Analyzing telematics data within heterogeneous vehicle populations

A computing system including one or more computing devices, comprising:

• a logic subsystem including one or more physical logic devices;
• and
• a storage subsystem including one or more physical memory devices having instructions stored thereon executable by the one or more physical logic devices of the logic subsystem to:
• obtain a set of vehicle telematics data for each vehicle of a population of vehicles,
• wherein for each vehicle of the population, the set of vehicle telematics data is obtained by receiving communications transmitted from that vehicle by a vehicle-based telematics device via a wireless communications network;
• identify, within each set of vehicle telematics data, a vehicle identifier of the vehicle from which that set of vehicle telematics data originated and a set of time-based measurements for a measurement type indicated by a measurement type identifier contained within the set of vehicle telematics data, the set of time-based measurements captured by one or more sensors of the vehicle and received from the one or more sensors along with the vehicle identifier of the vehicle by the vehicle-based telematics device via a physical connector of an on-board diagnostics (OBD) interface;
• combine the set of time-based measurements identified for each vehicle to obtain a combined set of time-based observations for the measurement type indicated by the measurement type identifier contained in each set of vehicle telematics data across the population of vehicles;
• apply a statistical model to the combined set of time-based observations to obtain a set of one or more probability distributions;
• identify an outlier observation from among the combined set of time-based observations that is located outside of the set of one or more probability distributions;
• for the outlier observation, identify the vehicle identifier attributed to the outlier observation;
• determine whether the outlier observation is part of a temporary deviation or a persistent deviation;
• if the outlier observation is part of a temporary deviation, then reduce an impact of the outlier observation on the set of time-based measurements of which the outlier observation is a member to obtain an augmented set of time-based measurements;
• if the outlier is part of a persistent deviation, then programmatically characterize the outlier observation based, at least in part, on the set of time-based measurements of which the outlier observation is a member to obtain a characterization of the persistent deviation;
• and
• output the augmented set of time-based measurements and/or the characterization of the persistent deviation by forwarding the augmented set of time-based measurements and/or the characterization of the persistent deviation to a mobile device of a subscriber associated with the vehicle identifier attributed to the outlier observation.