/social_distancing_sfm

Analyzing Pedestrian Social Distancing

Primary LanguagePython

Analysing Social Distancing using Social Force Models

We propose to model the mobility behavior of pedestrians in public spaces to characterize the exposure and potential spread of COVID-19. Helbing’s social-force model provides a realistic framework of modeling pedestrian dynamics in the vicinity of other pedestrians, obstacles, and area of interests. The social-force model will be used to predict pedestrian mobility in public using PTV VISSIM and Viswalk software. Figure shows preliminary results from a multi-pedestrian simulation of students on the University of Maryland campus entering the Brendan Iribe Center for Computer Science and Engineering, which is a slated to be re-opened for some classes on August 31, 2020. The Iribe Center hosts the UMCP Department of Computer Science, which is the most popular undergraduate major on campus, with nearly 4000 undergraduate students. Figure 8(a) shows a simulated visualization of a steady flow of students enter the lobby of the Iribe Center on the way to class. Figure8(b) shows the corresponding trajectories in space and time. Figure 8(c) shows the impact of increasing therate of students entering the building on two preliminary metrics for exposure and risk: average separation between students and the number of interactions within 2 meters, a commonly used threshold for safe social distancing. Evidently, the average separation between students decreases only slightly when the flow rate increases, whereas the number of close encounters increases exponentially—indicating increased risk. The proposed simulation framework will not only be used to evaluate the exposure/risk as a function of theparameters of the social-force model, but also to determine parameter thresholds and infrastructure changes that promote compliance with safety guidance during re-opening. For example, building/room entry and exit guidelines will be examined and developed to avoid potentially unsafe clustering.