Comparative Analysis of the Factors Influencing Metro Passenger Arrival Volumes in Wuhan, China, and Lagos, Nigeria: An Application of Association Rule Mining and Neural Network Models

This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.

Regenerative Braking Energy Recovery System of Metro Train Based on Dual-Mode Power Management

In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage,a hybrid regenerative braking energy recovery system with a dual-mode power management strategy is proposed.Firstly,the construction of the hybrid regenerative braking energy recovery system is explained.Then,based on the power demand of low-voltage load in metro stations,a dual-mode power management strategy is proposed to allocate the reference power of each system according to the different working conditions,and the control methods of each system are set.Finally,the correctness and effectiveness of the dual-mode strategy are verified through simulation,and the proposed braking energy utilization scheme is compared with other singleform utilization schemes.The results illustrate that the hybrid system with the dual-mode strategy can effectively recycle the regenerative braking energy of metro train and inhibit the busbar voltage fluctuation;the proposed braking energy utilization scheme has certain advantages on energy recovery and DC bus voltage stabilization compared with other single-form schemes;the proposed power management strategy can correctly allocate the reference power of each system with a lower construction cost.

Fatigue research of metro car body based on operational loads

Purpose–The principle of infinite life design currently directs fatigue resistance strategies for metro car bodies.However,this principle might not fully account for the dynamic influence of operational loads and the inevitable presence of defects.This study aims to integrate methods of service life estimation and residual life assessment,which are based on operational loads,into the existing infinite life verification framework to further ensure the operational safety of subway trains.Design/methodology/approach–Operational loads and fatigue loading spectra were determined through the field test.The material test was conducted to investigate characteristics of the fracture toughness and the crack growth rate.The fatigue strength of the metro car body was first verified using the finite element method and Moore–Kommers–Japer diagrams.The service life was then estimated by applying the Miner rule and high-cycle fatigue curves in a modified form of the Basquin equation.Finally,the residual life was assessed utilizing a fracture assessment diagram and a fitted curve of crack growth rate adhered to the Paris formula.Findings–Neither the maximum utilization factor nor the cumulative damage exceeds the threshold value of 1.0,the metro car body could meet the design life requirement of 30 years or 6.6 million km.However,three out of five fatigue key points were significantly influenced by the operational loads,which indicates that a single fatigue strength verification cannot achieve the infinite life design objective of the metro car body.For a projected design life of 30 years,the tolerance depth is 12.2 mm,which can underscore a relatively robust damage tolerance capability.Originality/value–The influence of operational loads on fatigue life was presented by the discrepancy analysis between fatigue strength verification results and service life estimation results.The fracture properties of butt-welded joints were tested and used for the damage tolerance assessment.The damage tolerance life can be effectively related by a newly developed equation in this study.It can be a valuable tool to provide the theoretical guidance and technical support for the structural improvements and maintenance decisions of the metro car body.

Comparative Analysis of Metro Passengers’Mobility Patterns and Jobs-housing Balance of Metropolitan

The advent of the big data era has provided many types of transportation datasets,such as metro smart card data,for studying residents’mobility and understanding how their mobility has been shaped and is shaping the urban space.In this paper,we use metro smart card data from two Chinese metropolises,Shanghai and Shenzhen.Five metro mobility indicators are introduced,and association rules are established to explore the mobility patterns.The proportion of people entering and exiting the station is used to measure the jobs-housing balance.It is found that the average travel distance and duration of Shanghai passengers are higher than those of Shenzhen,and the proportion of metro commuters in Shanghai is higher than that of Shenzhen.The jobs-housing spatial relationship in Shenzhen based on metro travel is more balanced than that in Shanghai.The fundamental reason for the differences between the two cities is the difference in urban morphology.Compared with the monocentric structure of Shanghai,the polycentric structure of Shenzhen results in more scattered travel hotspots and more diverse travel routes,which helps Shenzhen to have a better jobs-housing balance.This paper fills a gap in comparative research among Chinese cities based on transportation big data analysis.The results provide support for planning metro routes,adjusting urban structure and land use to form a more reasonable metro network,and balancing the jobs-housing spatial relationship.

