Abstract Manager

Digital twins are increasingly viewed as foundational tools for modern transportation asset management, yet many implementations struggle to move beyond static representations or short-lived pilot programs. Nowhere is this challenge more evident than in the curbside and public right of way: highly dynamic environments shaped by regulations, time-of-day rules, construction activity, and competing user needs. This presentation explores how practical automation and AI can be used to generate, operate, and maintain digital twins for these complex transportation assets at scale.

Drawing on CurbIQ’s experience working with cities across Canada and the United States, including projects in Edmonton, Toronto, Seattle, and Philadelphia, this talk examines how different jurisdictions require distinct approaches to digital twin development based on governance models, data maturity, and operational goals. The presentation will highlight key challenges agencies face, including fragmented data sources, rapidly changing curb regulations, and the high cost of manual data collection and upkeep.

The core objective of this session is to demonstrate how automation and AI can bridge the gap between real-world conditions and usable digital twins. Methodologies discussed will include automated data ingestion from regulations and field sources, AI-assisted interpretation of curb rules and signage, and workflow automation that enables continuous updates as conditions change. Real-world applications will be showcased, including planning and policy analysis, operational decision-making, enforcement support, and performance measurement.

A central theme of the presentation is that digital twins are only valuable if they are actively maintained. The session will emphasize why maintenance, not initial creation, is the true barrier to success, and how automation is essential to keeping digital twins accurate, trusted, and operational over time.

The presentation concludes with practical lessons learned, key success factors, and recommendations for agencies seeking to move from static inventories to living, operational digital twins that deliver long-term value for transportation systems.