Method, system and apparatus for classification of environmental conditions of a vehicle

Abstract

An automated vehicle comprises a gated camera system (16-1), a long-range LiDAR system (14), and a a control system (12) controlling an operation of the vehicle. The vehicle is further provided with a convolutional neural network, CNN, based controller for detecting environmental conditions of an operational environment of an automated vehicle. A Lidar image from the LiDAR sensor system is encoded into first feature vector (205) by a first pre-trained CNN (204), while a gated image and gated camera capture parameters from the gated camera system are encoded into a second feature vector (203) by a second pre-trained CNN (202). The first and second feature vectors (203, 205) are combined into a combined feature vector (207) that is inputted to two or more pre-trained environmental condition classifiers (210, 212, 214). Each classifier is configured to classify one environmental condition that can be used for controlling the vehicle.