The origin of the project comes from the need of classifying any city traffic network, in order to regulate it in smart ways later. Knowing this previous city classification is a fast way to have a first impression of the city, with some parameters that clearly describe its structure and its connections with other cities. These steps can save time to the researchers or, in terms of business, they can save money. The main objective is to do an analysis of typical traffic networks. What this means is to classify any city by its traffic network topology. The development of the project will be done by using the MATLAB programming language and observing the results. The first step, in order to carry out this project and achieve the objectives, is to do a deep literature research of the main topics. This literature investigation has been divided in five parts, considered as the main fields of study: map data (using reliable information is crucial to do a good study of different cities and compare them), graph theory (the basis of mathematics in this project), social network analysis (a strategy for looking into social networks and structures, by using mathematical formulations extracted from graph theory), traffic network topologies (many studies propose measures to characterize networks) and intersections (the classification of streets unions). Then, an experimental process is proposed, by using MATLAB and parameters chosen from other studies observations and the project limits (time of realization and difficulty to program). The main parameters here used, plotted in graphs, are: distance between two intersections which are connected by a street, the angle between the streets that arrive to an intersection, the degree of a node (number of streets that arrive and leave an intersection) and the significant orientation of the streets of a node (respect to 0). Then, other parameters are also displayed, as number of nodes, number of nodes, alpha index, beta index, etc. The process holds all the MATLAB functions and is divided in four parts. At first, the part which converts the OpenStreetMap (source of map data) file to MATLAB useful language. Then, to fix the matrices and to fix the map (two different steps) obtained in the first step is necessary. Finally, the functions to obtain results and characteristics are programmed. Once explained the functions, the results are summarized in graphs and tables, and then are analyzed. This analysis gives a global idea of the maps, by comparing 7 maps at the same time. The grids are totally recognized by their unmistakable characteristics, but the other types of maps are classified by the values obtained. In conclusion, this project studies a set of parameters but it is not a closed project, it can be extended and improved by whoever wants to.