Vulnerability of Fixed-Time Control of Signalized Intersections to Cyber-Tampering

TL;DR

This paper investigates how cyber-attacks on traffic sensors can destabilize fixed-time traffic signal control, proposing optimization methods to analyze worst-case and targeted sensor perturbations with real-world case studies.

Contribution

It formulates and solves bilevel optimization problems to assess the vulnerability of fixed-time traffic control to sensor tampering, introducing new attack models and solution techniques.

Findings

Cyber-attacks can significantly increase network and lane congestion.

Optimization models identify worst-case sensor perturbations.

Real network case study demonstrates attack impact and mitigation insights.

Abstract

Recent experimental studies have shown that traffic management systems are vulnerable to cyber-attacks on sensor data. This paper studies the vulnerability of fixed-time control of signalized intersections when sensors measuring traffic flow information are compromised and perturbed by an adversary. The problems are formulated by considering three malicious objectives: 1) worst-case network accumulation, which aims to destabilize the overall network as much as possible; 2) worst-case lane accumulation, which aims to cause worst-case accumulation on some target lanes; and 3) risk-averse target accumulation, which aims to reach a target accumulation by making the minimum perturbation to sensor data. The problems are solved using bilevel programming optimization methods. Finally, a case study of a real network is used to illustrate the results.