AllAboard: Visual Exploration of Cellphone Mobility Data to Optimise Public Transport

The deep penetration of mobile phones offers cities the ability to opportunistically monitor citizens' mobility and use data-driven insights to better plan and manage services. With large scale data on mobility patterns, operators can move away from the costly, mostly survey based, transportati...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2016-02, Vol.22 (2), p.1036-1050
Main Authors: Di Lorenzo, G., Sbodio, M., Calabrese, F., Berlingerio, M., Pinelli, F., Nair, R.
Format: Article
Language:English
Subjects:
Antennas
Cell Phone
Cell phones
Cities
Computer Graphics
Cote d'Ivoire
Data analysis
Data Mining
Developing countries
Humans
LDCs
Mobile handsets
Operators
Optimization
Planning
Public transportation
Quality of service architectures
Software
Spatio-Temporal Analysis
Transportation
Transportation planning
Travel demand
Urban areas
Urban transportation
Visualization
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Summary:The deep penetration of mobile phones offers cities the ability to opportunistically monitor citizens' mobility and use data-driven insights to better plan and manage services. With large scale data on mobility patterns, operators can move away from the costly, mostly survey based, transportation planning processes, 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. In this paper we present AllAboard, an intelligent tool that analyses cellphone data to help city authorities in visually exploring urban mobility and optimizing public transport. This is performed within a self contained tool, as opposed to the current solutions which rely on a combination of several distinct tools for analysis, reporting, optimisation and planning. An interactive user interface allows transit operators to visually explore the travel demand in both space and time, correlate it with the transit network, and evaluate the quality of service that a transit network provides to the citizens at very fine grain. Operators can visually test scenarios for transit network improvements, and compare the expected impact on the travellers' experience. The system has been tested using real telecommunication data for the city of Abidjan, Ivory Coast, and evaluated from a data mining, optimisation and user prospective.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2015.2440259