Simulating Crowds in Real-Time with Agent-Based Modelling and a Particle Filter
Kevin Minors, Andrew West and Nicolas Malleson
In this submission, we present an application of a particle filter to a crowd simulation model in order to demonstrate data assimilation on an agent-based model. Generally, agent-based models run independently from reality once initial conditions have been set. This is a major hurdle for smart city models that are constantly receiving new information. Using a particle filter to assimilate the data in real time is one way to overcome this challenge. We demonstrate how this can be done using a particle filter receiving location information from a corridor-like crowd simulation model.