Auditable Closed-Loop AI Agents for Urban Bridge Digital Twins

Synthetic Validation Followed by a Municipal-Scale Utsunomiya Implementation

Authors

  • Takayuki Shinohara AIST

DOI:

https://doi.org/10.62161/sauc.v12.6387

Keywords:

Urban resilience, Multi-objective optimization, Infrastructure asset management, Smart cities, Urban digital twins, Agentic AI

Abstract

Urban bridge maintenance is a smart-city governance problem involving uncertain evidence, constrained budgets, and safety-critical actions. We present an auditable closed-loop artificial intelligence architecture separating observations, inferred states, alternatives, decisions, and interventions. Mechanisms are validated in SynthTown, a ground-truth municipality with 50 bridges and 842 components, using hidden-state prediction, multiobjective planning, stakeholder screening, feedback recalibration, and verifier-repair safeguards. A public-data implementation covers 1,733 Utsunomiya bridges and integrates 1,592 persistent scatterer interferometric synthetic aperture radar points, inspection records, three-dimensional maintenance models, and capacity-aware plans. Verification eliminated unsafe outputs in the synthetic benchmark.

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Published

2026-09-03

How to Cite

Shinohara, T. (2026). Auditable Closed-Loop AI Agents for Urban Bridge Digital Twins: Synthetic Validation Followed by a Municipal-Scale Utsunomiya Implementation. Street Art & Urban Creativity, 12(5), 345–369. https://doi.org/10.62161/sauc.v12.6387

Issue

Vol. 12 No. 5 (2026)

Section

Research articles

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