Optimizing traffic patrol based on generalized maximal covering model

In this paper, we present a method to evaluate and optimize traffic patrol based on the generalized maximal covering model. We first build a criterion to evaluate how well a traffic patrol deployment is, and then we formulate an optimization problem for selecting optimal patrol centers from candidates. We show that the optimal patrol centers can be found by an algorithm derived from the method of Lagrange relaxation. Experiments over the datasets of the downtown of Hangzhou demonstrate that the proposed algorithm is effective and useful in the practical situations.