A probabilistic approach for road network analysis

Abstract

Complex networks are networks whose structure is irregular, complex and which evolves over time and are used in various branches of science and technology, such as in biochemistry, in the study of interactions in quantum field theory, in the study of IT processes, topologies in geographical databases and also on the web, in social networks such as Facebook and Linkedin and in the Google model. The term “complex” itself derives from the Latin cum (together)—plexus (intertwined), “intertwined together”: it highlights that a complex network system is composed of a set of parts connected and “intertwined” in such a way that the result (the effect produced) is different from the sum of the constituent parts. Therefore, the behavior of a complex system cannot be inferred by a simple analysis of the elements that compose it, but it is necessary to carry out a systematic examination of the interactions that are generated between them and the constraints that determine their operation. In this chapter we show how the probability of intersections for the Road Network Analysis (RNA) can be useful. We use a geometric probabilities approach for transportation planning operations. We show the utility of the probability of intersections in the determination of a classification rule for raster conversions in Geographical Information System (GIS) and GRASS GIS.