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A Framework for Identifying Critical Areas in Urban Road Networks Based on Percolation Theory Using Real Data

Ghandi Jelvani, Amin | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57609 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Amini, Zahra
  7. Abstract:
  8. Transportation networks serve as the primary foundation for economic growth and the development of nations. These networks play a pivotal role by facilitating the movement of goods and passengers, as well as providing essential resources for human activities. With the rapid urbanization and increasing population in cities, the importance and efficiency of these networks have become even more critical. Among the significant challenges faced in urban areas is traffic congestion, which leads to substantial costs, including wasted time and energy, and has negative impacts on public health. As a result, numerous studies have been conducted on the formation and spread of congestion in streets and traffic networks. Nevertheless, the adverse effects of traffic disruptions and the considerable costs they incur remain undeniable. The significance of this issue, coupled with increasing access to real-world transportation data, underscores the necessity for further research into organizing congestion in urban transportation networks. This thesis explores the application of percolation theory to analyze and understand the complex structure of urban transportation networks. The research provides a framework that utilizes percolation theory to evaluate the structure of traffic networks in various cities and assess their performance in serving traffic flow during different times of the day. The proposed framework dynamically identifies traffic bottlenecks in both temporal and spatial dimensions within urban traffic networks and offers a comprehensive, independent tool for urban decision-makers. To validate the research, real-time daily data from three cities—Berlin, Istanbul, and Moscow—was analyzed. The results demonstrate that percolation theory can be effectively used as a tool for monitoring the traffic service conditions of cities
  9. Keywords:
  10. Percolation Theory ; Dynamic Network Clustering ; Macroscopic Fundamental Diagram ; Network Critical Zone ; Traffic Bottlenecks

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