Vital problems in transportation such as mobility and safety of transportation, especially in highways and road ways, are considered as very important nowadays. Road traffic monitoring aims at acquisition and analysis of traffic signs, such as presence and numbers of vehicles, and automatic driver warning systems developed mainly for localization and safety purposes. In the past some methods have been presented for road and vehicle recognition, which either the accuracy of the results was not acceptable, or tolerable results were achieved only in specific conditions. This article presents a new approach for recognizing the vehicle and the road in satellite high-resolution images in non-urban areas. One of the results of this research was to control the traffic jam in roads and to recognize the traffic density quickly and accurately.. For recognition, they used feature extraction, image processing and machine learning like Hough transform, Gradient, and thresholding operation for road detection and feature extraction and SVM for Vehicles' detection. The average of results is about 85 percent and it shows that the used procedure has the suitable efficiency.