An Improved Simulation Model for Pedestrian Crowd Evacuation

TL;DR

This paper enhances a pedestrian crowd evacuation simulation model by introducing a new method that optimizes exit door placement based on evacuation times, improving safety and evacuation efficiency.

Contribution

It proposes an innovative method integrated into an existing AI-based evacuation model to determine optimal exit locations based on evacuation time analysis.

Findings

The new method accurately predicts the best exit door location.

The integrated model improves evacuation safety and efficiency.

Validation with various scenarios confirms the method's effectiveness.

Abstract

This paper works on one of the most recent pedestrian crowd evacuation models, i.e., "a simulation model for pedestrian crowd evacuation based on various AI techniques", developed in late 2019. This study adds a new feature to the developed model by proposing a new method and integrating it with the model. This method enables the developed model to find a more appropriate evacuation area design, among others regarding safety due to selecting the best exit door location among many suggested locations. This method is completely dependent on the selected model's output, i.e., the evacuation time for each individual within the evacuation process. The new method finds an average of the evacuees' evacuation times of each exit door location; then, based on the average evacuation time, it decides which exit door location would be the best exit door to be used for evacuation by the evacuees. To validate the method, various designs for the evacuation area with various written scenarios were used. The results showed that the model with this new method could predict a proper exit door location among many suggested locations. Lastly, from the results of this research using the integration of this newly proposed method, a new capability for the selected model in terms of safety allowed the right decision in selecting the finest design for the evacuation area among other designs.