Towards a model for urban mobility social simulation

Abstract

Metropolitan mobility models, 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 socio-ecological systems. The Jason Multi-modal Agent Decision Making (J-MADeM) library enables 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 CO2 emitted to the environment.