DOI: 10.5061/dryad.c2fqz619v
title: Pedestrian movement trajectories and collision avoidance strategies in interweaving pedestrian flow experiment

description: The mechanisms of Collision Avoidance(CA) behaviors in interweaving
 pedestrian flow movements are important for pedestrian space planning and
 emergency management but not well understood yet. A series of controlled
 interweaving pedestrian flow experiments with different pedestrian flow
 densities are carried out to investigate the CA behaviors, especially CA
 strategy choices. This dataset consists the movement trajectory and the CA
 strategy choices information of the participants in the experiment and was
 provided as a supplementary material of a journal paper submitted to
 “Royal Society Open Science”. All these experiments were conducted in an
 outdoor public square in the campus of Wuhan University of Technology. A
 total of 40 students aged 18-23 years participated these experiments. The
 experiment includes three “groups”, representing low, medium and high
 density levels of interweaving pedestrian flow. Each group of experiment
 was repeated three times to increase the reliability of the observations.
 Therefore, there are totally 9 data files in this dataset, each file
 contains the data of one experiment. After the experiment, the PeTrack
 software was used to extract pedestrians’ trajectories by identifying and
 tracking the coordinates of participants’ heads in the video records. This
 dataset provides the extracted trajectories of all the pedestrians in each
 experiment. Trajectory of each RP is marked as Collision Avoidance Segment
 (CAS) and Normal Walking Segment (NWS). During the CAS, pedestrians have
 shown collision avoidance strategies. Four types of CA strategies,
 including “deceleration”, “acceleration”, “detour”, and “stop” are
 manually identified in these experiments and marked in the dataset. More
 details of the data and the results of the study could be found in the
 associated journal paper. This dataset could be useful for researchers in
 this field.
description: Description of methods used for collection of data:
 This dataset was provided as a supplementary material of a
 journal paper submitted to “Royal Society Open Science”. The citation
 information will be updated in this readme file when it is ready. During
 the pedestrian flow experiment, a high definition video camera was placed
 at a height of 15.7m above the site to record the experiment at 25
 frames/s. The entire experiment site was recorded in an approximate
 top-down manner to ensure that everyone's trajectory can be clearly
 seen and can be extracted by pedestrian trajectory recognition
 algorithms. Methods for processing the data: 
 After the experiment, the PeTrack software was used to extract
 pedestrians’ trajectories by identifying and tracking the coordinates of
 participants’ heads in the video records. The PeTrack software can
 generate pedestrian movement trajectory information including ID of
 pedestrian, time, X coordinate, Y coordinate. The PeTrack software has
 been widely used in pedestrian empirical studies for pedestrian movement
 trajectory data collection and data analyses, and details of the software
 can be found from: Boltes M, Seyfried A. Collecting pedestrian
 trajectories[J]. Neurocomputing,2013, 100(JAN.16):127-133. After the
 trajectory data extraction, the collision avoidance strategies of each
 pedestrian were labeled in the data records based on manually observation
 of the video records.
description: Filename: Experiment group number – repeat time number 
 Column 1 – Unique ID of pedestrians in this experiment
 Column 2 – “RP” or “YP” labels of pedestrians
 Column 3 - time [s:frame] (25 frames per second)
 Column 4 - X coordinate [cm] Column 5 - Y
 coordinate [cm] Column 6 – labels of collision
 avoidance strategies (NWS: Normal Walking Segment ; A:acceleration;
 C:deceleration; T:detour; S:stop)