Abstract: A method for identifying hazardous conditions during vehicle operation includes: accessing data from a sensor corresponding to images of one or more other vehicles; computing, with a machine-learned model, a threat estimate for the one or more other vehicles based at least in part on the data from the sensor; and transmitting a threat alert to a driver interface of an ego vehicle.

Abstract: A method for identifying a vehicle of interest includes: accessing data corresponding to a vehicle of interest alert; accessing data from a sensor corresponding to images of one or more other vehicles; computing, with a machine-learned model, a vehicle of interest match estimate for the one or more other vehicles based at least in part on the data from the sensor; and computing a vehicle of interest identification.

Abstract: A method for identifying hazardous conditions during vehicle operation includes: accessing data from a sensor corresponding to images of one or more other vehicles; computing, with a machine-learned model, a threat estimate for the one or more other vehicles based at least in part on the data from the sensor; and transmitting a threat alert to a driver interface of an ego vehicle.

Abstract: A method of mitigating aquaplaning by a vehicle is disclosed. The method comprises creating an aquaplaning identification model using simulated data and deploying the model in a vehicle onboard computer. During vehicle operation, data is collected from one or more image sensors installed on the vehicle and directed to the model disposed on the onboard computer. The results of the model are deployed to a server cloud wherein the results are processed in a neural net and the model is updated in the server cloud and an updated model is deployed to the vehicle onboard computer in a software loop. The method of developing the model is also disclosed.