With the development of information technology, intermodal transport research pays more attention to dynamic optimization and multi-role cooperation. The core issue of this paper was to realize container routing with dynamic adjustment, real-time optimization, and multi-role cooperation characteristics in the intermodal transport network. This paper first introduces the Intermodal Transport Cooperation Protocol (ITCP) that describes the operation and analysis of intermodal transport systems with the concept of encapsulation and layering. Then, a new network flow control method was built based on Model Predictive Control (MPC) in the ITCP framework. The method takes real-time information from all ITCP layers as input and generates flow control decisions for containers. To evaluate the method’s effectiveness, a discrete event simulation experiment is applied. The results show that the proposed method outperforms the all-or-nothing method in scenarios with high freight volume, which means the method proposed in this paper can effectively balance the network transport load and reduce network operating costs. The research of this paper may throw some new light on intermodal transport research from the perspectives of digitization, multi-role cooperation, dynamic optimization, and system standardization.

中文翻译：

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基于模型预测控制的协同联运网络流量控制方法

随着信息技术的发展，多式联运研究更加注重动态优化和多角色合作。本文的核心问题是在多式联运网络中实现具有动态调整、实时优化和多角色协同特性的集装箱路线。本文首先介绍了多式联运合作协议（ITCP），它以封装和分层的概念描述了多式联运系统的运行和分析。然后，在ITCP框架下，基于模型预测控制（MPC）构建了一种新的网络流量控制方法。该方法将来自所有 ITCP 层的实时信息作为输入，并为容器生成流量控制决策。为了评估该方法的有效性，应用离散事件模拟实验。结果表明，该方法在高货运量场景下优于all-or-nothing方法，这意味着本文提出的方法可以有效平衡网络运输负载，降低网络运营成本。本文的研究可能会从数字化、多角色合作、动态优化和系统标准化的角度为多式联运研究提供一些新的视角。