Optimizing public restroom allocation in commercial districts: a pedestrian behavior-integrated simulation framework for equitable and resilient urban facilities

The equitable and resilient allocation of public service facilities in commercial districts is crucial for urban sustainability. However, conventional planning approaches relying on static indicators fail to account for the spatiotemporal fluctuations in pedestrian flow, leading to supply-demand mismatches. To address this, we introduce a simulation-based optimization framework that integrates spatial analysis, pedestrian behavior modeling, and multi-objective facility allocation from a spatial-behavioral interaction perspective. We develop an agent-based model with multi-attribute decision-making to simulate pedestrian distribution, considering spatial configuration, commercial attractiveness, and individual preferences. A Gaussian influence field algorithm dynamically optimizes facility layout. Applied to public restroom allocation in Xi’an Qujiang Creative Valley, the framework improves the demand satisfaction rate from 53.2% to 89.7%. By operationalizing equity as the spatial disparity in satisfaction rates (measured via Gini coefficient) and resilience as the system’s performance under peak-hour loads and disruption scenarios, this study offers a data-driven, adaptive methodology for human-centric urban facility planning.