  Adaptive-Cruise Control (ACC) automatically accelerates or decelerates a
vehicle to maintain a selected time gap, to reach a desired velocity, or to
prevent a rear-end collision. To this end, the ACC sensors detect and track the
vehicle ahead for measuring the actual distance and speed difference. Together
with the own velocity, these input variables are exactly the same as in
car-following models. The focus of this contribution is: What will be the
impact of a spreading of ACC systems on the traffic dynamics? Do automated
driving strategies have the potential to improve the capacity and stability of
traffic flow or will they necessarily increase the heterogeneity and
instability? How does the result depend on the ACC equipment level?
  We discuss microscopic modeling aspects for human and automated (ACC)
driving. By means of microscopic traffic simulations, we study how a variable
percentage of ACC-equipped vehicles influences the stability of traffic flow,
the maximum flow under free traffic conditions until traffic breaks down, and
the dynamic capacity of congested traffic. Furthermore, we compare different
percentages of ACC with respect to travel times in a specific congestion
scenario. Remarkably, we find that already a small amount of ACC equipped cars
and, hence, a marginally increased free and dynamic capacity, leads to a
drastic reduction of traffic congestion.
