TY  - CONF
AU  - Liao, Weichen
AU  - Tordeux, Antoine
AU  - Seyfried, Armin
AU  - Chraibi, Mohcine
AU  - Zheng, Xiaoping
AU  - Zhao, Ying
TI  - Detection of Steady State in Pedestrian Experiments
CY  - Cham
PB  - Springer International Publishing
M1  - FZJ-2016-07407
SP  - 73 - 79
PY  - 2016
AB  - Initial conditions could have strong influences on the dynamics of pedestrian experiments. Thus, a careful differentiation between transient state and steady state is important and necessary for a thorough 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.
T2  - Traffic and Granular Flow
CY  - 28 Oct 2015 - 30 Oct 2015, Delft (Neederlands)
Y2  - 28 Oct 2015 - 30 Oct 2015
M2  - Delft, Neederlands
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
DO  - DOI:10.1007/978-3-319-33482-0_10
UR  - https://juser.fz-juelich.de/record/824905
ER  -