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New approaches for the traffic counting location problem

2019; Elsevier BV; Volume: 132; Linguagem: Inglês

10.1016/j.eswa.2019.04.068

1873-6793

Pedro Henrique González, Glaubos Clímaco, Geraldo Regis Mauri, Bruno Salezze Vieira, Glaydston Mattos Ribeiro, Rômulo Dante Orrico Filho, Luidi Simonetti, Leonardo Roberto Perim, Ivone Catarina Simões Hoffmann,

Human Mobility and Location-Based Analysis

The traditional traffic counting location problem (TCLP) aims to determine the location of counting stations that would best cover a road network for the purpose of obtaining traffic flows. This information can be used, for example, to estimate origin-destination (OD) trip tables. It is well noted that the quality of the estimated OD trip tables is related to an appropriate set of links with traffic counters and to the quality of the traffic counting. In this paper, we propose two methods (Branch-and-Cut algorithm and Clustering Search heuristic) to define the location of the traffic counters in a network, in order to count all flows between origins and destinations. A Genetic Algorithm heuristic presented in the literature is implemented in order to perform a fair comparison of results. Computational experiments conducted on real instances, composed by the Brazilian states, have shown the benefit of the proposed methods. Statistical tests show that Clustering Search heuristic has outperformed all other approaches.