Using Fuzzy Cellular Automaton Graph Coloring Algorithm for Classifying Dangerous Traffic Region

With regard to roads and traffic routes to different levels of risk, it can be determined which of these sections of these roads and paths are more likely to crash and based on this risk, the maximum speed and the various authorized routes As low as possible. In this study, using a fuzzy graph as a math model of the urban chip network, we present a method for determining the different areas of traffic in terms of the level of risk. Based on the probability of accidents, traffic areas fall into three low risk areas (green), in the danger zone (yellow) and high risk (red). In this study, a graph coloring method is presented that includes two automatic solitary and fuzzy logic segments. In this method, we perform the coloring of the existing graph using a fuzzy automaton system. In this study, the amount of α indicates the quality sensitivity of that road and it has been shown that increasing the amount of α will increase the number of most dangerous routes and increase the sensitivity to driving quality.