Document Type

Journal Article

Publication Date


Subject Area

infrastructure - vehicle, infrastructure - bus/tram priority, infrastructure - bus/tram lane, land use - planning, ridership - forecasting, ridership - forecasting, ridership - demand, economics - pricing, mode - rail, mode - tram/light rail, mode - carpool


Value pricing (Road pricing), Uncertainty, Travel models (Travel demand), Travel demand, Transportation policy, Transportation planning, Scenarios, Sacramento (California), Road pricing, Ring roads, Projections, Priority lanes, Loops (Highways), Light rail transit, Land use transport interaction models, Land use, HOV lanes, High occupancy vehicle lanes, Forecasting, Economic models, Diamond lanes, Circumferential highways, Carpool lanes, Calibration, Calibrating, Beltways, Belt highways


Three land use and transport interaction models were applied to the Sacramento, California, region by various teams of researchers. The results of these efforts were compared with each other and with the traditional transport demand model used by the regional government. The results of the modeling efforts are compared, with the focus being on how the design of the modeling frameworks and their application influenced the modeling results. A trend scenario was compared with three different policy scenarios: one that involved high-occupancy vehicle (HOV) lane construction, one that added beltway construction as well as HOV construction, and a third that involved light rail construction and limited pricing of automobile use. The results differ among the different models for the trend scenario, as well as for each model with respect to scenario-to-trend comparisons. The results show some of the limitations of aggregate models calibrated to cross-sectional data. The differences between the models provide important insight into how models should be calibrated and how their results should be used. Uncertainty in land use transport interaction models seems inevitable, and further research should investigate how such modeling frameworks should best be used to understand the influence of policy in the face of uncertain futures.