For this study, we developed one of the first statewide pedestrian exposure models, using log-linear regression to estimate annual pedestrian crossing volumes at intersections on the California State Highway System. We compiled a database of more than 1,200 count locations, one of the largest ever used to create a pedestrian volume mode. We initially evaluated 75 explanatory variables for the model. The final model is based on the three land-use variables (employment density, population density, number of schools), four roadway network variables (number of street segments, intersections...