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) Borlange GPS data set collected in the Swedish city of Borlange; 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
Other approaches used to characterize the vehicles velocities are: @cite_5 use the fractal dimension to analyze vehicles velocities in the data set collected by Highway Performance Measurement Project, in Beijing, China. The data were collected by using sensors on the roads which sampled the velocities in intervals of 20 . Results showed that the traffic, in the scenarios considered, have multifractal characteristics and the degree of fractality increases proportionally to traffic congestion. Moreover, the local H "older exponent (or roughness) @cite_36 was used to predict heavy traffic. This exponent can be used to measure the local rate of fractality.
@cite_36 @cite_5
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In this paper we investigate from both a theoretical and a practical point of view the following problem: Let s be a function from [0;1] to [0;1] . Under which conditions does there exist a continuous function f from [0;1] to R such that the regularity of f at x , measured in terms of Holder exponent, is exactly s(x) , for all x ∈ [0;1] ? In this paper, we applied multifractal modeling techniques to analyze the traffic data collected from the Beijing Yuquanying. The results indicated that multifractal characteristics obviously exist in the traffic system; the degree of fractality of these traffic data tends to increase as the traffic system becomes congested; the Holder exponent that measures the local rate of fractality may be used as indicators to predict the presence of the traffic congestion.