Considering the influence of queue length on performance improvement for a new compact robotic automated parking system

Abstract With the development of the BI (Business intelligence) applications, robots and robot-based technology appear in various fields. Compact robotic automated parking system will facilitate the informatization and modernization of urban development and environmental protection. Compact robotic automated parking (CRAP) system is a new system with higher storage utilization and rapid response to store and handle cars. This system has double storage rings, instead of one storage ring in old compact automated parking (CAP) system for storing cars in each tier, and each tier is equipped with inner rotating ring and tier-captive automated guided vehicle for horizontal transport. The CRAP system has one elevator with vertical automated guided vehicle in the outer ring instead of the center part in the old CAP system for vertical transport. We first estimate the system performance using queuing network models. Second, we validate the analytical models through simulation and a real case. The simulation results show that we make an accurate estimation. Third, we optimize system configurations by minimizing the car retrieval time. Finally, given the same storage capacity, we compare the car retrieval time based on a real application and footprint area of CRAP system with CAP system. The results show that the car retrieval time can be reduced by at least 29.7% when the system capacity C is 400, and the space utilization can be improved by at least 32.0%.

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