With the growing demand for door-to-door transportation services and the heightened sensitivity to logistics costs, intermodal transport operators urgently need to provide efficient and economical container transportation services. Given that the entire container transportation chain involves multiple transport resources and links, these operators face the challenge of how to reasonably allocate transport resources and achieve effective coordination among various links. This study addresses the integrated optimization of container transportation routes and drayage truck scheduling, considering both trunk-line transportation and first/last-mile drayage services. Based on the spatiotemporal network for container transportation, we develop a mixed-integer linear programming model with the objective of minimizing total operational costs. A logic-based Benders decomposition algorithm framework is adopted to design an exact algorithm capable of effectively solving real-world scale problems. The experimental scenario is selected from a partial transportation network of the new western land-sea corridor. The results show that compared to Gurobi, the proposed algorithm has better solution efficiency in various-sized instances. Compared with traditional independent decision-making methods, the collaborative optimization model can reduce total operating costs by 5% to 7.5%.