How COVID-19 is Affecting Pedestrian Modeling and Simulation: The Case of Venice

Abstract

The use of computer-based pedestrian crowd simulations has become crucial in transport planning considering the unprecedented effects of the COVID-19 pandemic on urban mobility. However, there is still a lack of knowledge in relation to the impact of social distancing on crowding, queuing, route choice, and other pedestrian crowd phenomena. In this context, the aim of the current study was to apply the Social Force Model of the pedestrian simulation platform PTV Viswalk to investigate the effects of disruption of social distancing on pedestrian dynamics. First, a descriptive set of metrics and parameters was applied for calibrating the dynamic regulation of interpersonal distances among pedestrians. The plausibility of the proposed social distancing model was then evaluated against the so-called fundamental diagram to calibrate pedestrian volume-delay functions. Finally, the proposed model was integrated into the PTV Visum simulation platform to evaluate the effects of social distancing on large-scale pedestrian route choice. To do so, a macroscopic static model of the city of Venice was developed to test the effectiveness of alternative crowd management strategies related to pedestrian dynamics in a predictive scheme.

Agent-Based Simulation for Infectious Disease Modelling over a Period of Multiple Days, with Application to an Airport Scenario

“…Islam et al analysed indoor spaces in general [38]. Espitia et al [39] propose a "social distancing model", comparing the social force model to their own social distancing model. Their simulation considers the city of Venice.…”

Enhancing Sustainable Mobility: Evaluating New Bicycle and Pedestrian Links to Car-Oriented Industrial Parks with ARAS-G MCDM Approach

“…This situation can be attributed to traditional transport planning methods that calculate traffic flows between transportation districts without considering local street segment-level changes, but traditional methods are not sensible to micro-level or pathway segment-level changes. The present generation of traffic planners often relies on macro-level data, despite advancements in processing speed and data capacity [19][20][21][22]. Micro-simulation, typically performed with software such as PTV VISIM, analyses changes in existing traffic flows, link delays, volumes, and traffic light phases [23,24], but often fails to provide detailed predictions at the neighborhood level.…”