We present an innovative cooperative driving strategy known as Dynamic Resequencing and Platooning (DRP) designed to ensure the safe and efficient traversal of Connected and Automated Vehicles (CAVs) through signal-free intersections. By employing a Resequencing and Platooning Algorithm (RPA) grounded in state transition networks and CAV platooning, the optimal crossing sequence for CAVs is ascertained within a finite time. Through the utilization of a decentralized energy-optimal control framework, optimal trajectories are devised for CAVs, thereby facilitating optimal coordination among them. Simulation results underscore the substantial performance benefits of the DRP strategy compared to traffic light, First-In-First-Out (FIFO), and Local Dynamic Resequencing (LDR) strategies, with notable reductions observed in both travel delay and fuel consumption.