An understanding of human dynamics in urban subway traffic from the Maximum Entropy Principle

Nuo Yong, Shunjiang Ni, Shifei Shen and Xuewei Ji

Physica A: Statistical Mechanics and its Applications, 2016, vol. 456, issue C, 222-227

Abstract: We studied the distribution of entry time interval in Beijing subway traffic by analyzing the smart card transaction data, and then deduced the probability distribution function of entry time interval based on the Maximum Entropy Principle. Both theoretical derivation and data statistics indicated that the entry time interval obeys power-law distribution with an exponential cutoff. In addition, we pointed out the constraint conditions for the distribution form and discussed how the constraints affect the distribution function. It is speculated that for bursts and heavy tails in human dynamics, when the fitted power exponent is less than 1.0, it cannot be a pure power-law distribution, but with an exponential cutoff, which may be ignored in the previous studies.

Keywords: Human dynamics; Maximum Entropy Principle; Power-law distribution; Subway traffic (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:456:y:2016:i:c:p:222-227

DOI: 10.1016/j.physa.2016.03.071

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