自动化校准技术提升交通需求建模效率

[来源: CP] [分类提示: NEWS] 标题: Automated Calibration Streamlines Travel Demand Modeling Automated calibration is helping transportation planners make travel demand modeling faster, more efficient and responsive to changing travel patterns. Traditionally, calibrating travel demand models required months of manual adjustments to ensure model results matched real-world data such as traffic counts, transit ridership and household travel surveys. Automated calibration simplifies the process by using optimization algorithms to adjust multiple model parameters at once. Transportation professionals from WSP, Jacobs, and the City of Edmonton have used automated calibration through Bentley OpenPaths for a variety of travel demand models. WSP found that the technology helps identify errors more quickly and allows models to be validated across more data sources and travel segments. Jacobs reported that calibration runs could be completed in just five to 10 iterations, reducing reliance on spreadsheets and manual adjustments. In Edmonton, automated calibration helped update a model originally based on 2015 travel data to reflect post-COVID changes, including increased remote work and reduced transit use. The city also found it easier to incorporate updated population, employment and traffic data. The modelers said the technology not only saves time but also acts as a diagnostic tool, making the calibration process more transparent and allowing models to be updated more frequently. As travel behavior continues