Estimating Pedestrian Flows Using Route Distributions and Sparse Counting Data

Christina Maria Mayr; Gerta Köster

doi:10.17815/CD.2024.149

Authors

Christina Maria Mayr University of Applied Sciences and Technical University Munich, München, Germany https://orcid.org/0000-0003-1686-3460
Gerta Köster Hochschule München, University of Applied Sciences, München, Germany https://orcid.org/0000-0002-3369-6206

DOI:

https://doi.org/10.17815/CD.2024.149

Keywords:

Crowd management, Count study, Online Survey, Pedestrians, Traffic

Abstract

At metro station Münchner Freiheit in Munich soccer fans cause congestion before and after soccer matches on the shortest route to get from a bus station to the metro. Yet, an online survey suggests that, given the right information and incentive through a mobile app, fans are willing to take a detour. In this study we combine the survey results with passenger counts collected in a field study to quantitatively estimate the number of rerouted pedestrians in dependency of influx from a side entrance for which there is no data. We find a realistic range for the change in flow, despite incomplete measurement data, that we use as input for predictive simulations. The quantitative results are also helpful for traffic management.

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