Generating environmental parameters based on sensor data using machine learning

Abstract

First training sensor data detected by a plurality of real-world sensors are obtained. The first training sensor data is associated with physical environment conditions. Second training sensor data detected by a plurality of virtual sensors are obtained. The second training sensor data is associated with simulated physical conditions of a virtual environment. A machine learning model is trained using both real-world and virtual training datasets including the first training sensor data, the second training sensor data, and respective sensor setting parameters of the plurality of real-world sensors and the plurality of virtual sensors. The real-world and virtual training datasets used to train the machine learning model include indications associated with the respective sensor parameter settings including one or more of the following: different scan line settings or different exposure settings. The machine learning model is provided for use in generating current parameters of an environment in which a vehicle operates.