This paper proposes a model predictive controller to perform the lane merging task. We consider a hierarchical control structure which consists of an inner control loop and an outer one. The inner loop is an adaptive cruise controller which gives the acceleration command to the autonomous vehicle to follow the designated speed and keep a relative distance with the preceding vehicle while satisfying constraints. The outer loop is to determine the vehicle in the main lane that the autonomous one should follow to minimize the entropy in the decision making of the human drivers in the main lane. It is verified in the simulation that the proposed controller can complete the lane merging task under uncertainties and modeling errors.