  In future intelligent transportation systems, networked vehicles coordinate
with each other to achieve safe operations based on an assumption that
communications among vehicles and infrastructure are reliable. Traditional
methods usually deal with the design of control systems and communication
networks in a separated manner. However, control and communication systems are
tightly coupled as the motions of vehicles will affect the overall
communication quality. Hence, we are motivated to study the co-design of both
control and communication systems. In particular, we propose a control
theoretical framework for distributed motion planning for multi-agent systems
which satisfies complex and high-level spatial and temporal specifications
while accounting for communication quality at the same time. Towards this end,
desired motion specifications and communication performances are formulated as
signal temporal logic (STL) and spatial-temporal logic (SpaTeL) formulas,
respectively. The specifications are encoded as constraints on system and
environment state variables of mixed integer linear programs (MILP), and upon
which control strategies satisfying both STL and SpaTeL specifications are
generated for each agent by employing a distributed model predictive control
(MPC) framework. Effectiveness of the proposed framework is validated by a
simulation of distributed communication-aware motion planning for multi-agent
systems.
