  Driver assistance systems support drivers in operating vehicles in a safe,
comfortable and efficient way, and thus may induce changes in traffic flow
characteristics. This paper puts forward a receding horizon control framework
to model driver assistance and cooperative systems. The accelerations of
automated vehicles are controlled to optimise a cost function, assuming other
vehicles driving at stationary conditions over a prediction horizon. The
flexibility of the framework is demonstrated with controller design of Adaptive
Cruise Control (ACC) and Cooperative ACC (C-ACC) systems. The proposed ACC and
C-ACC model characteristics are investigated analytically, with focus on
equilibrium solutions and stability properties. The proposed ACC model produces
plausible human car-following behaviour and is unconditionally locally stable.
By careful tuning of parameters, the ACC model generates similar stability
characteristics as human driver models. The proposed C-ACC model results in
convective downstream and absolute string instability, but not convective
upstream string instability observed in human-driven traffic and in the ACC
model. The control framework and analytical results provide insights into the
influences of ACC and C-ACC systems on traffic flow operations.
