Fast Agent-Based Solution to Evaluate the Matching of Public Transport Offer vs Citizen Mobility Demand

Public transportation is fundamental to support the mobility demand of citizens and drive the development of sustainable and green mobility in smart city scenarios. However, planning an efficient public transport system is a challenging task since it requires on the one hand to deploy a widespread, fast, and reliable system able to fully respond to the mobility demand. On the other hand, financial sustainability must be guaranteed by avoiding excessive and unfruitful expenses that could in the long run hamper the whole transportation system. Therefore, to find such a balance, there is the need for tools able to analyze and evaluate the match between the transportation offer and the mobility demand to allow city officers and decision makers to plan optimal services. To respond to this necessity, in this paper we propose an agent-based solution, that, differently from available software, is easily configurable, requires minimal input, and is able to carry out simulation in a timely manner yet providing useful and accurate insights. Moreover, the proposed solution can be easily adopted for what-if analysis frameworks, thus realizing an extremely valuable tool for smart city transportation planning.