  The unknown sharp changes of vehicle acceleration rates, also called the
unknown jerk dynamics, may significantly affect the driving performance of the
leader vehicle in a platoon, resulting in more drastic car-following movements
in platooning tracking control, which could cause safety and traffic capacity
concerns. To address these issues, in this paper, we investigate cooperative
platooning tracking control and intermittent optimization problems for
connected automated vehicles (CAVs) with a nonlinear car-following model. We
assume that the external inputs of the leader CAV contain unknown but bounded
jerk parameters, and the acceleration signals of the leader CAV are known only
to a few neighboring follower CAVs in a free-design but directed communication
network. To solve these problems, a distributed observer law is developed to
provide a reference signal expressed as an estimated unknown jerk dynamic of
the leader CAV and implemented by each follower CAV. Then, a novel distributed
platooning tracking control protocol is proposed to construct the cooperative
tracking controllers under identical inter-vehicle constraints, which can
ensure a desired safety distance among the CAVs and allow each follower CAV to
track their leader CAV by using only local information interaction. We also
present a novel intermittent sampling condition and a robust intermittent
optimization design that can ensure optimally scheduled feedback gains for the
cooperative platooning tracking controllers to minimize the control cost under
nonidentical inter-vehicle constraints and unknown jerk dynamics. Simulation
case studies are carried out to illustrate the effectiveness of the proposed
approaches
