Using Spatial Analysis and Decision Support Systems for Design and Development of Urban Roads

‎The rapid growth of cities is a global phenomenon that has become a challenge in our country. The lack of development of urban infrastructures at the same time as the expansion of cities, especially in the transportation sector, has created many problems such as heavy traffic and air pollution for big cities. The aim of this research is to provide a solution to deal with the challenges facing the city of Tehran in the field of development of urban roads by using analysis based on geographic information system (GIS) and decision support systems so that it can improve planning in construction. And the development of urban roads achieved a sustainable development in the transportation sector. For this reason, it is very important to know the current situation in planning for road development in Tehran, to identify areas for improvement and to provide solutions based on GIS. These solutions lead to optimization of route selection, environmental impact assessments, efficient project cost management and effective risk management.

To achieve the research objectives, a multifaceted method was adopted. At first, the collection of spatial data related to the urban road network including transportation networks, environmental parameters and existing road infrastructures was done. Then, GIS technology was used to perform spatial analysis, route optimization using Dijkstra's shortest path algorithm (SPA) and environmental impact assessments. Decision support systems were developed to facilitate data-based decision making in each scenario in road construction project analysis. Finally, the scenarios obtained from the spatial analysis were compared with the road construction operational projects.

The results of this research showed the significant capacity of spatial information analysis based on GIS and decision support systems in modifying planning for the development of road construction in urban Tehran. These technologies reduce urban traffic by 20% through optimal route selection and improve the efficiency of urban transportation. Environmental impact assessments also showed that the use of these methods can lead to a 36% reduction in harmful effects, including air pollution. Also, the integration of GIS-based cost management tools led to the reduction of road construction costs. Identifying risk reduction strategies through spatial analysis ensures the success of the project in terms of timing and cost and ultimately leads to the satisfaction of citizens.

Using GIS-based spatial analysis and SPA algorithm, routes with minimum travel time were identified that reduce traffic and increase transportation efficiency. Reduction in travel time can lead to increase in productivity and improve the quality of life of citizens. In addition, optimized routing can help reduce fuel consumption and air pollution. In addition, the Environmental Impact Assessment (EIA) index has shown a significant improvement in the environmental sustainability of scenarios that are based on spatial analysis. Thus, reducing the levels of air and noise pollution and maintaining green spaces can help to increase the quality of life of citizens. In addition, reducing harmful environmental effects can contribute to the long-term growth and development of the city. On the other hand, by identifying capacity risk in the planning stage, project managers can allocate resources more effectively and implement measures to prevent delays and cost overruns.