基于AnyLogic的人流增多地铁站系统再优化
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U237.96

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Simulation and Optimization of Metro Station System Based on Anylogic
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    摘要:

    随着城市地铁及城市规划的持续扩建,伴随出现了一些建设较早的地铁站人流增多而引起的大客流现象。针对这一现象,从地铁站内、外两方面系统地分析了客流增多的原因,应用工业工程方法提出了优化思维导图和地铁再优化原则。以西安地铁二号线运动公园站为例,运用Anylogic行人库仿真技术进行了全尺寸、全数据仿真建模研究,在对进站人流特性进行分析的基础上,以密度图拥堵点、进出站用时和服务用时及它的队长等为指标,体现了优化前后的效果。结果表明,两侧入口人流得到明显均衡、瓶颈处人流密度降低,A、D侧行人安检耗时缩短4.48min,进站时间缩短4.08min,整体人流出站时间缩短了0.62min。地铁再优化思路以及案例具体的优化意见能够为现今地铁站的再优化提供一定的解决思路。

    Abstract:

    With the continuous expansion of urban subways and urban planning, there have been some phenomena of the increase in the number of people in earlier subway stations. Aiming at this phenomenon, the reasons for the increase of people flow are systematically analyzed from the inside and outside of the subway station. The principles of optimized mind map and subway re-optimization are put forward by applying industrial engineering methods. Taking the Sports Park Station of Xi'an Metro Line 2 as an example, the full-scale and full-data simulation modeling research was carried out using Anylogic pedestrian library simulation technology. Based on the analysis of the inflow characteristics of the inbound station, the density map was used to block the points and enter and exit the station. Time and service time and its captain are indicators, reflecting the effect before and after optimization. The results show that the flow of inlets on both sides is obviously balanced, and the flow density at the bottleneck is reduced. The pedestrian inspection time on A and D sides is shortened by 4.48min, the stop time is shortened by 4.08min, and the overall outflow time is shortened by 0.62min. Subway re-optimization ideas and case-specific optimization opinions can provide certain solutions for the re-optimization of today's subway stations.

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李建华,陈伟,陈祥儒. 基于AnyLogic的人流增多地铁站系统再优化[J]. 科学技术与工程, 2020, 20(33): 13847-13851.
Li Jianhua, Chen wei, Chen xiangru. Simulation and Optimization of Metro Station System Based on Anylogic[J]. Science Technology and Engineering,2020,20(33):13847-13851.

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  • 收稿日期:2019-11-26
  • 最后修改日期:2020-09-10
  • 录用日期:2020-05-31
  • 在线发布日期: 2020-12-18
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