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Improving the Stability of an Urban Traffic Network with Limited Data by Using Percolation Theory and Dynamic Clustering

Hassanzadeh, Ehsan | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55230 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Amini, Zahra
  7. Abstract:
  8. One of the most vital aspects of understanding the traffic phenomenon is scrutinizing the traffic transition status, such as the transition from free flow to congestion. The Percolation Theory is a renowned theory focusing on analyzing various network types to detect the critical zones, which are the zones including links that are important to control to improve stability. By calculating the quality indices of network links, the Percolation Theory can simulate the traffic percolation propagation in the network and determine possible critical zones for further analysis. Most studies in this field assume access to data of several traffic parameters for the entire transportation network, such as velocity and density, which require more advanced types of traffic sensing apparatus. This study provides a framework by applying the Percolation Theory for dynamically detecting critical zones in an urban traffic network with limited flow data. The proposed framework is applied to a dataset of recorded flows from Tehran city, Iran, in 2018. The results demonstrate that the overall network performance is enhanced significantly by increasing the capacity of the critical zone. These results provide promising findings for improving stability in urban networks
  9. Keywords:
  10. Percolation Theory ; Urban Transportation Network ; Dynamic Network Traffic ; Transportation Network Stability ; Dynamic Network Clustering ; Network Critical Zone

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