Mechanical responses of underground carriageway structures due to construction of metro tunnels beneath the existing structure:A case study

To understand the mechanical response pattern of the existing structure and ground due to the construction of metro tunnels underneath,the finite difference method is adopted to study the torsional deformation and stress variation of the existing structure and the effect of underground carriageway structures on the surface subsidence.The curves of the maximum differential subsidence,torsion angle,and distortion of the cross-section of the existing structure show two peaks in succession during traversing of two metro tunnels beneath it.The torsion angle of the existing structure changes when the two tunnels traverse beneath it in opposite directions.The first traversing of the shield tunnel mainly induces the magnitude variation in torsional deformation of the existing structure,but the second traversing of the subsurface tunnel may cause a dynamic change in the magnitude and form of torsional deformation in the existing structure.The shielding effect can reduce the surface subsidence caused by metro tunnel excavation to a certain extent,and the development trend of subsidence becomes slower as the excavation continues.

Research on passenger flow control at metro transfer stations based on real-time flow calculation of streamlines

Purpose – The volume of passenger traffic at metro transfer stations serves as a pivotal metric for theorchestration of crowd flow management. Given the intricacies of crowd dynamics within these stations andthe recurrent instances of substantial passenger influxes, a methodology predicated on stochastic processesand the principle of user equilibrium is introduced to facilitate real-time traffic flow estimation within transferstation streamlines.Design/methodology/approach – The synthesis of stochastic process theory with streamline analysisengenders a probabilistic model of intra-station pedestrian traffic dynamics. Leveraging real-time passengerflow data procured from monitoring systems within the transfer station, a gradient descent optimizationtechnique is employed to minimize the cost function, thereby deducing the dynamic distribution of categorizedpassenger flows. Subsequently, adhering to the tenets of user equilibrium, the Frank–Wolfe algorithm isimplemented to allocate the intra-station categorized passenger flows across various streamlines, ascertainingthe traffic volume for each.Findings – Utilizing the Xiaozhai Station of the Xi’an Metro as a case study, the Anylogic simulation softwareis engaged to emulate the intra-station crowd dynamics, thereby substantiating the efficacy of the proposedpassenger flow estimation model. The derived solutions are instrumental in formulating a crowd controlstrategy for Xiaozhai Station during the peak interval from 17:30 to 18:00 on a designated day, yielding crowdmanagement interventions that offer insights for the orchestration of passenger flow and operationalgovernance within metro stations.Originality/value – The construction of an estimation methodology for the real-time streamline traffic flowaugments the model’s dataset, supplanting estimated values derived from surveys or historical datasets withreal-time computed traffic data, thereby enhancing the precision and immediacy of crowd flow managementwithin metro stations.

地铁大语言模型垂直问答系统MetroGPT

为解决城市轨道交通大系统中各个运行层级间不协调与信息资源浪费的问题,以地铁系统为原型,分析地铁大系统的运作机制,设计易于实现的地铁大模型问答系统(MetroGPT)。MetroGPT是基于大语言模型(LLM)构建的地铁大语言模型垂直问答系统,以LangChain为设计框架,针对特定场景定制不同的AI智能体完成特定任务。基于现有的6种大语言模型制作垂域智能体,使用改进的德尔菲法设计评估流程,通过德尔菲法的评分结果选出与地铁某类垂域知识最为匹配的大语言模型引擎。研究结果表明:MetroGPT提供1种解决地铁运行系统中层级信息闭塞、交流不充分的方法,为运营方、乘客、服务人员提供1个三方交流平台,在不同条件下针对需求制定合乎规范与实际的解决方案。通过分析现有技术和挑战,提出1种结合知识图谱和大语言模型的问答系统设计方案,并讨论其在地铁运营中的具体应用场景和潜在价值。

Winding Function Theory Based Thrust Calculation on Nested-loop Secondary Linear Machine Adapted to Linear Metro

