TY - JOUR
T1 - Optimal allocation of public parking spots in a smart city
T2 - problem characterisation and first algorithms
AU - Arellano-Verdejo, Javier
AU - Alonso-Pecina, Federico
AU - Alba, Enrique
AU - Guzmán Arenas, Adolfo
N1 - Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/7/4
Y1 - 2019/7/4
N2 - 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.
AB - 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.
KW - NP problem
KW - Parking
KW - evolutionary algorithms
KW - smart cities
UR - http://www.scopus.com/inward/record.url?scp=85063863763&partnerID=8YFLogxK
U2 - 10.1080/0952813X.2019.1591522
DO - 10.1080/0952813X.2019.1591522
M3 - Artículo
AN - SCOPUS:85063863763
SN - 0952-813X
VL - 31
SP - 575
EP - 597
JO - Journal of Experimental and Theoretical Artificial Intelligence
JF - Journal of Experimental and Theoretical Artificial Intelligence
IS - 4
ER -