Traffic sensor location approach for flow inference

Abstract

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.