この出願は、車両走行可能検出方法、自律走行支援システム、及び自律走行車両を開示する。本方法は、ニューラル・ネットワークを使用して、カメラ装置によって取得された画像データを処理して、障害物の第１の確率分布を取得することと、レーダ・エコー信号のエコー幅及び飛行時間に基づいて障害物の第２の確率分布を取得することと、障害物の第１の確率分布及び障害物の第２の確率分布に基づいて、確率によって表される車両の走行可能領域を取得することであって、確率は、車両が領域を通って走行できない確率である、取得することと、を含む。

This application discloses a vehicle drivable area detection method, an autonomous driving assistance system, and an autonomous driving vehicle. The method includes: processing, by using a neural network, image data obtained by a camera apparatus, to obtain a first probability distribution of an obstacle; obtaining a second probability distribution of the obstacle based on a time of flight and an echo width of a radar echo signal; and obtaining, based on the first probability distribution of the obstacle and the second probability distribution of the obstacle, a drivable area of a vehicle represented by a probability, where the probability is a probability that the vehicle cannot drive through the area. The autonomous driving assistance system includes a camera apparatus, at least one radar, and a processor. The system is configured with the technical solutions that can implement the method. The autonomous driving vehicle includes the foregoing autonomous driving assistance system. In the method in this application, two sensors: a camera apparatus and a radar are integrated, distribution information about the obstacle obtained by the two sensors is fused, and the drivable area of the vehicle obtained after fusion is represented in a form of a probability. Therefore, information about the obstacle around the vehicle can be comprehensively obtained, so that a detection blind spot caused by a blind spot of the camera apparatus or a detection range of the radar is avoided.