Threatening degree calculation method in automatic driving, target selection method and application

Abstract

The invention provides a threatening degree calculation method, a target selection method concerned in the automatic driving, an automatic driving auxiliary device, an automatic driving device and a vehicle-mounted device. The threatening degree calculation method is used for calculating the threatening degree of a target object to an object body in the automatic driving, and comprises steps of acquiring a longitudinal distance and a transverse distance of the target object relative to the object body, and first horizontal speed and first transverse speed of the target object; and based on the longitudinal distance, the transverse distance, the first horizontal speed and the first transverse speed, calculating the threatening degree. According to the invention, precise defining of the threatening degree of the target object is facilitated; targets can be timely recognized and selected; and improved automatic driving is achieved.

Description

technical field [0001] The present invention generally relates to the field of automatic driving, and more specifically, relates to a method for calculating the threat degree of an object concerned by automatic driving, a method for selecting a target, an automatic driving assistance device, an automatic driving device, and a vehicle-mounted device. Background technique [0002] With the advancement of science and technology, self-driving technology has also been greatly developed, especially cars that apply self-driving technology. At present, the high-end configuration of many product models has automatic driving functions. The sensors carried by this type of vehicle generally include visual sensors, ultrasonic sensors, millimeter-wave radars, and lidars. These sensors usually give movement information of dozens of targets after data processing. If there is no data fusion processing for various types of sensors, the number of detected targets will be more. How to select ...

AI Technical Summary

Problems solved by technology

[0003] The existing technology lacks an effective judgment mechanism for the many targets involved in the autonomous driving scene, so that it is impossible to screen out the most worthy of attention and continuous tracking.

This leads to the lack of effective target information input at the motion control end of automatic driving, which affects the motion control in automatic driving, thus causing a higher risk of automatic driving

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