  Small Unmanned Aircraft Systems (sUAS) will be an important component of the
smart city and intelligent transportation environments of the near future. The
demand for sUAS related applications, such as commercial delivery and land
surveying, is expected to grow rapidly in next few years. In general, sUAS
traffic routing and management functions are needed to coordinate the launching
of sUAS from different launch sites and determine their trajectories to avoid
conflict while considering several other constraints such as expected arrival
time, minimum flight energy, and availability of communication resources.
However, as the airborne sUAS density grows in a certain area, it is difficult
to foresee the potential airspace and communications resource conflicts and
make immediate decisions to avoid them. To address this challenge, we present a
temporal and spatial routing algorithm and simulation platform for sUAS
trajectory management in a high density urban area that plans sUAS movements in
a spatial and temporal maze taking into account obstacles that are either
static or dynamic in time. The routing allows the sUAS to avoid static no-fly
areas (i.e. static obstacles) or other in-flight sUAS and areas that have
congested communication resources (i.e. dynamic obstacles). The algorithm is
evaluated using an agent-based simulation platform. The simulation results show
that the proposed algorithm outperforms other route management algorithms in
many areas, especially in processing speed and memory efficiency. Detailed
comparisons are provided for the sUAS flight time, the overall throughput,
conflict rate and communication resource utilization. The results demonstrate
that our proposed algorithm can be used to address the airspace and
communication resource utilization needs for a next generation smart city and
smart transportation.
