This study analysed evacuees' movements in three sequentially announced evacuation drills in a theatre to clarify evacuees' route choice mechanism in an auditorium and to obtain a data-set for the validation of evacuation simulations and egress time calculations. The drills were conducted in a multipurpose theatre in Japan over consecutive years, involving approximately 400-540 occupants aged 6-90. The coordinates of every occupant in the auditorium during the drills were accurately obtained every 0.5 s using the authors' original software programmes, so that evacuees' trajectories and walking speeds at each point could be obtained. Thereby, we obtained more than 100,000 data points in total to analyse. The drills were also compared from the point of view of the flow control of the facility's staff during the evacuation. The results revealed that, while the evacuees in the centre blocks chose the closest aisle from their seats, most of the evacuees in the side blocks chose the wall side aisles. The occupants did not create queues in aisles between seat blocks. They tended to walk along seatways, the narrow spaces between seat rows to get closer to their target exit, rather than stacking in the aisles. In addition, the specific flow at exit doors from the auditorium in a congested situation was ca. 0.96 pers./m/s.
This paper proposes a novel image processing method to extract pedestrian movements in a crowd from video images of the crowd seen from above. A large scale crowd evacuation experiment with 96 pedestrians was analyzed with this method. This method detects color markers on a cap of each pedestrian and makes trajectories of pedestrians by clustering neighboring markers and tracking them during the sequential video frames. The color combination of clustered markers indicates the body height of each pedestrian to result in a more accurate coordinate transform. This method successfully tracked the pedestrians to make their trajectories with the positioning error under 40 mm. Over 99 percent of pedestrian's position data were automatically calculated without manual operation thanks to the redundancy of multiple markers and the marker clustering. In the merging experiment, the flow rate through an opening decreased due to turning off after the opening and merging with pedestrians in the path. Detailed pedestrian behavior revealed that walking direction and walking speed were strongly linked to the interaction between neighboring pedestrians such as the distance and the relative velocity between them.
In this study, pedestrian crowd dynamics at corner turns were investigated by analyzing pedestrian trajectories in a subject experiment for building more reliable, general-purpose, pedestrian simulation models. An experiment under laboratory conditions was conducted wherein a pedestrian crowd walked straight for a short distance before turning into a right-angled corner built with partition walls; the opposite sides were unwalled. Trials were performed with different widths and densities of initial participant positions. Finally, the trajectories of the pedestrians were extracted from a video through computer image analysis. The results demonstrated that pedestrian behavior at corner turns depends on lane position, lane distance (from the wall), and crowd density.
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