  The design or the optimization of transport systems is a difficult task. This
is especially true in the case of the introduction of new transport modes in an
existing system. The main reason is, that even small additions and changes
result in the emergence of new travel patterns, likely resulting in an
adaptation of the travel behavior of multiple other agents in the system. Here
we consider the optimization of future Urban Air Mobility services under
consideration of effects induced by the new mode to an existing system. We
tackle this problem through a bi-level network design approach, in which the
discrete decisions of the network design planner are optimized based on the
evaluated dynamic demand of the user's mode choices. We solve the
activity-based network design problem (AB-NDP) using a Genetic Algorithm on a
multi-objective optimization problem while evaluating the dynamic demand with
the large-scale Multi-Agent Transport Simulation (MATSim) framework. The
proposed bi-level approach is compared against the results of a coverage
approach using a static demand method. The bi-level study shows better results
for expected UAM demand and total travel time savings across the transportation
system. Due to its generic character, the demonstrated utilization of a
bi-level method is applicable to other mobility service design questions and to
other regions.
