A Multi-Agent Proposal For Efficient Bike-Sharing Usage

Urban transportation systems have received a special interest in the last few years due to the necessity to reduce congestion, air pollution and acoustic contamination in today's cities. Bike sharing systems have been proposed as an interesting solution to deal with these problems. Nevertheless, shared vehicle schemes also arise problems that must be addressed such as the vehicle distribution along time and across space in the city. Differently to classic approaches, we propose the architecture for a muti-agent system that tries to improve the efficiency of bike sharing systems by introducing user-driven balancing in the loop. The rationale is that of persuading users to slightly deviate from their origins/destinations by providing appropriate arguments and incentives, while optimizing the overall balance of the system. In this paper we present two of the proposed system's modules. The first will allow us to predict bike demand in different stations. The second will score stations and alternative routes. This modules will be used to predict the most appropriate offers for users and try to persuade them.