This paper presents an online smooth-path lane-change control framework. We focus on dense traffic where inter-vehicle space gaps are narrow, and cooperation with surroundingdrivers is essential to achieve the lane-change maneuver. Wepropose a two-stage control framework that harmonizes ModelPredictive Control (MPC) with Generative Adversarial Networks(GAN) by utilizing driving intentions to generate smooth lane-change maneuvers. To improve performance in practice, thesystem is augmented with an adaptive safety boundary and aKalman Filter to mitigate sensor noise. Simulation studies are in-vestigated in different levels of traffic density and cooperativenessof other drivers. The simulation results support the effectiveness,driving comfort, and safety of the proposed method.