With the increasing demand for container transportation and the widespread application of new information technologies, the automation of container terminal operations has become the main development trend in domestic and international ports. It can not only effectively improve the efficiency and safety of terminal operations, but also significantly reduce the demand for human resources and the operational costs. The horizontal transportation system is an essential part of the container terminal handling system and an important link enabling the highly efficient container transportation between the quayside and the storage yard, so its operational reliability and the reasonableness of the scheduling directly affect the operational efficiency of the automated container handling system. The mostly used horizontal transportation equipment in container terminals is the automated guided vehicles (AGVs), which is responsible for horizontal transportation from the front quay crane to the rear yard in automated container terminals. In actual operation process, conflicts and congestion is inevitable when multiple AGVs operate simultaneously. On this basis, this paper used conflict-based search (CBS) to solve the conflict problem arising from the cooperative operation of multi-AGVs at the terminal. The upper layer algorithm searched for conflicts among AGVs, while the lower layer algorithm used the A* algorithm for path planning of AGVs. A load factor was introduced into the heuristic function of the A* algorithm in order to avoid congestion in the path planning and achieve load balancing on terminal roads. Further, a sliding time window conflict resolution (STWCR) based on CBS was adopted to improve computational efficiency for multiple AGVs path planning in the continuous operation scenario of multiple task points at the terminal. Simulation experiments verified that the proposed algorithm in this paper can effectively solve the conflict problem of multiple AGVs path planning at the terminal, while balancing the road network load, alleviating local road congestion, and improving the utilization of road resources. The research results of this paper provide a reference for the optimization of the horizontal transportation system in automated container terminals.