Free space detection using rgb-polarimetric images

A method for use with a free space estimation and visualization system, comprising:

• collecting red-green-blue (“RGB”) data and lidar data of a target drive scene using an RGB camera and a lidar sensor, respectively;
• generating, via a first neural network of a training computer, pseudo-labels of the target drive scene;
• collecting RGB-polarimetric data via an RGB-polarimeric camera;
• training a second neural network of the training computer using the RGB-polarimetric data and the pseudo-labels;
• using the second neural network in an electronic control unit (“ECU”) of the host vehicle as a run-time neural network to estimate an amount of free space in a potential driving path of the host vehicle as estimated free space, including processing additional RGB-polarimetric image data via the run-time neural network;
• and
• executing a control action aboard the host vehicle in response to the estimated free space.

A host vehicle, comprising:

• a vehicle body;
• road wheels connected to the vehicle body;
• and
• a free space estimation and visualization (“FSEV”) system including:
• a camera connected to the vehicle body and configured to collect red-green-blue (“RGB”)-polarimetric image data of drive environs of the host vehicle, including a potential driving path thereof, and
• an electronic control unit (“ECU”) in communication with the camera and configured to:
• receive the RGB-polarimetric image data from the camera;
• estimate an amount of free space in the potential driving path as estimated free space, including processing the RGB-polarimetric image data via a run-time neural network;
• and
• execute a control action aboard the host vehicle in response to the estimated free space.