In this paper, a fine vehicle model measurement method based on plane distance measurement is proposed. This method involves several steps. First, the vehicle image is captured using a camera and then preprocessed. The key feature points of the vehicle are extracted using image processing and the faster regional convolutional neural network (R-CNN) algorithm model. Next, the feature points are accurately measured using a plane ranging algorithm, enabling the analysis of fine models of heavy vehicles, such as the number of axles, lanes, and speed information. The experimental results demonstrate that the proposed fine vehicle measurement method achieves excellent results in measuring vehicle size. Compared with conventional measurement methods, this method offers higher measurement precision and accuracy. Additionally, this method significantly reduces the measurement time and workload while improving measurement efficiency.