With advantages of strong drive capability,nested-loop secondary linear machine(NLS-LM)has great potentiality in linear metro.For its secondary structure with multiple loops,it is difficult to calculate the electromagnetic thrust of NLS-LM reasonably.Hence,in this paper,one thrust calculation method is proposed considering variable loop inductance and transient loop current.Firstly,to establish the secondary winding function,the modeling domain is confined to a limited range,and the equivalent loop span is employed by analyzing the coupling relationship between primary and secondary.Then,in order to obtain the secondary flux density,the transient secondary current is solved based on the loop impedance and induced voltage.Finally,the electromagnetic thrust can be calculated reasonably by the given primary current sheet and the calculated secondary flux density.Comprehensive simulations and experiments have demonstrated the effectiveness of the proposed method.

A Convolutional Autoencoder Based Fault Detection Method for Metro Railway Turnout

Railway turnout is one of the critical equipment of Switch&Crossing(S&C)Systems in railway,related to the train’s safety and operation efficiency.With the advancement of intelligent sensors,data-driven fault detection technology for railway turnout has become an important research topic.However,little research in the literature has investigated the capability of data-driven fault detection technology for metro railway turnout.This paper presents a convolutional autoencoder-based fault detection method for the metro railway turnout considering human field inspection scenarios.First,the one-dimensional original time-series signal is converted into a twodimensional image by data pre-processing and 2D representation.Next,a binary classification model based on the convolutional autoencoder is developed to implement fault detection.The profile and structure information can be captured by processing data as images.The performance of our method is evaluated and tested on real-world operational current data in themetro stations.Experimental results show that the proposedmethod achieves better performance,especially in terms of error rate and specificity,and is robust in practical engineering applications.

Research on the cooperative train control method in the metro system for energy saving

Purpose–To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure,energy-saving performance of the whole metro system cannot be guaranteed.Design/methodology/approach–A cooperative train control framework is formulated to regulate a novel train operation mode.The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train.An improved brute force(BF)algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.Findings–Case studies on the actual metro line in Guangzhou,China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters.The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.Originality/value–Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process,which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation.This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea,where energy-efficient train operation can be realised once train running time is determined,thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Translation of Metro Station Names in Guangzhou and Foshan from the Perspective of Symbolic Function of Translation Landscape

Guangzhou and Foshan enjoy relatively mature metro network.However,some names of metro stations are over-transliterated in Pinyin.Such a translation method is used in translating general names,nouns of locality and some names of tourist destinations.With translation landscape and linguistic landscape theories,the reasons and impacts of over-transliteration in Guangzhou and Foshan metro will be discussed from the perspective of symbolic function.English names of Metro stations in other cities serve as a reference so as to appropriate solutions.

欧盟质量型选择性分销协议适用Metro标准合理规则的困境——以限制网络销售为例

纵向限制是近年来欧洲竞争法中争议较大的领域,本文探究纵向限制中质量型选择性分销协议的合法性认定标准。在欧盟的纵向限制规制框架下,首先考虑质量型选择性分销协议是否属于《欧盟运行条约》第101条第1款的范围,因此需判断协议的目的或效果是否影响竞争。若协议为该款所规制的对象,那么就要以Metro标准评估选择性分销造成的品牌内竞争减弱是否能被品牌间质量竞争产生的积极效果所抵消。可是Metro标准固然为质量型选择性分销协议提供了合法性认定标准,但是在实际判定过程中存在模糊性,尤其是对合理规则进行具体解释的时候,许多现实问题有待解决。

Last train timetable optimization for metro network to maximize the passenger accessibility over the end-of-service period

Purpose-This study aims to improve the passenger accessibility of passenger demands in the end-ofoperation period.Design/methodology/approach-A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway,the minimum headway and the latest end-of-operation time.The objective of the model is to maximize the number of reachable passengers in the end-of-operation period.A solution method based on a preset train service is proposed,which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.Findings-The results of the case study of Wuhan Metro show that the solution method can obtain highquality solutions in a shorter time;and the shorter the time interval of passenger flow data,the more obvious the advantage of solution speed;after optimization,the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.Originality/value-Existing research results only consider the passengers who take the last train.Compared with previous research,considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination.Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network,but due to the decrease in passenger demand,postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

