Automatic driving control method aiming at low-pass obstacles

Abstract

The invention discloses an automatic driving control method aiming at a low-pass obstacle. Two-stage visual identification is carried out on image content collected in continuous driving process of automatic driving vehicle, accurate information of target obstacle is obtained, and mapping imaging principle is combined; an existing distance measuring method based on a phase and time difference relation is improved into a mode of solving the distance of a target obstacle through a plane geometrical relation, and the method is particularly suitable for distance measurement and calculation of low-pass obstacles; and in order to ensure the accuracy of the distance measurement result, a plurality of solving results are fused, and finally, the identified target obstacle information and the accurate distance measurement result are utilized to realize the adaptive obstacle avoidance decision with the obstacle type as the guide. According to the invention, accurate detection of the low-pass obstacle is realized, the distance measurement process is significantly simplified, driving safety measures can be flexibly adjusted in cooperation with the detection result of the low-pass obstacle, and the purpose of reasonably avoiding or passing through the low-pass obstacle in a targeted manner is achieved.

Description

technical field [0001] The invention relates to the field of automatic driving, in particular to an automatic driving control method for low-passage obstacles. Background technique [0002] Self-driving cars realize the perception of the environment through high-precision maps + positioning systems, radar detection systems, and high-definition cameras. The radar detection system can realize the distance measurement of obstacles, the high-definition camera collects images, and through machine vision recognition, it can be judged whether the obstacle is a person, a car or other things. Among them, the radar is suitable for detecting objects with a certain height within the sensing range, but the road conditions of the vehicle are more complicated. It is difficult to achieve correct detection. The low-pass obstacle mentioned here refers to the obstacle that occupies a small interval in the Z direction relative to the vehicle coordinate system (it can be simply understood as a ...

AI Technical Summary

Problems solved by technology

Among them, the radar is suitable for detecting objects with a certain height within the sensing range, but the road conditions of the vehicle are more complicated. It is difficult to achieve correct detection. The low-pass obstacle mentioned here refers to the obstacle that occupies a small interval in the Z direction relative to the vehicle coordinate system (it can be simply understood as a relatively low obstacle); and the installation Although the lidar on the self-driving car can detect low-pass obstacles and draw point cloud data, it is also limited by the capture angle of the target scene object, and the imaging resolution of low-pass obstacles is not high. Too high, the generated 3D point cloud data is also difficult to accurately describe the distance of low-pass obstacles

[0003] Therefore, the ranging effect of the existing technology on low-pass obstacles is not ideal

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