Method and a system of determining LiDAR data degradation degree

A computer-implemented method of determining a degree of point cloud data degradation of a Light Detection and Ranging (LiDAR) sensor of a Self-Driving Car (SDC) using a Machine-Learning Algorithm (MLA), the method being executable by at least one processor communicatively coupled to the LiDAR sensor, the method comprising, during a training phase, training the MLA by:

• receiving, by the at least one processor from the LiDAR sensor, training sensed data including a given training point cloud representative of a given portion of a surrounding area of the SDC;
• determining, by the at least one processor, based on the given training point cloud, a plurality of LiDAR features associated with the given portion of the surrounding area of the SDC;
• receiving, by the at least one processor from a camera sensor of the SDC, a respective training image representative of the given portion of the surrounding area of the SDC,
• the respective training image having been generated, by the camera sensor, at a same time as the sensed data by the LiDAR sensor;
• projecting, by the at least one processor, the given training point cloud onto the respective training image to generate a merged representation of the given portion of the surrounding area of the SDC including statistical data of coverage of training objects present in the respective image with LiDAR points;
• determining, by the at least one processor, for each training object present in the given portion of the surrounding area of the SDC, based on the statistical data, a plurality of enrichment features;
• receiving, by the at least one processor, for the merged representation of the given portion, a respective label indicative of a degradation degree of the training sensed data generated by the LiDAR sensor;
• generating, by the at least one processor, based on the plurality of LiDAR features, the plurality of enrichment features associated with each training object present in the given portion of the surrounding area of the SDC, and the respective label, a given training feature vector of a plurality of training feature vectors;
• training, by the at least one processor, the MLA based on the plurality of training feature vectors to determine an in-use degree of degradation of in-use sensed data of the LiDAR sensor representative of in-use objects in the surrounding area of the SDC.