Tag
A city-building simulator called Discretionary Review puts players in the role of navigating San Francisco's housing approval process, where the city would prefer you didn't build anything.
Anthroposcaper turns tagged 2D plans into textured 3D urban environments, rebuilding scenes automatically from drawing changes and supporting MCP-connected AI agents for template and material setup. Available on Product Hunt for browser-based drafting or DXF import with GLB export to editors and game engines.
This article investigates the optimal shape of cities by modeling the effects of urban form on distances, likely employing computational methods to analyze urban design.
Praxis has begun construction on a new city in Uruguay, with residents expected to move in by 2027, as announced in a tweet linking to a New York Times article.
Garry Tan comments on a strategy where developers propose large data centers to gauge public opposition, then pivot to housing projects to gain approval, suggesting it was the original plan.
CityPlanner introduces a unified sandbox environment and atomic-task reinforcement learning for executable urban planning, outperforming heuristic, task-specific RL, and general LLM-agent baselines on a real-world benchmark.
A visualization project displays every existing building in Los Angeles, showing when each was built from 1880 to 2026 to illustrate urban development.
This paper introduces PermitGPT, a unified generative AI framework that converts construction permit descriptions into structured outputs for safety hazard identification, permit requirements, and community impact assessment using fine-tuned language models.
This study proposes a ring-based Spatial Transformer to model non-linear spatial interactions between building distribution and pedestrian flow around railway stations in Tokyo, outperforming Geographically Weighted Regression and challenging compact city assumptions in urban planning.
This paper measures the implicit assumptions language models make about 'a city' by scoring anonymized urban profiles across 40 indicators, finding a shared preference for larger, faster-growing, and more infrastructure-rich cities. It uses open-weight checkpoints and replication data to make the default portrait of cities in LLMs empirically traceable.
Queensland will trial Australia's first AI-powered traffic lights, raising questions about fairness and who gets priority on public roads, with potential broader implications for urban design.
The article explores the 3-30-300 rule for urban tree coverage—three trees in view, 30% canopy coverage, and within 300m of a park—and discusses its adoption and impact on mental and physical health.
This paper introduces two inverse optimal transport estimators to recover latent choice costs from observed origin-destination flows, applied to Philippine school choice data to quantify how much perceived travel cost an education subsidy offsets.
This paper introduces UPBench, a benchmark to evaluate large language models on urban planning knowledge across four knowledge pillars and five cognitive levels, finding that models perform better on higher-order analysis than factual recall, and identifying epistemic limitations such as regulatory hallucination and phronetic deficit.
A new study in PNAS introduces the concept of an 'urban pulse' measured via remote sensing data, revealing three key vital signs of urbanization that could inform urban planning policy.
This paper introduces PlanBench-V, the first comprehensive benchmark for evaluating Vision-Language Models on spatial planning map interpretation, including an expert-annotated dataset and a four-dimension evaluation framework. Experiments show significant progress but highlight persistent challenges in implementation-oriented tasks.
This research introduces the Housing Potential Common Data Model (HPCDM) to integrate diverse datasets for housing analysis and demonstrates its application through a City Digital Twin pilot.
This academic paper introduces an AI-enabled analytics framework using existing CCTV infrastructure to evaluate the impact of soft traffic interventions on vehicle speed and safety at urban intersections.