面向自动化集装箱码头的AGV行驶时间估计

Automated Container Terminal Oriented Travel Time Estimation of AGV

自动导引车(Automated Guided Vehicle, AGV)在自动化集装箱码头的水平运输中发挥了重要作用,对AGV行驶时间进行准确估计,有利于减少码头各作业环节的资源闲置,提高整体效率。针对AGV在自动化集装箱码头的行驶时间估计问题,提出了一种AGV行驶时间估计方法。首先,根据AGV的行驶模式将目标行驶路径切分为若干段,使用神经网络模型对其进行编码;其次,对该路径出发前后一段时间内的其他路径进行编码并将其作为环境信息,以通过模型预测其是否与目标路径发生冲突作为辅助任务;最后,综合两类信息对行驶时间进行估计。该方法引入了路径间冲突对时间估计造成的影响。基于自动化集装箱码头的历史数据的实验表明,相比AGV场景中常用的静态时间估计方法,所提方法能够将时间估计的误差降低18%以上,可以更准确地估计AGV的行驶时间。

Automated guided vehicles(AGV)are crucial for the horizontal transportation of automated container terminals.Accurate estimation of the travel time of each AGV will reduce the number of idle AGV resources and increase the efficiency of the entire terminal.This paper proposes a method for travel time estimation of AGV in automated container terminals.Firstly, the target route of AGV is divided and encoded into several segments.Secondly, other routes are encoded as environment information, which depart before or after the target route.And the conflict between these routes and target route is estimated as an auxiliary task.Finally, the travel time with all encodings is calculated.The proposed method introduces the influence of path conflicts on time estimation.Experiments based on historical data of automated terminals show that, compared with static time estimation methods commonly used in AGV scenarios, the proposed method can reduce the time estimation error by more than 18%,and can estimate the travel time more accurately.