Utilizing Agent-Based Modeling for Optimization of Wayfinding in Hospital: A Case Study.

Objectives: This research aims to propose a novel methodology for analyzing and optimizing wayfinding in complex environments by examining their spatial configurations.

Background: Wayfinding difficulties often lead to disorientation and hinder users' ability to locate destinations. Although architectural design can aid in simplifying user access, existing approaches lack a specific focus on wayfinding optimization despite its significant impact on users' navigational abilities.

Methods: In this study, an agent-based model was employed to assess the efficacy of wayfinding in a multistory hospital. Subsequently, the layouts were optimized, leading to the creation of a new space distribution diagram. The simulation was then repeated to examine the potential improvement in wayfinding. Data collection encompassed user types, workflow scenarios, population distribution, and user speed.

Results: Comparative analysis of the agent-based simulation findings before and after layout optimization revealed a decrease in total distance and time spent on the modified floor plans for all users when compared to the existing layout. This suggests that the optimized layout holds significant potential for enhancing wayfinding performance. Given the positive outcomes observed for users, this approach is particularly well suited for preliminary design stages of complex environments, where designations among user groups are less crucial or flexibility is desired. Additional advantages include the ability to generate a comprehensive simulation of users' daily workflow, which is integrated into the optimization process and considers specific requirements regarding spatial adjacency.