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arXiv · 1601.06128

RioBusData: Outlier Detection in Bus Routes of Rio de Janeiro

Aline Bessa·Fernando de Mesentier Silva·Rodrigo Frassetto Nogueira·Enrico Bertini·Juliana Freire
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Abstract

Buses are the primary means of public transportation in the city of Rio de Janeiro, carrying around 100 million passengers every month. Recently, real-time GPS coordinates of all operating public buses has been made publicly available - roughly 1 million GPS entries each captured each day. In an initial study, we observed that a substantial number of buses follow trajectories that do not follow the expected behavior. In this paper, we present RioBusData, a tool that helps users identify and explore, through different visualizations, the behavior of outlier trajectories. We describe how the system automatically detects these outliers using a Convolutional Neural Network (CNN) and we also discuss a series of case studies which show how RioBusData helps users better understand not only the flow and service of outlier buses but also the bus system as a whole.

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Aline Bessa, Fernando de Mesentier Silva, Rodrigo Frassetto Nogueira, Enrico Bertini, Juliana Freire. 2016-01-22. RioBusData: Outlier Detection in Bus Routes of Rio de Janeiro. https://arxiv.org/abs/1601.06128

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