Fuzzy Ant Colony Paradigm for Virtual Pedestrian Simulation

Abstract

Pedestrian's studies are applied benefit and deployed in many areas; including public trip planning, and human factors analysis for building evacuation, or other situations where masses of people gather such as sporting events, etc. In this paper we describe a simulation system for virtual pedestrians. We mix the concept of fuzzy ant given by Ant Colony paradigm and associated cellular automaton model. We have adopted a fuzzy model for its particular ability to better represent uncertainty and imprecision about space perception. In our model we use it to represent virtual pedestrian's fuzzy pedestrian's desirability or visibility. A software solution was developed for this purpose. The Simulation results confirm predictions given by the first-order traffic flow theory. The proposed fuzzification is a preliminary step to consider other factors. The given system in its deployment phase will be integrated for pedestrians' accidents analysis in urban transportation networks. The strength of our model takes advantage in using explicit Ant Colony model and on projecting fuzzy theory to apprehend pedestrians' perceptions.