计算机科学 ›› 2018, Vol. 45 ›› Issue (12): 187-191.doi: 10.11896／j.issn.1002-137X.2018.12.030
刘文龙1, 张晶1, 周绥平2, 李月龙1
LIU Wen-long1, ZHANG Jing1, ZHOU Sui-ping2, LI Yue-long1
摘要： 针对地铁乘客人群的运动行为,基于Agent模型和粒子群搜索算法,利用仿真平台Repast Simphony建立了人群运动行为仿真模型,该模型模拟了乘客进入地铁候车大厅寻找车厢门进行排队和地铁到站时进入车厢的过程;基于此,提出了一种基于马尔可夫决策模型的改进寻路算法。实验表明,该算法有效地解决了传统粒子群算法容易陷入局部解的问题,明显减少了冲突次数。此外,文中提出增加地铁车厢人数指示器来避免部分车厢的拥挤状况,实验结果显示该方法行之有效,并能将乘客进入车厢的效率提高9%。
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