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answering particular questions or testing specific policies, and how to use them via first-hand experience running three models for testing a variety of policy issues.  As the course progressed from simple models to the more complex models the students were able to first, understand the necessity for the more complex models and second, gain an appreciation of the difficulties involved in using them.

Placing the model in the hands of students created the need for the GUI to check each input and parameter change to ensure that it was within allowable limits. The GUI also allows for quick and easy side-by-side comparisons of outputs generated by different policy scenarios. Many model runs are necessary, in order to understand the model, and to explore all policy combinations for desired effects. Many counterintuitive effects occur, that lead to the users learning about urban economic behaviors, in general, and about local problems with land uses and transportation systems.   

The development and use the GUI for the Sacramento MEPLAN model proved to be successful, but it was a close call with the last-minute debugging. Overall, this effort was worth it, as the students' Final Papers were rich with groups of scenarios that were designed to test various economic and political concepts. They certainly learned that full urban models are complex to calibrate (from the readings and lectures), and to operate and interpret the results (from their direct experiences).

It is useful to compare this experience with those of instructors who teach travel modeling in U.S. universities. Generally, the instructors have the students estimate logit mode choice models from cleaned-up regional household travel survey datasets. The rest of the MPO's model set is explained, but seldom do students have to actually run the model systems software to get results for regional policy scenarios. This is probably

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