  Safety is the foremost concern for autonomous platooning. The
vehicle-to-vehicle (V2V) communication delay and the sudden appearance of
obstacles will trigger the safety of the intended functionality (SOTIF) issues
for autonomous platooning. This research proposes a holistic robust motion
controller framework (MCF) for an intelligent and connected vehicle platoon
system. The MCF utilizes a hierarchical structure to resolve the longitudinal
string stability and the lateral control problem under the complex driving
environment and time-varying communication delay. Firstly, the H-infinity
feedback controller is developed to ensure the robustness of the platoon under
time-varying communication delay in the upper-level coordination layer (UCL).
The output from UCL will be delivered to the lower-level motion-planning layer
(LML) as reference signals. Secondly, the model predictive control (MPC)
algorithm is implemented in the LML to achieve multi-objective control, which
comprehensively considers the reference signals, the artificial potential
field, and multiple vehicle dynamics constraints. Furthermore, three critical
scenarios are co-simulated for case studies, including platooning under
time-varying communication delay, merging, and obstacle avoidance scenarios.
The simulation results indicate that, compared with single-structure MPC, the
proposed MCF can offer a better suppression on position error propagation, and
get improvements on maximum position error in the three scenarios by $19.2\%$,
$59.8\%$, and $15.3\%$, respectively. Last, the practicability and
effectiveness of the proposed MCF are verified via hardware-in-the-loop
experiment. The average conducting time of the proposed method on Speedgoat
real-time target machine is 1.1 milliseconds, which meets the real-time
requirements.

Systems and Control;Systems and Control