An intelligent floor field cellular automata model for pedestrian dynamics

TL;DR

This paper introduces an advanced cellular automata model for pedestrian movement that incorporates environment analysis, patience, and realistic route choices, improving simulation accuracy for regular pedestrian behaviors.

Contribution

It presents a novel CA model combining floor fields and environment analysis with patience factors, enhancing realism in pedestrian dynamics simulation.

Findings

Model effectively simulates regular pedestrian movement.

Comparison shows improved realism over basic floor field models.

Simulation results validate the model's applicability.

Abstract

A stochastic cellular automata (CA) model for pedestrian dynamics is presented. Our goal is to simulate different types of pedestrian movement, from regular to panic. But here we emphasize regular situations which imply that pedestrians analyze environment and choose their route more carefully. And transition probabilities have to depict such effect. The potentials of floor fields and environment analysis are combined in the model obtained. People patience is included in the model. This makes simulation of pedestrians movement more realistic. Some simulation results are presented and comparison with basic FF-model is made.