Large-Scale Agent-Based Transport Model for the Metropolitan City of Messina

Abstract

Complex traffic dynamics can be modeled in real time through simulation models and methods which are attracting more and more research efforts. In particular, agent-based models based on agent behaviors with local plans or strategies can be useful for transportation study areas. These models can be used to solve real-world policy problems simulating certain regions or cities. In this paper, we implemented an agent-based transport model for analyzing traffic in the metropolitan city of Messina (Sicily, Italy). We created a scenario using (i) the Messina road network information from OpenStreetMap, (ii) public transport supply data of the Municipality of Messina from General Transit Feed Specification, and (iii) census data related to the six districts of Messina. Then, we made a preliminary analysis of the generated simulation output computing average travel time by agent trip mode, average activity duration and link volumes. Our scenario can be extended and adapted to solve specific problems related to the mobility of individuals in Messina.

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