Optimal allocation of public parking spots in a smart city: problem characterisation and first algorithms: problem characterisation and first algorithms

Javier Arellano-Verdejo, Federico Alonso-Pecina, Enrique Alba, Adolfo Guzmán Arenas

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Having a mechanism to mathematically model the problem of the optimal allocation of parking spots within cities could bring great benefits to society. According to the International Parking Institute, about 38% of the cars circulating throughout a city are looking for available parking spots, leading to increased pollution and subsequent health problems, as well as economic losses due to wasted man-hours. In the work presented here, a new mathematical model describing the problem of the optimal allocation of parking spots is proposed, along with an evolutionary algorithm to demonstrate how this model can be used in practice. A simulated annealing algorithm was implemented to test the effectiveness of this approach. The proposed strategy will allow users to find parking more quickly and easily, as well as lead to new services for the hot-topic of smart mobility. For the definition of the problem, a real map of the city of Malaga, Spain, was used along with Sumo software to carry out the simulations. The results clearly demonstrated that the proposed mechanism is capable of minimising the global cost of parking, implying a direct benefit for users.

Original languageEnglish
Pages (from-to)575-597
Number of pages23
JournalJournal of Experimental and Theoretical Artificial Intelligence
Volume31
Issue number4
DOIs
StatePublished - 4 Jul 2019

Keywords

  • evolutionary algorithms
  • NP problem
  • Parking
  • smart cities

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