Traffic signal control is one of the most common means of traffic management in urban areas. To create an efficient urban transportation network, the optimization of signal control strategy is required. Various methods and tools can be used for that purpose. This study proposes two signal control algorithms that are based on backpressure model, which is originally developed to maximize the throughput in communication networks. Thus, one of the goals was to determine if such control strategies can lead to maximum throughput through an urban traffic network. In addition, the evaluation of the two algorithms included comparison of their performances with the performances of the conventional signal control strategies in microsimulation software. Evaluation results, in terms of various performance measures, demonstrate that backpressure control models are outperformed by conventional (fixed and actuated) signal timings optimized by a genetic algorithm.