Characterization of vehicle behavior with information theory

Andre L.L. Aquino (), Tamer S.G. Cavalcante, Eliana S. Almeida, Alejandro C. Frery and Osvaldo A. Rosso

The European Physical Journal B: Condensed Matter and Complex Systems, 2015, vol. 88, issue 10, 1-12

Abstract: This work proposes the use of Information Theory for the characterization of vehicles behavior through their velocities. Three public data sets were used: (i) Mobile Century data set collected on Highway I-880, near Union City, California; (ii) Borlänge GPS data set collected in the Swedish city of Borlänge; and (iii) Beijing taxicabs data set collected in Beijing, China, where each vehicle speed is stored as a time series. The Bandt-Pompe methodology combined with the Complexity-Entropy plane were used to identify different regimes and behaviors. The global velocity is compatible with a correlated noise with f − k Power Spectrum with k ≥ 0. With this we identify traffic behaviors as, for instance, random velocities (k ≃ 0) when there is congestion, and more correlated velocities (k ≃ 3) in the presence of free traffic flow. Copyright EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2015

Keywords: Statistical and Nonlinear Physics (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1140/epjb/e2015-60384-x

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