Recently, 5G commercialization issues and standardization of WAVE communication have been done on V2X communication of autonomous vehicles. In this paper, we propose an algorithm for predicting the communication performance of multichannel V2X with a vision sensor. The proposed method recognizes the surrounding environment as a vision sensor and provides information to the TCU board to select optimal parameters. The sensing system integrates camera and LiDAR sensor data into a single data set. We applied the CNN-based object detection algorithm to the fusion sensor and recognized the driving environment. We defined the situation that affects the communication performance and measured the accuracy by perceiving the scenario. This algorithm can optimize the communication channel and select the communication channel suitable for the driving environment in advance to improve the communication stability.