# Pedestrian Flow Model Based on Cellular Automata Under Visual Trajectory and Multi-Scenario Evacuation Simulation Research

## TL;DR

This paper introduces a new pedestrian flow model using computer vision and cellular automata to simulate evacuation scenarios and improve safety design.

## Contribution

The study introduces data-driven transition probabilities from real pedestrian trajectories into a cellular automata model for evacuation simulation.

## Key findings

- Moderate panic can shorten evacuation time, but excessive panic leads to behavioral disorders.
- Group movement is limited by the slowest individual in the group.
- Increased hazard source speed reduces the proportion of safe pedestrians.

## Abstract

Precise modeling and simulation of pedestrian flow are crucial for public space safety design and emergency management. This study proposes an interdisciplinary method integrating computer vision and cellular automata (CA). First, unidirectional pedestrian flow video data with different densities were collected from an overpass scene via controlled experiments. High-precision pedestrian trajectory extraction and tracking were achieved using the YOLO 11 model and DeepSORT algorithm, with image distortion corrected by perspective transformation. For the first time, the probability distribution of pedestrian turning angles derived from trajectory analysis was converted into data-driven transition probabilities for the Moore neighborhood in the CA model. An improved evacuation model was then constructed, comprehensively considering real-data-based transition probabilities, speed–density distribution, panic coefficient, individual life value, and hazard source dynamics. Multi-scenario simulations show that moderate panic may shorten evacuation time, while excessive panic causes behavioral disorders; group movement is constrained by the slowest individual, and increased hazard source speed reduces the proportion of safe pedestrians. This study provides new insights and methodological support for refined pedestrian evacuation simulation and safety management.