Citation

González PH, Clímaco G, Mauri GR, Vieira BS, Ribeiro GM, Orrico Filho RD, Simonetti L, Perim LR, Hoffmann ICS. Expert Syst. Appl. 2019; 132: 189-198.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.eswa.2019.04.068

PMID

unavailable

Abstract

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.

Language: en

Keywords

Branch-and-Cut; Metaheuristics; Traffic count location