Integrated Transportation and Land Use Modeling by Using Simulation Methods (Case Study: ‌Qom)

Document Type : Original Article

Authors

1 Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.

2 Associate Professor, School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.

3 Ph.D., Grad., School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.

4 M.Sc., Student, Department of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.

10.22034/tri.2021.118089

Abstract

These days, many researchers and planners pay a lot of attention to the mutual relations as a common border between transportation planning models and land use models. The impacts of land use patterns in trip generation and trip distribution are of high significance. Using integrated land use and transportation models causes the possibility for forecasting different areas’ development, changes in trips patterns in traffic zones and also provides more precise predictions and reduces errors. These scenarios may contain different control policies, strategic projects and developing infrastructures. Therefore, in this research, a pattern of location choice for living and working with following goals has been provided by using discrete choice model in Urbansim software for Qom city: providing an integrated transportation and land use model regarding land price and people behaviors, analysis of different effective factors in location choice for living and working to predict the changes in locations, calculating the effects of local house pricing policies on transportation. For conducting this research, effective variables have been identified and different social and economic information were gathered from authorities and governmental organizations. At the next step, according to the base year information, the processes of making models and calibration have been done and all land use models and sub models were made. It is followed by evaluating based on unused data and finally presenting a set of integrated models in order to recognizing population and job distribution in the horizon year. Results show that accessibility between traffic zones, economic and social variables such as income, number of people in each family, car ownership and land price are important factors in determining living and working locations in Qom. Furthermore, people in different age groups with different income have various priorities for their living and working locations.

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