C-MP: A decentralized adaptive-coordinated traffic signal control using the Max Pressure framework

TL;DR

This paper introduces C-MP, a decentralized Max Pressure-based traffic signal control framework that effectively coordinates signals along arterial roads, improving stability, travel time, and fuel efficiency without relying on fixed offsets.

Contribution

The paper proposes a novel decentralized Max Pressure control algorithm, C-MP, that explicitly detects vehicle platoons to coordinate traffic signals without fixed offsets, maintaining stability and improving traffic flow.

Findings

C-MP maintains maximum stability property.

C-MP achieves larger stable regions than benchmark policies.

C-MP reduces travel time and fuel consumption effectively.

Abstract

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.