Distributed consensus based adaptive ramp metering algorithms in freeway systems

In recent years, traffic management has the attention of many researchers due to the public's increasing demand for fast, efficient, and convenient means of travel. In the literature, there has been a vast amount of research and improvement on traffic management control in freeways in various forms such as optimization, consensus protocols, and nonlinear control. The objective of this thesis is to develop a distributed consensus based ramp metering algorithm with the coordination of the traffic network. The applications of the distributed consensus algorithms in the literature indicate the importance of design and analysis of consensus protocols with which the agents in the systems achieve a common objective by exchanging information. Contrary to existing studies on coordinated ramp metering, centralized and decentralized on-ramp flow control algorithms are proposed without assigning priorities to on-ramps with bottlenecks at the upstream cells. Subsequently, the on-ramp flow control algorithm is improved with a consensus based density control algorithm which provides a smooth traffic density in the traffic infrastructure. At the final step, the mainstream inflow control is utilized in order to achieve the decided on-ramp flow and the traffic density. The averaging based and minimum consensus protocols are used to control the mainstream inflow. The performance and the convergence speed analysis of the proposed algorithms are evaluated with numerical simulations.