  Earlier work has established a decentralized framework to optimally control
Connected Automated Vehicles (CAVs) crossing an urban intersection without
using explicit traffic signaling while following a strict First-In-First-Out
(FIFO) queueing structure. The proposed solution minimizes energy consumption
subject to a FIFO-based throughput maximization requirement. In this paper, we
extend the solution to account for asymmetric intersections by relaxing the
FIFO constraint and including a dynamic resequencing process so as to maximize
traffic throughput. To investigate the tradeoff between throughput maximization
and energy minimization objectives, we exploit several alternative problem
formulations. In addition, the computational complexity of the resequencing
process is analyzed and proved to be bounded, which makes the online
implementation computationally feasible. The effectiveness of the dynamic
resequencing process in terms of throughput maximization is illustrated through
simulation
