Outcome Assessment of Peer-to-Peer Adaptive Control Adjacent to a National Park

Abstract

In the town of Moab, Utah, a combination of seasonal tourist traffic, heavy truck traffic, and high pedestrian volumes creates a unique traffic management challenge; Moab’s remote location adds additional challenges for real-time traffic monitoring and maintaining of signal timing plans. The Main Street corridor is a strong candidate for an adaptive traffic control system (ATCS). Peer-to-peer (P2P) communication and user-definable control logic were used to develop and implement a cost-effective ATCS called “P2P adaptive control” that used only the existing local controllers and detection. The adaptive control logic adjusts green time along the mainline in response to detector inputs while keeping the side streets at the minimum time needed for pedestrian service. System performance was evaluated by comparing performance measures generated from high-resolution signal controller data before and after implementation of P2P adaptive control. The P2P adaptive control increased the through bandwidth of the corridor and reduced the number of split failures (i.e., the number of phase occurrences with insufficient green). Future work will include adjusting the algorithm to improve service on side streets and expanding P2P adaptive control to additional signals expected to be constructed in the area.