AllAboard: Visual Exploration of Cellphone Mobility Data to Optimise Public Transport | IEEE Journals & Magazine | IEEE Xplore

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


Abstract:

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 ser...Show More

Abstract:

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.
Published in: IEEE Transactions on Visualization and Computer Graphics ( Volume: 22, Issue: 2, 01 February 2016)
Page(s): 1036 - 1050
Date of Publication: 03 June 2015

ISSN Information:

PubMed ID: 26731450

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