Efficient trajectory planning plays a crucial rolein the development of autonomous vehicles, ensuring safe andoptimized navigation in dynamic environments. This paperproposes a novel energy-efficient hybrid trajectory planningby integrating a sampling-based method with an optimizationbased path refining method. It uses the strength of the samplingbased methods to reduce the solution space and generatea reactive trajectory in a dynamic environment. Followingpath selection, a septic path is generated and utilized asa reference for an energy-efficient path-refining optimizationproblem, producing a jerk-controlled trajectory with enhancedcomputational efficiency. The simulations were conducted ina joint-simulation environment using Simulink/Matlab andthe Scaner Studio vehicle dynamics and driving environmentsimulator. The findings demonstrate the effectiveness of ourapproach in achieving significant energy savings while adeptlyaddressing dynamically changing environments.