The implementation of connected and automated vehicle (CAV) technologies
enables a novel computational framework for real-time control actions aimed at
optimizing energy consumption and associated benefits. Several research efforts
reported in the literature to date have proposed decentralized control
algorithms to coordinate CAVs in various traffic scenarios, e.g., highway
on-ramps, intersections, and roundabouts. However, the impact of optimally
coordinating CAVs on the performance of a transportation network has not been
thoroughly analyzed yet. In this paper, we apply a decentralized optimal
control framework in a transportation network and compare its performance to a
baseline scenario consisting of human-driven vehicles. We show that introducing
of CAVs yields radically improved roadway capacity and network performance.