A motion planning method for simulating a virtual crowd

Abstract

A model of motion planning for agent-based crowd simulation is one of the key techniques for simulating how an agent selects its velocity to move towards a given goal in each simulation time step. If there is no on-coming collision with other agents or obstacles around, the agent moves towards the designated goal directly with the desired speed and direction. However, the desired velocity may lead the agent to collide with other agents or obstacles, especially in a crowded scenario. In this case, the agent needs to adjust its velocity to avoid potential collisions, which is the main issue that a motion planning model needs to consider. This paper proposes a method for modelling how an agent conducts motion planning to generate velocity for agent-based crowd simulation, including collision detection, valid velocity set determination, velocity sampling, and velocity evaluation. In addition, the proposed method allows the agent to really collide with other agents. Hence, a rule-based model is applied to simulate how the agent makes a response and recovers from the collision. Simulation results from the case study indicate that the proposed motion planning method can be adapted to different what-if simulation scenarios and to different types of pedestrians. The performance of the model has been proven to be efficient.