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

Area of Science:

• Urban planning and architectural design
• Human-computer interaction
• Computational social science

Background:

• Wayfinding challenges in complex environments lead to user disorientation.
• Architectural design can improve navigation, but lacks specific optimization strategies.
• Effective wayfinding is crucial for user experience and efficiency.

Purpose of the Study:

• To propose a novel methodology for analyzing and optimizing wayfinding in complex environments.
• To examine the impact of spatial configurations on navigational performance.
• To develop an optimized layout that enhances user wayfinding.

Main Methods:

• Utilized an agent-based model to simulate wayfinding in a multistory hospital.
• Optimized spatial layouts based on simulation results.
• Collected data on user types, workflows, population distribution, and speed.

Main Results:

• Optimized layouts reduced total distance and time for all user types compared to the original.
• Agent-based simulations demonstrated significant improvements in wayfinding performance.
• The approach integrates user workflow and spatial adjacency requirements.

Conclusions:

• The proposed methodology effectively enhances wayfinding in complex environments.
• Optimized layouts offer substantial benefits for user navigation and efficiency.
• This approach is ideal for preliminary design stages of complex buildings.