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.

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Urban traffic congestion is a chronic problem faced by many cities in the US and worldwide. It results in inefficient infrastructure use as well as increased vehicle fuel consumption and emission levels. Congestion is intertwined with delay, as road users waste precious hours on the road, which in turn reduces productivity. Researchers have developed, and continue to develop, tools and systems to alleviate this problem. Network perimeter control is one such tool that has been studied extensively. It attempts to control the flow of vehicles entering a protected area to ensure that the congested regime predetermined by the Network Fundamental Diagram (NFD) is not reached. In this paper, an approach derived from sliding mode control theory is presented. Its main advantages over proportional-integral controllers include (1) minimal tuning, (2) no linearization of the governing equations, (3) no assumptions with regard to the shape of the NFD, and (4) ability to handle various demand profiles without the need to retune the controller. A sliding mode controller was implemented and tested on a congested grid network. The results show that the proposed controller produces network-wide delay savings and disperses congestion effectively.Index Terms-Network fundamental diagram, network perimeter control, sliding mode control, traffic signal control

This paper compares the operation of a decentralized Nash bargaining traffic signal controller (DNB) to the operation of state-of-the-art adaptive and gating traffic signal control. Perimeter control (gating), based on the network fundamental diagram (NFD), was applied on the borders of a protected urban network (PN) to prevent and/or disperse traffic congestion. The operation of gating control and local adaptive controllers was compared to the operation of the developed DNB traffic signal controller. The controllers were implemented and their performance assessed on a grid network in the INTEGRATION microscopic simulation software. The results show that the DNB controller, although not designed to solve perimeter control problems, successfully prevents congestion from building inside the PN and improves the performance of the entire network. Specifically, the DNB controller outperforms both gating and non-gating controllers, with reductions in the average travel time ranging between 21% and 41%, total delay ranging between 40% and 55%, and emission levels/fuel consumption ranging between 12% and 20%. The results demonstrate statistically significant benefits of using the developed DNB controller over other state-of-the-art centralized and decentralized gating/adaptive traffic signal controllers.

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