- By:
- Luo, Xiangyong ; Zhang, Yiran; Xu, Guanhao ; Li, Wan ; Wang, Chieh ; Zhou, Xuesong
- Page Number:
- 2320-2331
- Book Title:
- Proceedings of the 2025 Winter Simulation Conference
- Publication Date:
- March 12, 2026
- Publisher Location:
- IEEE, New Jersey, United States of America
- Conference Name:
- 2025 Winter Simulation Conference (WSC)
- Conference Location:
- Seattle, Washington, United States of America
- Conference Sponsor:
- ACM/SIGSIM, ASA (Technical Co-Sponsor), ASIM (Technical Co-Sponsor), IEEE/SMC (Technical Co-Sponsor), IISE, INFORMS-SIM, NIST (Technical Co-Sponsor), SCS, and ORS (Technical Sponsor)
- View DOI Listing:
- https://doi.org/10.1109/WSC68292.2025.11338949
Abstract
Modern transportation research relies on seamlessly integrating traffic signal data with robust network representation and simulation tools. This study presents utdf2gmns, an open-source Python tool that automates conversion of the Universal Traffic Data Format, including network representation, signalized intersections, and turning volumes into the General Modeling Network Specification (GMNS) Standard. The resulting GMNS-compliant network can be converted for microsimulation in SUMO. By automatically extracting intersection control parameters and aligning them with GMNS conventions, utdf2gmns minimizes manual preprocessing and data loss. utdf2gmns also integrates with the Sigma-X engine to extract and visualize key traffic control metrics, such as phasing diagrams, turning volumes, volume-tocapacity ratios, and control delays. This streamlined workflow enables efficient scenario testing, accurate model building, and consistent data management. Validated through case studies, utdf2gmns reliably models complex urban corridors, promoting reproducibility and standardization. Documentation is available on GitHub and PyPI, supporting easy integration and community engagement.
