  We develop a systemic risk framework to explore cascading systemic failures
in networked control systems. A time-delayed version of the vehicle platooning
problem is used as a benchmark to study the interplay among network
connectivity, system dynamics, physical limitations, and uncertainty onto the
possibility of cascading failure phenomena. The measure of value-at-risk is
employed to investigate the domino effect of failures among pairs of vehicles
within the platoon. The systemic risk framework is suitably extended to
quantify the robustness of cascading failures via a novel manipulation of
bi-variate distribution. We establish closed-form risk formulas that explain
the effect of network parameters (e.g., Laplacian eigen-spectrum, time delay),
noise statistics, and systemic event sets onto the cascading failures. Our
findings can be applied to the design of robust platoons to lower the cascading
risk. We support our theoretical results with extensive simulations.
