Dynamic lateral lane change (DLLC) control of automated and connected vehicles (ACVs) is challenging because of the time-varying and complex properties of the traffic environment. This study proposes a DLLC control strategy combining dynamic trajectory planning and tracking. According to the real-time longitudinal accelerations and velocities of multiple surrounding vehicles, as well as the real-time states of the ACVs, the safe trajectory reference of DLLC is obtained by solving a case-dependent constrained optimisation problem. The lane changing efficiency, vehicle stability and passenger comfort are considered jointly in the trajectory planning. Then, the dynamic trajectory reference is tracked through a gain-scheduling control algorithm combining previewed trajectory feed-forward and ACVs states feedback. Gain-scheduling control algorithm based on a linear time-varying form is utilised to achieve the precise control of the different velocities and improve the real-time ability of the algorithm. The proposed strategy is tested through software and hardware-in-loop experiments, and in different test scenarios. The results of simulations and experiments show that the proposed control strategy can achieve a satisfactory performance of DLLC. The lane changing efficiency, safety, passenger comfort and vehicle stability are verified in complex traffic environments.