MUSA–I. towards New Social Tools for Advanced Multi-Modal Transportation in Smart Cities

Abstract

Urban mobility optimization problem has a great focus in the context of Smart cities. To its solution a very important factor is the transport demand, which is mostly inferred using Big Data and Artificial Intelligence techniques from Automatic Fare Collection (AFC) and mobile devices data. In this paper a novel approach, based on Transport Demand Management techniques is proposed, using technology to produce a more active social involvement in the planning and optimization of mobility. This paper describes, a first step to this long-term objective, the general architecture and current implementation of an explicit multi-modal transport demand system for Smart Cities, which is being developed in the frame of MUSA—I project in the city of Madrid.