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@ARTICLE{Bode:858465,
author = {Bode, Nikolai W. F. and Chraibi, Mohcine and Holl, Stefan},
title = {{T}he emergence of macroscopic interactions between
intersecting pedestrian streams},
journal = {Transportation research / B Methodological Part B},
volume = {119},
issn = {0191-2615},
address = {Amsterdam [u.a.]},
publisher = {Elsevier},
reportid = {FZJ-2018-07337},
pages = {197 - 210},
year = {2019},
abstract = {The interactions between individual pedestrians can lead to
emergent effects, such as the formation of lanes in
bidirectional flows. Here, we expose properties of an
emergent effect at a macroscopic level, namely interactions
between pedestrian streams that arise when pedestrians walk
into and through four-way intersections from different
directions. We propose non-spatial models for the number of
pedestrians from different streams inside an intersection.
Each model encodes a different hypothesis for how streams
interact and can produce dynamics fundamentally distinct
from the other models. By fitting our models to large
experimental data sets and determining which model explains
the data best, we determine when and how entire streams of
pedestrians start to interact. We find that as arrival rates
increase, streams start to interact and compete for space.
Our results suggest that these interactions result in an
even balance of pedestrian numbers across two orthogonally
intersecting streams. Neither of the streams can dominate.
In contrast, for four intersecting streams, our findings
suggest that jams in some streams can coincide with higher
flow rates in other streams and that the relative dominance
of streams can switch stochastically. By adapting existing
methodology, we thus present a coherent conceptual approach
for investigating emergent effects in temporal dynamics at
aggregated levels in pedestrian flows that could be applied
to other scenarios. Our approach is flexible and uses easily
measured quantities, making it highly suitable for
observational data in different scenarios or deployment in
applications.},
cin = {IAS-7},
ddc = {380},
cid = {I:(DE-Juel1)IAS-7-20180321},
pnm = {511 - Computational Science and Mathematical Methods
(POF3-511)},
pid = {G:(DE-HGF)POF3-511},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000456900900011},
doi = {10.1016/j.trb.2018.12.002},
url = {https://juser.fz-juelich.de/record/858465},
}