Abstract: The present disclosure is directed to improving safety of drivers that drive vehicles that belong to a fleet of vehicles. This may include identifying individual drivers that should receive a training or coaching session. Scores that associated vehicle type, vehicle weight class, time of day, number of stops/starts, and other factors could be evaluated to identify drivers that may have been assigned a highest risk factor. Company telematic data as well as public data that identify types of roadways, roadway conditions, experience levels, and other factors may be combined with numbers of accidents or speeding tickets when an analysis is performed. Methods described herein may be implemented according to a machine learning model based on a processor executing instructions out of a memory. This may include deep learning or the neural network technology.

Abstract: The present disclosure is directed to dynamically analyzing data and conditions associated with the movement of a vehicle. A processor may evaluate vehicle location and speed information when identifying an amount of navigation data to send to a computer at a vehicle. The amount of information sent to the computer may vary based on the vehicle speed, a type of road that the vehicle is able to drive along, or may vary based on other attributes. The information sent to the computer may also relate to an area that the vehicle is anticipated to move through in a given time frame. Mapping data sent to the vehicle computer may be associated with a larger area when a vehicle is moving at a faster speed and may be associated with a smaller area when the vehicle is moving at a slower speed.

Abstract: The present disclosure is directed to dynamically analyzing data and conditions associated with the movement of a vehicle. A processor may evaluate vehicle location and speed information when identifying an amount of navigation data to send to a computer at a vehicle. The amount of information sent to the computer may vary based on the vehicle speed, a type of road that the vehicle is able to drive along, or may vary based on other attributes. The information sent to the computer may also relate to an area that the vehicle is anticipated to move through in a given time frame. Mapping data sent to the vehicle computer may be associated with a larger area when a vehicle is moving at a faster speed and may be associated with a smaller area when the vehicle is moving at a slower speed.