  Coordinated traffic signals seek to provide uninterrupted flow through a
series of closely spaced intersections, typically using pre-defined fixed
signal timings and offsets. Adaptive traffic signals dynamically change signal
timings based on observed traffic conditions in a way that might disrupt
coordinated movements, particularly when these decisions are made independently
at each intersection. To alleviate this issue, this paper introduces a novel
Max Pressure-based traffic signal framework that can provide coordination even
under decentralized decision-making. The proposed Coordinated Max Pressure
(C-MP) algorithm uses the space mean speeds of vehicles to explicitly detect
freely flowing platoons of vehicles and prioritizes their movement along a
corridor. Specifically, upstream platoons are detected and their weight in the
MP framework increased to provide priority, while downstream platoons are
detected and their weight reduced to ensure smooth traffic flow across
corridors. The study analytically proves that C-MP maintains the desirable
maximum stability property, while micro-simulation analyses conducted on an
arterial network demonstrate its ability to achieve a larger stable region
compared to benchmark MP control policies. Simulation results also reveal that
the proposed control algorithm can effectively coordinate traffic signals in
both directions along an arterial without explicitly assigned offsets or
constraints. The results also reveal C-MP's superiority to benchmark
coordination strategies in reducing travel time, and fuel consumption both at
the corridor level and the network level by balancing the negative impact
imparted to vehicles in the minor direction.
