DIRTY MONOCULAR CAMERA DETECTION METHODS FOR AUTONOMOUS DRIVING VEHICLE

Systems and methods are disclosed for identifying a dirty camera in a monocular camera comprising n cameras. For each of one or more cycles, a dirty counter variable for each of the n cameras is set to 0. For each of the n cameras, an image is captured from the camera and an image metric is determined for the image, e.g. brightness and/or contrast. If the image metric is 10% greater, or 10% less, than the image metric for any of the other n−1 cameras in the monocular camera, then that camera is determined to be dirty and a corrective action is taken, such as sending an alarm to an occupant the vehicle or initiating a cleaning operation. If the dirty condition persists for a camera that has been cleaned within a threshold period of time (i.e., recently), then an alarm is sent to an operator of the vehicle.