Franco Callegati, Maurizio Gabbrielli, Saverio Giallorenzo, Andrea Melis, and Marco Prandini

Abstract

Multi-modal travelling is a common phenomenon. However, planning multi-modal journeys is still an unstructured and time-consuming experience for customers: they lose time assembling a comprehensive plan out of disparate data, spread over a multitude of information systems — each corresponding to a different company responsible for one of the legs in the journey. Also transport operators are affected by the sparsity of the transportation market, as they might lose potential customers who could not find or know about their services. In this paper, we propose Mobility as a Service (MaaS) as a solution to such problems. Key element of MaaS is that MaaS operators can aggregate solutions of multiple providers to deliver dynamic, transparent multi-modal travels to their users, who experience transportation as managed directly by a single operator. However, given the volume and sparsity of the transportation market, we argue that MaaS operators cannot rely on one-to-one, custom contracts of usage with single mobility operators. Instead, we envision the creation of platforms that automatise the marketing of services for mobility among many mobility providers.

In this work, we detail the required features of a general software platform for such a MaaS market. In particular, we provide a precise definition of MaaS through the MaaS Stack — a tiered view of the components needed by entities to join the MaaS market. Then, through the lens of the MaaS Stack, we elicit the features of an enabling software platform. Finally, to validate our approach, we present a compliant prototype, called SMAll, and discuss its main design choices, among which: i) how SMAll supports the creation of a federation-based MaaS market and ii) how microservices — an emerging architectural style that fosters cohesiveness and minimality of components — enhance flexibility and let the platform and the services of its members efficiently scale according to dynamic demands.

  • Link to the Paper, accepted at ITSC’17