1. A system, comprising a computer having a processor and a memory, the memory storing instructions executable by the processor including instructions to: receive video data from a video data source affixed to a vehicle; receive light detecting and ranging (LIDAR) data from a LIDAR data source affixed to the vehicle; send the video data to a recurrent neural network (RNN) that includes feedback elements to provide feedback from a first layer to a second layer to identify a roadway feature; send the video data to a dynamic convolutional neural network (DCNN) to apply a convolution filter to the video data to generate a convolution image and a pooling filter to the convolution image to develop a feature map to identify the feature; send the LIDAR data to the RNN to identify the feature; send the LIDAR data to the DCNN to identify the feature; send a RNN output value and a DCNN output value to a softmax decision network to aggregate the RNN output value and the DCNN output value; determine a softmax output based on whether the RNN output value and the DCNN output value are within a range; determine a vehicle positional location on the roadway of the vehicle based on the softmax output; compare the vehicle positional location on the roadway relative to an edge of the roadway and an image from a set of training data images to determine an error rate; determine a change in a weight value for the RNN and the DCNN from the error rate; apply the change in the weight value to the RNN and the DCNN; and control at least a steering, a braking and an acceleration of the vehicle from at least the vehicle positional location of the vehicle.