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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Smart-parking management algorithms in smart city.

Mahdi Jemmali1,2,3, Loai Kayed B Melhim4, Mafawez T Alharbi5

  • 1Department of Computer Science and Information, College of Science in Zulfi, Majmaah University, AL-Majmaah, 11952, Saudi Arabia. m.jemmali@mu.edu.sa.

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This summary is machine-generated.

This study introduces a new framework with seven algorithms for equitable smart city parking lot allocation, ensuring efficient traffic flow. The MR algorithm demonstrated superior performance, achieving 96.1% efficiency with minimal gaps and fast execution times.

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Area of Science:

  • Smart City Technologies
  • Urban Planning
  • Artificial Intelligence

Background:

  • Smart cities leverage advanced technologies to enhance urban living quality.
  • Efficient parking management is crucial for smooth traffic flow in smart cities.
  • Equitable distribution of people across parking spaces is a key challenge.

Purpose of the Study:

  • To propose a novel framework for smart parking lot allocation.
  • To ensure equitable distribution of people among available parking spaces.
  • To develop algorithms that minimize the population gap between parking lots.

Main Methods:

  • Development of a set of seven algorithms for parking lot allocation.
  • Emphasis on equitable allocation based on population counts and available spaces.
  • Extensive experimentation on 2430 cases to evaluate performance.

Main Results:

  • The developed algorithms demonstrate good performance in gap reduction and execution time.
  • The MR algorithm outperformed existing literature algorithms.
  • MR algorithm achieved 96.1% performance, with an average gap of 0.02 and execution time of 0.007s.

Conclusions:

  • The proposed algorithms effectively address the parking lot allocation problem.
  • The framework ensures equitable distribution and efficient traffic management.
  • The MR algorithm offers a highly efficient solution for smart city parking challenges.