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Erschienen in:
2013 | OriginalPaper | Buchkapitel
AllAboard: A System for Exploring Urban Mobility and Optimizing Public Transport Using Cellphone Data
verfasst von : Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Rahul Nair, Fabio Pinelli, Marco Luca Sbodio
Erschienen in: Machine Learning and Knowledge Discovery in Databases
Verlag: Springer Berlin Heidelberg
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The deep penetration of mobile phones offers cities the ability to opportunistically monitor citizens’ interactions and use data-driven insights to better plan and manage services. In this context, transit operators can leverage pervasive mobile sensing to better match observed demand for travel with their service offerings. With large scale data on mobility patterns, operators can move away from the costly and resource intensive transportation planning processes prevalent in the West, to a more data-centric view, that places the instrumented user at the center of development. In this framework, using mobile phone data to perform transit analysis and optimization represents a new frontier with significant societal impact, especially in developing countries.