Simulating Crowd Behavior Using Artificial Potential Fields: An Agent-Based Simulation Approach

This paper presents an associate agent-based model (ABM) of the rebellions where protesters and mobs move in a crowd and try to reach valuable sites while cops settled in front of sites to safeguard them and use obstacles to disperse them. This paper aims to show how people during a protest decide and steer to get their target, such as valuable buildings. To simulate the protest and entities, we employ agent-based modeling, which provides a flexible tool for assessing scenarios. Our paper uses steering behavior techniques to simulate the higher cognitive process of rebellions and police at the microscopic level. It considers the special characteristics of protesters' behavior, like avoiding obstacle collision relating to perceived hardship and grievance. The artificial potential field is used to show the movement of people. The projected model consists of 4 forms of agents; policemen, protesters, mobs, and facilities that give an acceptable framework for future studies.