Project Summary
As California prepares to transition from fuel taxes to a mileage-based Road Usage Charge (RUC), a central challenge lies in designing pricing systems that are fiscally sustainable, equitable, and publicly acceptable. This project develops a modeling and computation framework to support the design of RUC systems that explicitly account for traveler heterogeneity in income, travel necessity, and privacy concerns.
The researchers first design a mileage-based pricing mechanism that incorporates differentiated per-mile charges and lump-sum mileage credits, tailored to household characteristics such as income and baseline travel needs. This mechanism is intended to ensure equity and revenue sufficiency without requiring detailed location data. This baseline design is compared with an extension that includes time- and location-based pricing enabled by GPS, which supports congestion-responsive pricing but raises privacy concerns. By computing outcomes under each mechanism, the team evaluates how much additional benefit GPS-based pricing provides—and at what privacy cost.
Using California-specific data from Replica, the American Community Survey, and Caltrans PeMS traffic sensors, this work calibrates and computes five RUC policy scenarios. The project’s outputs—including a policy brief, computation results, and an interactive dashboard—can inform Caltrans and California Transportation Commission as they develop equitable and effective RUC strategies.
