Patent ID: 10252461

Abstract:
Methods, systems, and computer program products for driving anomaly detection based on spatio-temporal landscape-specific driving models are provided herein. A method includes generating, for each of multiple users, a temporally-related driving skill model pertaining to one or more landscapes, wherein the model is based on temporally-related driving data associated with the users and landscape-related information of trips driven by the users; monitoring the users participating in a ride-sharing trip in a vehicle by analyzing ride-sharing trip data; detecting driving-related anomalies attributed to the monitored users by comparing the ride-sharing trip data and the respective temporally-related driving skill model for each monitored user; updating a schedule for the trip based on the detected anomalies and estimated conditions attributed to remaining portions of the trip by modifying an assignment of selected users to drive the vehicle during the remaining portions of the trip; and outputting the updated schedule to the selected users.