  Cooperative driving, enabled by communication between automated vehicle
systems, is expected to significantly contribute to transportation safety and
efficiency. Cooperative Adaptive Cruise Control (CACC) and platooning are two
of the main cooperative driving applications that are currently under study.
These applications offer significant improvements over current advanced driver
assistant systems such as adaptive cruise control (ACC). The primary motivation
of CACC and Platooning is to reduce traffic congestion and improve traffic
flow, traffic throughput, and highway capacity. These applications need an
efficient controller to consider the computational cost and ensure driving
comfort and high responsiveness. The advantage of Model Predictive Control is
that we can realize high control performance since all constrain for these
applications can be explicitly dealt with through solving an optimization
problem. These applications highly depend on information update and
Communication reliability for their safety and stability purposes. In this
paper, we propose a Model Predictive Control (MPC) based approach for CACC and
platooning, and examine the impact of communication loss on the performance and
robustness of the control scheme. The results show an improvement in response
time and string stability, demonstrating the potential of cooperation to
attenuate disturbances and improve traffic flow.
