Many of the predictive models used by California’s transportation agency fail to account for post-pandemic travel patterns and induced demand.
A review commissioned by Caltrans reveals that the California transportation agency’s travel demand models are often “outdated, poorly documented, and ill-suited to the purposes agencies sometimes use them for.”
As Leslie Vasquez-Guzman explains in an article for the State Smart Transportation Initiative, “Transportation agencies rely on models to forecast traffic and guide billions of dollars in infrastructure investment. Without updates, these tools risk locking in old assumptions about growth and travel behavior rather than helping agencies plan for a more sustainable and efficient future.”
The Caltrans analysis found that regional travel demand models had base years at least five years old that failed to reflect post-pandemic travel patterns. “Many were not able to account for key effects such as long-term induced travel—new driving that results from expanding road capacity.”
The report highlights the potential difference in outcomes between a forecast and real-world results once a project is built or not built. “To address these issues, Caltrans recommends several actions that could help guide modeling in other states. These include updating models with recent data, improving documentation and guidance for agencies, and testing for induced travel and land use changes. The report also calls for a model suitability checklist, better coordination among agencies, and updated standards for project-level modeling to improve consistency and transparency.”
FULL STORY: Caltrans review finds outdated and misunderstood models hinder project analysis
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