(*) Dipartimento di Ingegneria Civile e Ambientale, Università di Catania (**) Dipartimento di Sociologia e Metodi delle Scienze Sociali, Università di Catania (***) Dipartimento di Fisica e Astronomia, Università di Catania, e INFN Sez.Catania Agent - based simulation of pedestrian behaviour di Salvatore Caprì(*), Cesare Garofalo(**), Matteo Ignaccolo(*), Giuseppe Inturri(*), Alessandro Pluchino(***), Andrea Rapisarda(***), Salvatore Tudisco(***) 1 Introduction Walking is the most sustainable mode of transport, involves 75% of all trips under a kilometre, is the first and last segment of every travel, affects the level of service of important transport infrastructure such as airports and railway stations, is of fundamental importance in fields related to urban planning, emergency, disaster planning. Nevertheless, transportation engi- neering is traditionally focused on motorized travel and therefore there is a general lack of research and methods to model pedestrian behaviour. Existing transport pedestrian models can be roughly separated in ana- lytical models and micro-simulations. The first ones include “before and after” methods, regression analysis models (Older, 1968; Pushkarev, 1971), analogies with fluids, gas kinetics and other physical flow systems (Helbing, 1992; Henderson, 1974), entropy maximization (Butler, 1978), dynamic network analysis with flow models calibrated on the basis of data collected (Di Gangi, 2007), discrete choice model to predict pedestrians’ route choice (Antonini, 2006; Ignaccolo 2006), stochastic queuing and Markovian models (Mitchell, 2001). They use mathematical models to calculate average pedestrian flows along a path, but are not able to include peculiar aspects of pedestrian (human) be- haviour. The second ones simulate the movement of each single pedestrian fol- lowing a set of pre-determined rules of behaviour, and are applicable to a greater variety of situations, such as closed spatial environments, or un- usual demand flows, where local dynamics of individual decision making is strongly affected by geometry, randomness, social preferences, local and collective behaviour of other individuals. Some simulation approaches are based on the concept of “social force”, that include a sort of internal moti-