As the scale of container shipping continuously increases driven by mega vessels and rising transportation demands, Automated Container Terminals (ACTs) have emerged as a promising solution to enhance operational efficiency, leveraging technologies such as automated guided vehicles (AGVs) for container transporting tasks. The AGV traffic within the transportation area, serving as a critical link between quayside and yard side operations, faces challenges due to complex conflicting relations among AGV movements. This study proposes a novel framework for routing and flowpath design (RFD) problem of AGVs in ACTs.Through investigating conflicting mechanisms of AGV movements, the study first proposes conflict-free principles for elementary grid networks, aiming to achieve conflict-free operations and enhance traffic efficiency. Theoretical analysis validates the maximum space–time resource utilization of the RFD under certain conditions. Furthermore, customized design methods are developed to adapt to real-world ACT scenarios, and an integrated optimization model is established to optimize RFD schemes. Numerical experiments are conducted to evaluate the proposed methods, highlighting their effectiveness in enhancing operational efficiency and mitigating traffic congestion in ACTs. This study provides a streamlined yet effective approach to AGV traffic organization within container terminals. By proactively resolving AGV travel conflicts, it addresses the computational challenges in real-time implementation and serves as a cornerstone for effective online operation of AGVs.

中文翻译：

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集装箱码头自动导引车的无冲突路线和流路设计

随着大型船舶和运输需求不断增长的推动集装箱运输规模的不断扩大，自动化集装箱码头 （ACT） 已成为一种很有前途的解决方案，可以利用自动导引车 （AGV） 等技术完成集装箱运输任务，从而提高运营效率。运输区域内的 AGV 交通是码头和堆场运营之间的关键纽带，由于 AGV 运动之间复杂的冲突关系而面临挑战。本研究提出了一种新的 ACT 中 AGV 的路线和流路设计 （RFD） 问题框架，通过调查 AGV 运动的冲突机制，该研究首先提出了基本网格网络的无冲突原则，旨在实现无冲突运行并提高交通效率。理论分析验证了 RFD 在特定条件下的最大时空资源利用率。此外，开发了定制的设计方法以适应现实世界的 ACT 场景，并建立了一个集成的优化模型来优化 RFD 方案。进行了数值实验以评估所提出的方法，突出了它们在提高 ACT 运营效率和缓解交通拥堵方面的有效性。本研究为集装箱码头内的 AGV 交通组织提供了一种简化而有效的方法。通过主动解决 AGV 出行冲突，它解决了实时实施中的计算挑战，并成为 AGV 有效在线作的基石。