PASSENGER MOVEMENT SIMULATION IN A VEHICLE BASED ON CELLULAR AUTOMATA

Abstract

This paper discusses a multi-agent crowd movement simulation model based on cellular automata on a rectangular lattice. The study focuses on two main aspects of stress: interpersonal stress, which arises from agents' efforts to avoid overcrowding and contact with other agents, and positional stress, which arises from agents' efforts to reach a specific goal. The combined stress model integrates these two factors, allowing agents to make decisions that consider both the necessity to avoid overcrowding and the need to move towards a goal. Interpersonal stress is calculated as the sum of agents in neighboring cells, and agents try to move to the cell with the fewest neighbors. This approach helps minimize conflicts and overcrowding. Positional stress considers the distance to the specified goal, allowing agents to move in the direction of the goal. The wave algorithm is used to calculate the agents' movement trajectories, which helps avoid collisions and find optimal paths to the goal.

Modeling and visualization of the results showed that the proposed model effectively reproduces the movement of passengers in a transport vehicle, demonstrating the adequacy and accuracy of the proposed approach.