C-EQ-ALINEA: Distributed, Coordinated, and Equitable Ramp Metering Strategy for Sustainable Freeway Operations

TL;DR

C-EQ-ALINEA is a decentralized, fairness-aware extension of the ALINEA ramp metering controller that improves equity in delay distribution while maintaining efficiency, using minimal communication among ramps.

Contribution

It introduces a lightweight, decentralized coordination method for ramp metering that explicitly incorporates multiple fairness notions without complex optimization or centralized control.

Findings

Significantly improves fairness of delay distribution across ramps.

Maintains or surpasses efficiency of existing coordinated strategies like METALINE.

Operates effectively in a realistic microsimulation of Amsterdam's A10 ring road.

Abstract

Ramp metering is a widely deployed traffic management strategy for improving freeway efficiency, yet conventional approaches often lead to highly uneven delay distributions across on-ramps, undermining user acceptance and long-term sustainability. While existing fairness-aware ramp metering methods can mitigate such disparities, they typically rely on centralized optimization, detailed traffic models, or data-intensive learning frameworks, limiting their real-world applicability, particularly in networks operating legacy ALINEA-based systems. This paper proposes C-EQ-ALINEA, a decentralized, coordinated, and equity-aware extension of the classical ALINEA feedback controller. The approach introduces lightweight information exchange among neighbouring ramps, enabling local coordination that balances congestion impacts without centralized control, additional infrastructure, or complex optimization. C-EQ-ALINEA preserves the simplicity and robustness of ALINEA while explicitly addressing multiple notions of fairness, including Harsanyian, Egalitarian, Rawlsian, and Aristotelian perspectives. The method is evaluated in a calibrated 24-hour microsimulation of Amsterdam's A10 ring road using SUMO. Results demonstrate that C-EQ-ALINEA substantially improves the equity of delay distributions across ramps and users, while maintaining (in several configurations surpassing) the efficiency of established coordinated strategies such as METALINE. These findings indicate that meaningful fairness gains can be achieved through minimal algorithmic extensions to widely deployed controllers, offering a practical and scalable pathway toward sustainable and socially acceptable freeway operations. Open source implementation available on GitHub.