New Definition and Analysis of Spatial-Headway in Two-Dimensional Pedestrian Flow

Xu Mai (), Weiguo Song () and Jian Ma ()
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Xu Mai: University of Science and Technology of China, State Key Laboratory of Fire Science
Weiguo Song: University of Science and Technology of China, State Key Laboratory of Fire Science
Jian Ma: School of Transportation and Logistics, Southwest Jioatong University, National United Engineering Laboratory of Integrated and Intelligent Transportation

A chapter in Traffic and Granular Flow '13, 2015, pp 111-119 from Springer

Abstract: Abstract In recent years researchers have paid attention to the dependency between required length and velocity, which is rather important for modeling pedestrian movement. Some researchers have observed that the velocity of individuals is related to the spatial headway by a linear relation. The other people have found in experiment that there is phase transitions in the following behavior through a larger range of velocities. However, most relations are derived from one-dimensional experiments such as single-file movement, while the study of spatial-headway in two-dimensional pedestrian flow is relatively rare. Here we conducted an experiment suitable for a new insight into the two-dimensional headway.In this study, two-dimensional experiments are carried out to study pedestrian movement behaviors in a circular passageway. The full pedestrians’ trajectories are extracted through an automatic image processing method of high accuracy based on mean-shift algorithm. Here we redefine the spatial-headway in two-dimensional following behavior, which is elaborated in detail later. The results show that the two-dimensional spatial-headway is distinctively different from that obtained in single-file movement. The velocity in every ligature is also extracted to get the relationship between velocity component and distance in different angles. Results of the more crowded situation show that the pedestrians turn into three steady lanes and the spatial-headway also keeps in a stable state. The findings may be useful for model calibration.

Keywords: Spatial Clearance; Single-file Movement; Automated Image Processing Method; Pedestrian Trajectories; Local Density Values (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-3-319-10629-8_13

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