Waiting in crowded places: influence of number of pedestrians, waiting time and obstacles

Abstract

At crowded places, like railway platforms at rush hour, the spatial distribution of waiting pedestrians has a significant influence on performance and level of comfort. However, the choice of waiting places and the resulting spatial distribution of the crowd have rarely been studied. This study investigates the effects of obstacles, number of passengers and waiting time on the distribution of waiting passengers. Laboratory experiments were performed using a mock-up platform with three set-ups: without obstacles, with a narrow and a wide obstacle. Density profiles determine preferred waiting places. While the space usage by waiting passengers is inhomogeneous, the distances between the individuals show surprisingly small variations, regardless of obstacles and number of passengers. This suggests a robust collective optimization of the crowd when searching for waiting positions. In doing so, and without necessity, the participants chose distances to each other extending into the personal zone specified in classical personal-space-concepts. These results indicate necessary refinements of the concept by considering context and collective behaviour. The findings are transformed into floor-fields modelling the space usage by a superposition of attractive or repulsive areas which consider optimization of distances and comfort. This model does not only reproduce the waiting places at platforms but can be adapted for other use cases.

Behavioral repertoires in moving crowds: An observational approach

“…Speed ranges from 0-2 m/s, density ranges from 0-2 persons/m2. The heatmaps were created by following the procedures described in Küpper and Seyfried (2023) using the Python library PedPy (Schrödter & Team, 2022). The analysis focuses on the time before the entry gate was opened (approximately 1 min), divided into intervals of 15 sec.…”