by Kazem Oryani
In this paper we will discuss our methodology in reviewing land use models and identifying desired attributes for recommending a model for application by the Delaware Valley Planning Commission (DVRPC). The need for land-use transportation interaction is explored, followed by a synthesis of inventory of land use models for agency use. This is followed by an overview of three operational land use models.
Details of three operational models — DRAM-EMPAL (S. H. Putman), MEPLAN (Marcial Echenique)
and METROSIM (Alex Anas) — are explored in terms of model formulation and special features. In order to draw on the main factors in implementation, we conducted detailed telephone interviews with five major Metropolitan Planning Organizations (MPOs) who use land use models. These interviews were performed as part of our work for the enhancement of DVRPC’s travel simulation models in 1996.
A two-step model selection and implementation process is proposed. The recommendation is that limited versions of the above three modes be acquired for prototype use, policy analysis and impact assessment. The final selection will be based on objective performance of the models using a similar battery of tests on the same data sets.
Details of three operational models — DRAM-EMPAL (S. H. Putman), MEPLAN (Marcial Echenique)
and METROSIM (Alex Anas) — are explored in terms of model formulation and special features. In order to draw on the main factors in implementation, we conducted detailed telephone interviews with five major Metropolitan Planning Organizations (MPOs) who use land use models. These interviews were performed as part of our work for the enhancement of DVRPC’s travel simulation models in 1996.
A two-step model selection and implementation process is proposed. The recommendation is that limited versions of the above three modes be acquired for prototype use, policy analysis and impact assessment. The final selection will be based on objective performance of the models using a similar battery of tests on the same data sets.
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