A J-MADeM Agent-Based Social Simulation to Model Urban Mobility

The mobility models followed within metropolitan areas, mainly based on the massive use of the car instead of the public transportation, will soon become unsustainable unless there is a change of citizens’ minds and transport policies. The main challenge related to urban mobility is that of getting free-flowing greener cities, which are provided with a smarter and accessible urban transport system. In this paper, we present an agent-based social simulation approach to tackle this kind of social-ecological systems. The Jason Multi-modal Agent Decision Making (JMADeM) library enable us to model and implement the social decisions made by each habitant about how to get to work every day, e.g., by train, by car, sharing a car, etc. In this way, we focus on the decision making aspects of this problem at a micro level, instead of focussing on spatial or other macro issues. The first results show the different outcomes produced by societies of individualist and egalitarian agents, in terms of the average travel time, the use of the urban transportation and the amount of

CO

2

emitted to the environment.