Automated guided vehicles (AGVs) are widely used in various material handling systems due to their high efficiency and low cost, particularly in warehouses. However, deadlock resolution among vehicles is still a thorny issue. Many algorithms re-plan motion paths to avoid deadlocks resulting in greatly increasing the computational complexity, while other deadlock resolution algorithms in which vehicles have fixed paths are less efficient. This paper proposes a spare zone based hierarchical (SZH) motion coordination algorithm supporting time-efficient collision-and-deadlock resolution among vehicles. Unlike previous deadlock resolution methods in which the vehicles can change their paths to avoid deadlocks at any time, SZH avoids deadlocks just by locally adjusting their paths in a decentralized manner. The introduction of a spare zone mechanism ensures reliable resolution of different types of collision and deadlocks while achieving high time efficiency. The allocation of spare zones for each vehicle before performing their missions guarantees that there exist enough free zones to which the vehicles taking part in deadlocks can temporary departs from their current path to avoid deadlocks. In order to improve the efficiency, the vehicle’s spare zones are updated as soon as the vehicle arrives at a zone. The algorithm is realized based on a hierarchical strategy, where the top layer considers the allocation and update of spare zones, while the bottom layer considers the coordination among vehicles within two zones. Extensive simulation results demonstrate the feasibility and efficiency of the proposed motion coordination algorithm.

自动导引车（AGV）由于其高效率和低成本而被广泛应用于各种物料搬运系统，尤其是在仓库中。但是，车辆之间的死锁解决仍然是一个棘手的问题。许多算法会重新规划运动路径以避免死锁，从而导致计算复杂性大大增加，而其他具有固定路径的车辆的死锁解析算法效率较低。提出了一种基于备用区的分层运动协调算法，该算法支持车辆之间高效的碰撞和死锁解决方案。与以前的死锁解决方法不同，在以前的死锁解决方法中，车辆可以随时更改其路径以避免死锁，而SZH只是通过分散地局部调整其路径来避免死锁。备用区机制的引入确保了可靠地解决各种类型的碰撞和死锁，同时实现了高时间效率。在执行任务之前，为每辆车分配备用区可确保存在足够的自由区，参与死锁的车辆可以暂时离开其当前路径以避免死锁。为了提高效率，一旦车辆到达某个区域，便会更新其备用区域。该算法基于分层策略来实现，其中顶层考虑备用区域的分配和更新，而底层考虑两个区域内车辆之间的协调。大量的仿真结果证明了该运动协调算法的可行性和有效性。