file structures, but none for this application specifically. It was decided to make only a few inputs available to the students, to simplify their efforts. The goal was for them to be able to manipulate both the travel market and the land market represented in MEPLAN. The students were allowed access to the global variable for out-of-pocket costs for auto travel (default is $0.15/mi.). This could represent higher auto costs (including a change in gasoline taxes), or lower relative transit costs. We also let them select the regional transportation network, but limited these to: No Build, New HOV Lanes (on all freeways), and Transit (which added new light rail lines and feeder buses and reduced headways on the whole system). These, and other, networks had been prepared for earlier research by Johnston and others, using this model. Network preparation for this model was time-consuming and so having them already done was one reason to use this model. Network editing for travel models and for some urban models has only recently become fairly easy to do, using GIS-based methods.
Two inputs for the land market were also selected. First, the students were allowed to change the acres available for development in the 53 internal zones in the (four-county) model. In each zone, they were allowed to interchange available, vacant land among four land use types: Open space (not developable), Industrially designated land (which permitted all developed land use types), Medium-density residential, and Low-Density residential. Most of these lands in the region have Open Space or Medium- and Low-Density Residential zoning designations so this subset of land uses made the majority of undeveloped land available to manipulate in most zones. The Access GUI was designed to keep the zonal acreage totals the same (necessary for the model to run properly). The students could simulate NIMBYism by restricting land availability in