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Traffic congestion is a major challenge in urban areas, and is associated with longer travel times, increased vehicle emissions, and numerous vehicle crashes. Creating an efficient mobility system is difficult, given that each driver is usually trying to optimize their individual trip within the network without accounting for other road users. However, new technologies in modern vehicles, especially connected vehicle technologies, make it increasingly possible to find solutions to network efficiency problems. Connected technologies allow data sharing between vehicles, allowing for greater system optimization. This work takes advantage of connectivity to develop a global framework to increase transportation network efficiency and address the aforementioned challenges. To enhance mobility, this paper presents a dynamic freeway speed controller based on the sliding mode theory, which uses the fundamental equations governing traffic dynamics in combination with variable speed limit control in order to provide advisory speeds for connected vehicles. Simulation results on a downtown Los Angeles network show significant reductions in trip times and delays both on freeways (where the control was activated) and network-wide (i.e., freeways and other roadways). Specifically, the results for the entire network showed a 12.17% reduction in travel time and a 20.67% reduction in total delay. These results had the secondary effect of reducing fuel consumption and therefore CO 2 emissions by 2.6% and 3.3%, respectively. The results for the freeway network alone showed a 20.48% reduction in travel time and a 21.63% reduction in queued vehicles. These results reveal the significant potential benefits of using the proposed speed harmonization controller on real large-scale networks. INDEX TERMS Connected vehicles, large scale network, sliding control, speed harmonization, variable speed control.