Traffic sensors serve an important function in obtaining traffic information. In this paper, a novel traffic sensor location approach is proposed to determine the maximum number of traffic flows by considering the time-spatial correlation. The problem is formulated as three 0–1 programming models to maximise the number of obtained flows under different cases. To solve these novel sensor location problems, an ant colony optimisation algorithm with a local search procedure is designed. Numerical experiments are conducted in both a simulated network and in the Sioux–Falls network. Results demonstrate the effectiveness and robustness of the proposed algorithm, which is believed to possess potential applicability in real surveillance network design.
Traffic sensor location approach for flow inference
IET Intelligent Transport Systems ; 9 , 2 ; 184-192
2015-03-01
9 pages
Article (Journal)
Electronic Resource
English
time-spatial correlation , Sioux–Falls network , sensor placement , search problems , road traffic control , simulated network , flow inference , SLP problem , traffic sensor location approach , ant colony optimisation algorithm , network theory (graphs) , local search procedure , real surveillance network design , ant colony optimisation , 0–1 programming model
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