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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Area of Science:

  • Urban planning
  • Transportation engineering
  • Network analysis

Background:

  • Traffic congestion is a complex, dynamic issue in urban networks.
  • Effective traffic management requires understanding and clustering congestion patterns.
  • Perimeter control, using macroscopic fundamental diagrams, is a key strategy, but relies on homogenous traffic regions.

Purpose of the Study:

  • To develop a cost-effective method for defining homogenous, contiguous, and compact traffic clusters.
  • To improve the precision of perimeter control by ensuring reliable regional homogeneity.
  • To offer a computationally efficient approach for urban traffic management.

Main Methods:

  • Utilizing a community detection algorithm (Infomap) to initially identify clusters.
  • Refining identified communities by considering road heterogeneity for improved boundary definition.
  • Applying and validating the method on real-world data from Shenzhen, China, and San Francisco, USA.

Main Results:

  • The proposed method effectively detects homogenous traffic communities.
  • It demonstrates superior performance in ensuring cluster contiguity compared to previous methods.
  • The approach guarantees the connectedness of clusters, a critical requirement for perimeter control.

Conclusions:

  • The developed method provides a robust and efficient way to define traffic management regions.
  • It enhances perimeter control strategies by ensuring prerequisite conditions like homogeneity and connectedness.
  • This research offers a significant advancement in urban traffic flow optimization.