FUZZY LOGIC BASED MODELING OF TRAFFIC FLOWS INDUCED BY REGIONAL SHOPPING MALLS

In this paper, we present an agent-based model aiming at supporting decisions about the planning of shopping malls (SM), with a main focus about their environmental impact. The model forecasts the traffic flows induced by SM at the regional level on the whole road network of Canton Ticino (Switzerland), and has been used by the public administration as a support to decide master plan rules. The system has been modeled as an interaction space, a new type of modeling framework that includes both multi-agent systems and cellular automata as a particular case. We define a grammar to specify different agents' trips, and we associate a fuzzy logic based indicator to each one of these specifications. Similarly, we define attractiveness indicators for zones containing economical activities related to agents' trips. The use of these indicators permits to obtain agents' location choices of secondary activities with a great computational efficiency. Simulations include several environmental indicators, like concentrations of nitrogen dioxide, counting changes in a given small part of a road or an estimation of roads' level of service.