Design of Active Collision Avoidance Algorithm for Driverless Cars Based on Machine Vision

With the continuous progress of society, the problem of traffic congestion is becoming increasingly serious. However, when an unmanned vehicle is driving on the highway, it is unavoidable to encounter situations such as vehicle collisions and rear-end collisions. In order to effectively solve this problem, this article proposes to use machine vision technology to deal with such events. By using a computer image recognition system, the required recognition information can be analyzed and extracted to obtain the required results. At the same time, the video data also needs to be converted into digital signals and output to the control unit to realize the automatic collision avoidance function. This article tests the performance of the active collision avoidance algorithm of driverless cars. The test results show that the recall rate of the collision avoidance algorithm is between 0.7-0.89, and the highest collision avoidance accuracy can reach 0.97. This shows that this method can greatly improve the safety performance of driverless cars and create a safer and more convenient travel environment.