Abstract
Urban open places with a public service function (e.g., urban parks) are likely to be populated in peak hours and during public events. To mitigate the risk of overcrowding and even events of stampedes, it is of considerable significance to realize a real-time full coverage estimate of the population density. The main challenge has been the limited deployment of crowd surveillance detectors in open public spaces, leading to incomplete data coverage and thus impacting the quality and reliability of the density estimation. To remedy this issue, this paper proposes a modified inverse distance weighting (IDW) method, named the inverse distance weighting based on path selection behavior (IDWPSB) method. The proposed IDWPSB method adjusts the distance decay effect according to visitors’ path selection behavior, which better characterizes the human dynamics in open spaces. By implementing the model in a real-world road network in the Shichahai scenic area in Beijing, China, the study shows a decrease in the absolute deviation by 17.62% comparing the results between the new method and the traditional IDW method, justifying the effectiveness of the new method for spatial interpolation in open public places. By considering the behavioral factor, the proposed IDWPSB method can provide insights into public safety management with the increasing availability of data derived from location-based services.
Highlights
In Chinese cities, open places serving a public service function are likely to be populated in peak hours and during public events
To estimate the spatial distribution of the crowd population in open public places, we have proposed a new interpolation method called the inverse distance weighting method based on path selection behavior (IDWPSB)
In terms of computational efficiency, the interpolation process took 52.4 seconds using the IDW method and 74.3 seconds using the IDWPSB method under the same computing environment. These various aspects of comparison suggest that including the path selection behavior in the IDWPSB method can improve the interpolation accuracy without significantly increasing the computational demand
Summary
In Chinese cities, open places serving a public service function (e.g., urban parks) are likely to be populated in peak hours and during public events. The inherent difficulties of surveillance and crowd control in these open spaces highlight the numerous evacuation problems that could arise in an emergency, including the occurrence of stampedes. This is precisely what occurred on February 5, 2004, at the Lantern Festival in Beijing’s Miyun Park. In this instance, the primary viewing space was trampled and caused 37 fatalities even though the total number of visitors was far below the park’s maximum capacity. Controlling the total number of visitors is insufficient for comprehensive safety management in open public places. It is paramount to realize a real-time and full coverage population density estimate to prevent local overcrowding
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