Intelligent Control System of Unmanned Vehicle Based on CAN Controller

Abstract

In order to enable the driverless vehicle formation controller to automatically control the driving of the fleet, an intelligent driverless vehicle control system based on the CAN controller is proposed. Expansion convolution of different expansion rates is used to obtain multi-scale target information and to fuse the feature information at different scales during upsampling to enrich the semantic information. Finally, the driverless CAN bus communication platform was established, the driverless monitoring interface was developed, and the software program was written; experiments on the steering control, speed control, voltage, current, speed, and angular speed acquisition, respectively, were performed. The experimental results show that the average semantic segmentation accuracy of the obstacles in concentrated vehicles, pedestrians, and bicycles reached 84.6%, and the detection and segmentation accuracy of the models was good. Therefore, the unmanned intelligent vehicle control system designed in this paper can meet the performance requirements of the vehicle control. No matter whether the given desired path is a straight line or a curve, the unmanned car can complete the path tracking control quickly, stably, and accurately.