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A MULTI AGENT SYSTEM MODELLING AN INTELLIGENT TRANSPORT SYSTEM 135 X A MULTI AGENT SYSTEM MODELLING AN INTELLIGENT TRANSPORT SYSTEM Vincenzo Di Lecce 1 , Alberto Amato 1 , Domenico Soldo 2 , Antonella Giove 1 1 Politecnico di Bari – DIASS 2 myHermes S.r.l Italy 1. Introduction Nowadays, the globalization is one of the most significant phenomena of contemporary life. There are many debates about the real meaning of the globalization, its roots, effects and future. Among the most important aspects of the globalization is surely the global transportation system. In this framework it is clear how the availability of an advanced integrated transportation system, for moving goods and people as quickly as possible all around the world, is a crucial requirement that cannot be ignored in any case, but actually accomplished in the best way possible. In (Frank and Engelke, 2000) there is a remarkable work of review highlighting the steady interaction between transportation systems and human activities and how the former ones have a strong impact on the organization of the built environment. These ideas give explanation for the increasing interest that the scientific community has shown in the field of the transportation systems. The recent improvements in ICT allow for the implementation of novel and pervasive systems. Indeed, in these days a wide spread of the Global Position System (GPS) and communication technologies (e.g. GSM, GPRS and UMTS network) has led to the implementation of interesting Intelligent Transportation System (ITS). These systems try to improve the optimization of many transportation system aspects such as vehicles, loads, routes and (overall) safety just by using these new technologies. Route planning is an optimization problem that has been studied extensively in the past decades. Dijkstra’s algorithm (Dijkstra, 1959) is the most well-known algorithm for determining the shortest path from one location to all other locations in a road network. Moreover it is noteworthy to mention other significant shortest path algorithms e, such as the Bellman-Ford algorithm (Bellman, 1958; Ford Jr. and Fulkerson, 1962), the D’Esopo-Pape algorithm (Pape, 1974), etc. An overview in this regard is given by (Bertsekas, 1998). One of the biggest problems of these algorithms is the huge dimension of the solution space. This fact led the researchers to use parallel computing (Delle Donne et al., 1995) and/or to propose new heuristic methods often based on artificial intelligence techniques (Suzuki et al., 1995; Pellazar, 1998).  corresponding author 9 www.intechopen.com

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