vehicle operation data from mobile devices respectively disposed within the vehicles, and may use the data to group the vehicles into multiple groups. A driving pattern for each vehicle may be established and compared against a group driving pattern of its corresponding group to identify outliers. A driver score the outliers may be adjusted positively or negatively based on whether the outlier behaved in a manner more or less safe than its group. Further, unsafe driving events performed by the outlier that were the result of another vehicle's unsafe driving event may be ignored or positively accounted for in determining or adjusting the outlier's driver score.

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: Methods, computer-readable media, systems and apparatuses for determining and implementing dynamic usage-based insurance policies are presented. A cost per day and a cost per mile associated with the dynamic usage-based insurance policy may be determined. The cost per mile may be computed independently for each of a plurality of road segments comprising a trip based on a time of day that the vehicle traveled each road segment, a road type associated with each road segment. The cost per mile of each road segment of the driving trip may further include whether or not hard braking or hard cornering events were encountered during a specified cumulative driving distance that may include, at least a portion, of a plurality of driving trips. The cost per mile for each of the plurality of driving trips may be adjusted once a threshold distance has been traveled by the vehicle based on the number of hard braking events and hard cornering events occurred during that distance.

Abstract: A driving analysis server may be configured to receive vehicle operation data from mobile devices respectively disposed within the vehicles, and may use the data to group the vehicles into multiple groups. A driving pattern for each vehicle may be established and compared against a group driving pattern of its corresponding group to identify outliers. A driver score the outliers may be adjusted positively or negatively based on whether the outlier behaved in a manner more or less safe than its group. Further, unsafe driving events performed by the outlier that were the result of another vehicle's unsafe driving event may be ignored or positively accounted for in determining or adjusting the outlier's driver score.

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 of analyzing a target vehicle based on other vehicles are disclosed. One or more computing devices may receive monitoring vehicle driving data collected from vehicle operation sensors within at least one monitoring vehicle by a telematics device. The one or more computing devices may further receive target vehicle driving data from the telematics device of the at least one monitoring vehicle. The one or more computing devices may determine a driving behavior associated with the target vehicle based on an analysis of the monitoring vehicle driving data and the target vehicle driving data. The one or more computing devices may calculate one or more driver scores based on the driving behavior.