Parking in large metropolitan areas is often a time-consuming task with further implications toward traffic patterns that affect urban landscaping. Reducing the premium space needed for parking has led to the development of automated mechanical parking systems. Compared to regular garages having one or two rows of vehicles in each island, automated garages can have multiple rows of vehicles stacked together to support higher parking demands. Although this multi-row layout reduces parking space, it makes the parking and retrieval more complicated. In this work, we propose an automated garage design that supports near 100% parking density. Modeling the problem of parking and retrieving multiple vehicles as a special class of multi-robot path planning problem, we propose associated algorithms for handling all common operations of the automated garage, including (1) optimal algorithm and near-optimal methods that find feasible and efficient solutions for simultaneous parking/retrieval and (2) a novel shuffling mechanism to rearrange vehicles to facilitate scheduled retrieval at rush hours. We conduct thorough simulation studies showing the proposed methods are promising for large and high-density real-world parking applications.
翻译:在大都市地区停车往往是一项耗时的工作,对影响城市景观景观的交通模式有进一步影响。减少停车所需额外空间已导致自动机械停车系统的发展。与每个岛屿一两排车辆的正常车库相比,自动化车库可以堆叠多行车辆,以满足更高的停车需求。虽然这种多行布局减少了停车空间,但使停车和取用更为复杂。在这项工作中,我们提议一个自动车库设计,可支持近100%的停车密度。模拟停车和回收多部车辆的问题,作为多式道路规划的特殊类别,我们建议采用相关算法处理自动车库的所有共同操作,包括:(1) 最佳算法和近最佳方法,为同时停车/回收找到可行和高效的解决方案,(2) 新型的车辆后置机制,以便利在高峰时间进行预定的回收。我们进行彻底的模拟研究,表明拟议方法对大型和高密度实际停车应用程序很有希望。