In this research study, a multistage fuzzy logic controller (MS-FLC) was developed for traffic control in incident management on expressways. The MS-FLC serves as the traffic operator's decision-making support tool at the operational level. The MS-FLC gathers real-time traffic and incident data to analyze and predict traffic conditions, as well as to recommend alternative control measures to the traffic operator in the form of linguistic expressions. The MS-FLC is embedded in a traffic simulator controller (TSC) prototype, and was evaluated by comparing its performance with no control scenario and ALINEA\Q, a popular local ramp control algorithm, across several incident scenarios in a simulation environment. In general, MS-FLC outperformed ALINEA\Q with respect to global objectives. In particular, whereas the ALINEA\Q algorithm favors the mainline, the MS-FLC algorithm significantly improves mainline travel conditions while substantially reducing ramp queues. It is concluded that, if properly designed, the MS-FLC can be a robust tool for traffic control on expressways under incident conditions.