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This paper presents the design of dual heuristic programming (DHP) for the optimal coordination of ramp metering in freeway systems. Specifically, we implement the DHP method to solve both recurrent and nonrecurrent congestions with queuing consideration. A coordinated neural network controller is achieved by the DHP method with traffic models. Then, it is used for verifications with different traffic scenarios. Simulation studies performed on a hypothetical freeway indicate that the achieved neural controller maintains good control performance when compared with the classical ramp metering algorithm ALINEA. We emphasize that these neural controllers can be developed offline by using approximate traffic models. This offline mechanism avoids the risks of instability that incur during continual online training. We also discuss some real-time implementation issues.