FairSCOSCA: Fairness At Arterial Signals - Just Around The Corner

2026-01-09

arXiv.org

AI Summary

This study addresses the prevalent efficiency-centric focus of existing traffic signal control systems—such as SCOOT and SCATS—which often neglect fairness, resulting in excessively long waiting times for certain road users. To bridge this gap, the authors integrate normative fairness principles, including egalitarianism and Rawlsian justice, into the operational framework of SCOOT/SCATS for the first time. Their approach dynamically optimizes green signal phases and proactively terminates underutilized phases to achieve more equitable allocation of intersection resources. Evaluation on a microsimulation-calibrated arterial network in Esslingen, Germany, demonstrates that the proposed method significantly improves multidimensional fairness metrics, effectively reducing both temporal inequality in waiting times and horizontal disparities between major arterials and minor side streets, all while preserving overall traffic efficiency.

Technology Category

• Game Theory and Economic Paradigms: Fair Division
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Philosophy and Ethics of AI: Bias, Fairness & Equity

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Traffic signal control at intersections, especially in arterial networks, is a key lever for mitigating the growing issue of traffic congestion in cities. Despite the widespread deployment of SCOOTS and SCATS, which prioritize efficiency, fairness has remained largely absent from their design logic, often resulting in unfair outcomes for certain road users, such as excessive waiting times. Fairness however, is a major driver of public acceptance for implementation of new controll systems. Therefore, this work proposes FairSCOSCA, a fairness-enhancing extension to these systems, featuring two novel yet practical design adaptations grounded in multiple normative fairness definitions: (1) green phase optimization incorporating cumulative waiting times, and (2) early termination of underutilized green phases. Those extensions ensure fairer distributions of green times. Evaluated in a calibrated microsimulation case study of the arterial network in Esslingen am Neckar (Germany), FairSCOSCA demonstrates substantial improvements across multiple fairness dimensions (Egalitarian, Rawlsian, Utilitarian, and Harsanyian) without sacrificing traffic efficiency. Compared against Fixed-Cycle, Max-Pressure, and standard SCOOTS/SCATS controllers, FairSCOSCA significantly reduces excessive waiting times, delay inequality and horizontal discrimination between arterial and feeder roads. This work contributes to the growing literature on equitable traffic control by bridging the gap between fairness theory and the practical enhancement of globally deployed signal systems. Open source implementation available on GitHub.

Problem

• traffic signal control
• fairness
• arterial networks
• waiting time inequality
• equitable traffic management

Innovation

• fairness-aware traffic control
• green phase optimization
• cumulative waiting time
• signal timing adaptation
• equitable urban mobility