  We address the problem of controlling Connected and Automated Vehicles (CAVs)
in conflict areas of a traffic network subject to hard safety constraints. It
has been shown that such problems can be solved through a combination of
tractable optimal control problem formulations and the use of Control Barrier
Functions (CBFs) that guarantee the satisfaction of all constraints. These
solutions can be reduced to a sequence of Quadratic Programs (QPs) which are
efficiently solved on line over discrete time steps. However, the feasibility
of each such QP cannot be guaranteed over every time step. To overcome this
limitation, we develop an event-driven approach such that the next QP is
triggered by properly defined events and show that this approach can eliminate
infeasible cases due to time-driven inter-sampling effects. Simulation examples
show how overall infeasibilities can be significantly reduced with the proposed
event-triggering scheme, while also reducing the need for communication among
CAVs without compromising performance.
