Application of collaborative information exchange in urban public transport: the Seamless Mobility solution

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Tânia Daniela Fontes
Marta Campos Ferreira
Vera Lúcia Costa
Teresa Galvão
José Luís Borges
João Falcão Cunha
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Contemporary urban transportation networks are facing challenges to address the growing needs of mobility, all the while improving their economic gains and environmental sustainability. Several studies demonstrate that competitive alternatives to individual private transport are able to address these challenges, such as public transportation services. Thus, the need for optimising their operational efficiency and offer user-centric service delivery arises, with a range of challenges related to the inherent complexity of urban transportation networks as well as the range of dynamic elements involved in such systems. An innovative approach to this problem leverages personal mobile devices in combination with collaborative exchange of information. In this study a system was developed to combine information provided by travellers with data from public transport operators. The result is a rich model of the transportation network that enables the distribution of information in a personalized way and in real-time: the Seamless Mobility solution. Large-scale and expensive infrastructures, such as existing ticketing systems, constitute a threat to such flexibility and traveller access to services. As a result, a distributed architecture was targeted with the goal of integrating personal mobile devices in the infrastructure, with benefits for travellers and transport operators. The proposed solution integrates a broad scope of challenges, including application of secure mobile payments methods, data aggregation from different components and distribution based on relevance techniques. With the implementation of this solution we expect to positively impact the way travellers and transport operators interact, and contribute towards mobility services that are more agile and adequate, taking into account that mobility patterns vary from person to person, seasonally, and even throughout a day. (C) 2016 The Authors. Published by Elsevier B.V.