Using Traffic Management Approaches to Assess Digital Infrastructure Disruptions: Insights from a Signal Tampering Case Study

This paper introduces a methodological framework for assessing the impacts of digital infrastructure disruptions in urban traffic networks, using traffic signal tampering as a case study. A readily quantifiable indicator, the Average Flow Reduction Metric (AFRM), is proposed to capture network-wide flow reduction based on the principles of the Macroscopic Fundamental Diagram (MFD). The framework is applied to a simulated network under various tampering scenarios and routing behaviors, including fixed, flexible, semi, and fully adaptive routing. The results show that AFRM correlates meaningfully with conventional disutility-based network performance metrics and serves as a reliable proxy for network degradation, especially under established or rationally adaptive routing behaviors. Due to its reliance on commonly available traffic measurements, AFRM provides a practical tool for diagnosing and managing digital disruptions in traffic networks. As such, it may support traffic managers in assessing, preparing for, monitoring, and responding to disruptions in real time.