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Internal boundary control of Lane-free automated vehicle traffic

Malekzadehkebria Milad

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Summary

Road transportation is undergoing a profound transformation, which is triggered by significant technological developments regarding the road infrastructure, the vehicles and the traffic management. In this context, vehicles communicate seamlessly with each other and with the infrastructure and are guided by real-time data and advanced algorithms, allowing them to move autonomously. Connected Automated Vehicles (CAVs) are equipped with an array of sensors, cameras, Lidar, radar, and V2X (Vehicle-to-Everything) communication systems. These technologies enable vehicles to "see" their surroundings, exchange information with nearby vehicles, traffic signals, and infrastructure, and make intelligent decisions based on this collective awareness.One of the many advancements that have come about in this context is the TrafficFluid paradigm, which is a forward-thinking approach to road mobility that becomes increasingly important in the age of CAVs. TrafficFluid proposes lane-free movement of vehicles. Traditionally, roads have been demarcated by parallel lanes to ease human driving. However, the lane-free paradigm represents a departure from this rigid framework in the era of CAVs. Instead of confining vehicles to predefined lanes, it envisions a dynamic and adaptable traffic ecosystem.Lane-free traffic implies that incremental road widening (narrowing) leads to corresponding incremental increase (decrease) of capacity; and this opens the way for consideration of real-time Internal Boundary Control (IBC) on highways and arterials, in order to flexibly share the total (both directions) road width and capacity among the two directions in dependence of the bi-directional demand and traffic conditions, so as to maximize the total (two directions) flow efficiency. The problem is initially presented in this thesis as a convex Quadratic Programming (QP) problem, which can be solved easily and effectively. Furthermore, the novel IBC control action is thoroughly investigated through various case studies, which highlight its features, capabilities and potential. This thesis efficiently addresses IBC also in a second step by developing suitable feedback-based Linear-Quadratic regulators, with or without integral action (LQI and LQ regulators). The proposed regulators have been put to the test through macroscopic simulation investigations that involve different demand scenarios on a realistic highway stretch. The findings indicate that the regulators can be just as efficient as an open-loop nonlinear constrained optimal control solution. Furthermore, the regulators do not require accurate modeling or external demand prediction, thus being more robust. Nonetheless, centralized solutions that call for information from the entire highway stretch being considered can be burdensome for lengthy highways in relation to the scope of required real-time communication. Therefore, during the third step of this work, two different decentralized control schemes, specifically overlapping LQR method and Linear Matrix Inequality (LMI) method, are developed for IBC in lane-free CAV traffic.As a final step, the present thesis completes and validates the IBC concept in a much more realistic way via microscopic simulation and active internal boundary moving, using the SUMO-based TrafficFluid-Sim simulation tool. To effectuate IBC, an LQR feedback control scheme is employed. In addition, to enhance the performance of the LQR controller, a feedforward term, accounting for external disturbances, i.e. mainstream entering flow and on-ramp flows, is designed, leading to an augmented LQR-FF control scheme. The LQR and LQR-FF controllers are tested and compared in the created realistic environment, demonstrating how IBC may operate in practice to combat traffic congestion on highways with unprecedented efficiency.

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