  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.
