This paper proposes an integrated system to control ramps and ad-just Variable Speed Limits. It includes three essential modules to predict the starting time of congestion and a fuzzy controller to determine the parameters and a model predictive control. An Apriori algorithm that is a powerful tool for frequent pattern mining is used in the , rst module. The proposed system is neither sensitive to the tra, c distribution nor computationally intensive. Two tra, c simulators of Aimsun and CTMSIM are applied to validate the results. Compared with the most recent algorithms, including Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM), this system improves prediction accuracy up to 2. 63%. The results of ramp metering and Variable Speed Limit subsystems are also promising. The embedded controller shows 0. 6% and 4% overall and rush hour improvement in the total travel time.