Abstract
This paper investigates a new method to simulate pedestrian crowd movement in a large and complex virtual environment, representing a public place such as a shopping mall. To demonstrate pedestrian dynamics, we consider different group sizes with various categories of pedestrian sharing a crowded environment. Each category has its own characteristics, such as gender, age, position, velocity, and energy. The proposed method uses the multi-group microscopic model to generate real-time trajectories for all people moving in the defined virtual environment. Additionally, an agent-based model is introduced for modelling group behaviour. Based on the proposed method, every pedestrian in each group can continuously adjust their attributes and optimize their path towards the desired visiting points, while avoiding obstacles and other pedestrians. The simulation results show that the proposed method can describe a realistic simulation of dynamic behaviour in a given virtual environment.