Abstract
Given that there are restrictions on expanding the infrastructure for the purpose of fulfilling future transportation demand, it is critical to consider the capacity of the existing transportation system and the sustainable extent of development, in order to avoid problems such as traffic congestion and air pollution. In this study, by applying the inverse of conventional transportation planning, which is different from the land-use transportation interaction modeling, land-use limits for each Traffic Analysis Zone (TAZ) are determined as a function of the transportation system capacity. Indeed, this method is applied to examine the trip generation capacity of each TAZ with respect to its trip end values. Comparing the indicated capacity with the current demand for each zone can act as a key tool for urban policy makers and planners to define the spatial distribution of new activities based on the present capacity of the transportation system in the studied area. For this purpose, after selecting the transportation network of the central business district in the City of Isfahan as a case of study, the artificial neural networks solution is used to solve the inverse transportation planning problem.
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