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Earlier work has established a decentralized framework to optimally controlConnected Automated Vehicles (CAVs) crossing an urban intersection withoutusing explicit traffic signaling while following a strict First-In-First-Out(FIFO) queueing structure. The proposed solution minimizes energy consumptionsubject to a FIFO-based throughput maximization requirement. In this paper, weextend the solution to account for asymmetric intersections by relaxing theFIFO constraint and including a dynamic resequencing process so as to maximizetraffic throughput. To investigate the tradeoff between throughput maximizationand energy minimization objectives, we exploit several alternative problemformulations. In addition, the computational complexity of the resequencingprocess is analyzed and proved to be bounded, which makes the onlineimplementation computationally feasible. The effectiveness of the dynamicresequencing process in terms of throughput maximization is illustrated throughsimulation

A Decentralized Optimal Control Framework for Connected Automated Vehicles at Urban Intersections with Dynamic Resequencing