Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Understanding Urban Dynamics from Taxi GPS Traces

Understanding Urban Dynamics from Taxi GPS Traces
View Sample PDF
Author(s): Lin Sun (TELECOM SudParis, France), Chao Chen (TELECOM SudParis, France) and Daqing Zhang (Institut Telecom SudParis, France)
Copyright: 2014
Pages: 19
Source title: Creating Personal, Social, and Urban Awareness through Pervasive Computing
Source Author(s)/Editor(s): Bin Guo (Northwestern Polytechnical University, China), Daniele Riboni (University of Milano, Italy) and Peizhao Hu (NICTA, Australia)
DOI: 10.4018/978-1-4666-4695-7.ch013


View Understanding Urban Dynamics from Taxi GPS Traces on the publisher's website for pricing and purchasing information.


The GPS traces collected from a large taxi fleet provide researchers novel opportunities to inspect the urban dynamics in a city and lead to applications that can bring great benefits to the public. In this chapter, based on a real life large-scale taxi GPS dataset, the authors reveal the unique characteristics in the four different trace stages according to the passenger status, study the urban dynamics revealed in each stage, and explain the possible applications. Specifically, from passenger vacant traces, they study the taxi service dynamics, introduce how to use them to help taxis and passengers find each other, and reveal the work shifting dynamics in a city. From passenger occupied traces, they introduce their capabilities in monitoring and predicting urban traffic and estimating travel time. From the pick-up and drop-off events, the authors show the passenger hotspots and human mobility patterns in a city. They also consider taxis as mobile GPS sensors, which probe the urban road infrastructure dynamics.

Related Content

Bin Guo, Yunji Liang, Zhu Wang, Zhiwen Yu, Daqing Zhang, Xingshe Zhou. © 2014. 20 pages.
Yunji Liang, Xingshe Zhou, Bin Guo, Zhiwen Yu. © 2014. 31 pages.
Igor Bisio, Alessandro Delfino, Fabio Lavagetto, Mario Marchese. © 2014. 33 pages.
Kobkaew Opasjumruskit, Jesús Expósito, Birgitta König-Ries, Andreas Nauerz, Martin Welsch. © 2014. 22 pages.
Viktoriya Degeler, Alexander Lazovik. © 2014. 23 pages.
Vlasios Kasapakis, Damianos Gavalas. © 2014. 26 pages.
Zhu Wang, Xingshe Zhou, Daqing Zhang, Bin Guo, Zhiwen Yu. © 2014. 18 pages.
Body Bottom