Adaptive Urban Planning: A Hybrid Framework for Balanced City Development

TL;DR

The paper presents a hybrid urban planning framework that blends a deterministic solver with region-specific planning agents to balance city-wide infrastructure with local demographic needs. A genetic-algorithm-based solver optimizes fundamental accessibility and ecological metrics, while four regional planners propose sub-regional adjustments coordinated by a master planner under a minimal-change policy. Validated on AMRUT/Bhuvan-derived maps from Kanpur, Lucknow, and Raipur, the approach shows progressive gains in service accessibility, ecological coverage, and resident satisfaction across planning stages, demonstrating robustness and generalizability. The work advances scalable, inclusive urban planning for rapidly urbanizing regions by integrating systematic optimization with demographic-driven customization, aligned with the 15-minute city concept.

Abstract

Urban planning faces a critical challenge in balancing city-wide infrastructure needs with localized demographic preferences, particularly in rapidly developing regions. Although existing approaches typically focus on top-down optimization or bottom-up community planning, only some frameworks successfully integrate both perspectives. Our methodology employs a two-tier approach: First, a deterministic solver optimizes basic infrastructure requirements in the city region. Second, four specialized planning agents, each representing distinct sub-regions, propose demographic-specific modifications to a master planner. The master planner then evaluates and integrates these suggestions to ensure cohesive urban development. We validate our framework using a newly created dataset comprising detailed region and sub-region maps from three developing cities in India, focusing on areas undergoing rapid urbanization. The results demonstrate that this hybrid approach enables more nuanced urban development while maintaining overall city functionality.

Figures (3)

• Figure 1: Workflow of the proposed urban planning framework. Integrating Deterministic Optimization, Regional Planner inputs, and Master Planner Coordination to achieve balanced and Area-Specific city layouts
• Figure 2: Conversion of the original map image into the annotated map image showcasing land-use categorization through color-based segmentation
• Figure 3: Utilization of mask images to validate centroids of land-use regions, showing the original map and corresponding masks defining valid sub-regions