Abstract: A method for providing proactive driving alerts includes determining a road segment of interest, receiving GPS data and contextual data, and identifying a triggering condition in a vicinity of the segment of interest. The method also includes determining an applicability of the triggering condition to the segment of interest, retrieving an alert threshold corresponding to the triggering condition, and obtaining an action factor correlating to a user's driving behavior. The method further includes determining whether the action factor exceeds the alert threshold and providing a proactive alert related to the triggering condition to the user.

Abstract: Aspects of the embodiments include receiving, from one or more telematics sensors in a vehicle and by the one or more data processing systems, a plurality of telematics data items that are sampled at a plurality of sample times. For a given sample time, accessing a given telematics data item that satisfies the one or more conditions, computing a fuel consumption amount at the given sample time, and determining a distance traveled by the vehicle from a previous sample time that is prior to the given sample time, to the given sample time. For each telematics data items that satisfies the conditions, computing a total distance and a total fuel consumption amount, with the computing based on distances traveled and fuel consumption amounts for the plurality of telematics data items; and determining a fuel efficiency score the total fuel consumption amount and the total distance or a total time.

Abstract: A method for identifying correlated mobile computing devices associated with a common vehicle or trip includes determining, based on data received from one or more first sensors associated with a first mobile computing device, that the first mobile computing device is on a trip in a vehicle, broadcasting, by the first mobile computing device, a signal indicating that the first mobile computing device is on the trip in the vehicle, receiving, by at least one second mobile computing device, the signal being broadcasted from the first mobile computing device, determining that the second mobile computing device is in the same vehicle as the first mobile computing device, and in response to the determination, causing the second mobile computing device to cease collection of data from one or more second sensors associated with the second mobile computing device.

Abstract: A system can include one or more processors and computer storage storing executable computer instructions executable by the one or more processors to receive a first vehicle input comprising telematics data characterizing one or more telematics characteristics of a vehicle; receive a second vehicle input comprising vehicle data characterizing one or more vehicle symbol characteristics of the vehicle; process the first vehicle input and the second vehicle input to generate an embedding; and process the embedding using a prediction model to generate the risk prediction. Risk assessments determined using telematics information can be interpreted or modified based on vehicle-specific information.

Abstract: A method for providing proactive driving alerts includes determining a road segment of interest, receiving GPS data and contextual data, and identifying a triggering condition in a vicinity of the segment of interest. The method also includes determining an applicability of the triggering condition to the segment of interest, retrieving an alert threshold corresponding to the triggering condition, and obtaining an action factor correlating to a user's driving behavior. The method further includes determining whether the action factor exceeds the alert threshold and providing a proactive alert related to the triggering condition to the user.

Abstract: Among other things, safety performance of vehicles is monitored or evaluated, or both. Sensor data is received from one or more sensors at a vehicle. One or more risk sources encountered by the vehicle during a period of operation of the vehicle are identified based on the sensor data. One or more safety events experienced by the vehicle during the period of operation are identified based on the sensor data. A risk of a safety event experienced by the vehicle during the period of operation is determined based on the one or more risk sources. A safety performance of the vehicle during the period of the vehicle during the period of operation of the vehicle is determined based on the one or more safety events and the risk.

Abstract: A method and system for detecting and monitoring discrete interactions within a physical social network is provided. The system and method detects attributes associated with human communication activities and distinguishes them from other concurrently detected activities in order to identify discrete interactions that are in turn transmitted across a network having a limited data rate. Generally, in its simplest form a plurality of wireless sensors are deployed across a cross-section of people of interest. Once deployed, the wireless sensors establish an ad-hoc network that transmits a small amount of data relating to the each of the discrete individuals bearing a sensor. The collected data is analyzed through the application of rules set forth in a Bayesian belief network to make a determination regarding the probability that an actual interaction between two individuals bearing sensors in fact occurred.