Researchers at the Indian Institutes of Technology (IIT), Madras, have developed fluid dynamic models to study crowd behaviour. These models can enhance safety measures and provide insights into how people navigate obstacles. They are also valuable for analysing disease transmission within crowds, as observed during the Covid-19 pandemic.
They have created a microscopic pedestrian model that takes into account social and behavioural factors, from which a hydrodynamic model was mathematically derived. Equations governing how obstacles interact with pedestrians were formulated. Furthermore, the researchers investigated crowd behaviour when encountering obstacles while aiming for an exit or target.
This information is instrumental in establishing safety regulations. Additionally, these models are applicable to studying interactions among people, vehicles, and robots in various scenarios. The researchers suggest potential applications in autonomous vehicles and robot navigation, according to the university's statement.
The study's modelling has showcased adaptability across a wide range of real-world situations. It has been applied to analyse vehicular traffic and disease contagion, with potential future applications in driverless cars and robot navigation.
Professor Dr Thomas Goetz from the University of Koblenz in Germany emphasized the importance of understanding human behaviour in large crowds to prevent accidents.
He said, "Understanding the dynamics of human crowds in mass events like rock concerts, sports, or religious events is a major key to preventing crowd disasters, such as the Love Parade 2010 in Germany or the Hajj 2015 in Mecca, Saudi Arabia. Modelling and simulating the behaviour of human crowds have been hot topics in research over the past decades."