移动机器人智能车场停车资源调度分配

商业、民航业、汽车制造业停车场的“效率低、管理难”问题日渐严峻，通过引入AGV构建自动化智能停车场迫在眉睫。与柔性制造系统、自动化码头等领域不同，AGV智能停车场可以自由选择终点，而传统的停车资源分配方法：随机分配或就近分配对AGV运行情况的预测不足，造成等待时间与停车资源的大量浪费。本文提出了一种停车资源分配方案的代价评价模型，通过计算分配方案的路径干涉概率对分配方案进行评价，并在传统分配方法的基础上提出了两种新的停车资源分配方法。通过Plant Simulation对模型进行仿真验证，仿真结果显示：在44个停车位，4辆AGV投入运输的情况下，降低路径干涉概率，将仿真总时长降低了30.4%，提高了停车场的运输效率。

AGV intelligent parking lot allocation model under peak demand

The problem of "low efficiency and difficult management" of parking lots in commercial, civil aviation and automobile manufacturing industries is becoming increasingly serious. It is extremely urgent to construct automated intelligent parking lots by introducing AGV. Different from flexible manufacturing systems and automated terminals, AGV intelligent parking lots can choose their destination freely. However, traditional allocation methods of parking resources: random allocation or nearby allocation can not predict the operation of AGV, resulting in a lot of waste of waiting time and parking resources. In this paper, a cost evaluation model of parking resource allocation scheme is proposed, and the allocation scheme is evaluated by calculating the path interference probability of allocation scheme, and two new allocation methods of parking resource are proposed based on the traditional allocation method. Plant Simulation was used to verify the model. The Simulation results showed that in the case of 44 parking Spaces and 4 AGVs being transported, the total Simulation time was reduced by 30.4% by reducing the probability of path interference, and the transportation efficiency of parking lots was improved.