Detection of Steady State in Pedestrian Experiments

Weichen Liao (), Antoine Tordeux (), Armin Seyfried (), Mohcine Chraibi (), Xiaoping Zheng () and Ying Zhao ()
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Weichen Liao: Beijing University of Chemical Technology
Antoine Tordeux: Forschungszentrum Jülich GmbH
Armin Seyfried: Forschungszentrum Jülich GmbH
Mohcine Chraibi: Forschungszentrum Jülich GmbH
Xiaoping Zheng: Tsinghua University
Ying Zhao: Beijing University of Chemical Technology

A chapter in Traffic and Granular Flow '15, 2016, pp 73-79 from Springer

Abstract: Abstract Initial conditionsLiao, Weichen could have strong influencesTordeux, Antoine on the dynamics of pedestrianSeyfried, Armin experiments. Thus, a carefulChraibi, Mohcine differentiation between transientZheng, Xiaoping state and steady state is important and necessary for a thoroughZhao, Ying study. In this contribution a modified CUSUM algorithm is proposed to automatically detect steady state from time series of pedestrian experiments. Major modifications on the statistics include introducing a step function to enhance the sensitivity, adding a boundary to limit the increase, and simplifying the calculation to improve the computational efficiency. Furthermore, the threshold of the detection parameter is calibrated using an autoregressive process. By testing the robustness, the modified CUSUM algorithm is able to reproduce identical steady state with different references. Its application well contributes to accurate analysis and reliable comparison of experimental results.

Keywords: Time Series; Steady State; Control Chart; Transient State; Kernel Estimation (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-33482-0_10

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DOI: 10.1007/978-3-319-33482-0_10

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