盾构始发与接收对工作井围护结构的影响研究

[目的]一般情况下,盾构机均在盾构工作井主体结构施工完成后才进行始发或接收,由于诸多因素的限制,往往需要考虑盾构工作井主体结构尚未施工时进行盾构始发或接收的情况,因此需研究盾构始发与接收对盾构工作井围护结构的影响。[方法]以成都地铁某标准地下三层岛式车站为例,研究盾构工作井在未施作主体内衬结构状态下实现盾构始发与接收时的围护结构受力及变形情况,并分析了盾构始发与接收对围护结构稳定性的影响。[结果及结论]研究结果表明:无内衬状态工作井盾构始发与接收时,围护结构桩体水平位移最大值及弯矩最大值均发生在盾构工作井端墙中跨第4道钢支撑处,围护结构剪力最大值发生在盾构工作井端墙中跨底板处;当盾构工作井未施作主体内衬结构时,围护结构桩体变形及受力均有所增大,但其位移及力学指标均满足规范要求;围护结构在剪力及弯矩作用下能够满足承载能力及强度要求;无内衬状态下的工作井盾构始发与接收可提高施工效率,有效节省工期,节约工程成本。

地铁列车刨削式防爬吸能结构冲击力平稳行为参数优化

为提升地铁列车在碰撞过程的平稳性和耐撞性,提出一种刨削式吸能防爬器。该吸能结构因其抗偏载能力强,结构紧凑等优点被广泛应用于地铁列车的端部吸能结构中。以某型地铁列车的刨削式防爬器为研究对象,使用有限元仿真的方式建立该吸能结构的对称简化模型,并结合台车冲击的试验数据验证有限元模型的准确性;通过数值仿真的方式,将刨刀前角(α)、刨刀后角(β)、刨刀宽度(w)和刨削深度(d)作为输入变量,以总吸能量(E_(A))和吸能阶段的平均刨削力(M_(PF))为耐撞性指标,以样本方差(S^(2))作为考核参照,通过全因子法对输入变量进行参数化分析;在此基础上,利用径向基函数构建代理模型,并采用多目标遗传算法(MOGA)对该吸能结构的主要设计参数进行优化设计,以确定结构参数的最佳的配置方案。研究结果表明:在该型刨削式防爬吸能结构的主要设计尺寸参数中,β对E_(A)、M_(PF)以及S^(2)的影响均不明显;α对MPF、E_(A)呈负相关,同时与S^(2)呈正相关;w和d对E_(A)与M_(PF)呈正相关、与S^(2)呈负相关;通过优化设计得到的吸能结构的最优的参数设计方案中:d为3.94 mm;α为7.78°,w为34 mm;最优设计方案的E_(A)提高了5.91%,M_(PF)提高了5.89%,S^(2)降低了45.4%,耐撞性与平稳性得到了提高。研究结果可为地铁列车刨削式防爬吸能结构的设计提供工程参考。

时速120 km地铁快线空气动力学试验研究

为探明设计时速120 km快速地铁列车在多区段桥隧衔接线路运行时的气动效应和气密性能,采用实车试验的方法,在武汉某多区段桥隧衔接地铁快线对某4车编组的新研A型密封性地铁列车开展空气动力学测试。实验测试系统采用LL-250-15A型Kulite压力传感器,通过测量列车外部和内部的瞬态压力变化,分析全线路车外压力波动特性,对比沿列车长度方向不同测点位置的压力变化幅值,并分析不同空调状态下的车内压力舒适性。经过3次实验测试分析,该实验的结果具有可重复性。研究结果表明:全线路运行时,列车在隧道段内加减速导致车外压力变化幅值明显大于高架段,气动效应最恶劣的位置为地下段人防门变截面处,列车上行通过该处时车外任意3 s内压力变化幅值为1 071 Pa,下行通过该处时车外任意3 s内压力变化幅值为905 Pa;相对于下行线全线路,上行线车外任意3 s内压力变化幅值大18.3%;列车正线运营时压力波保护阀会在压力变化剧烈区段进行动作响应,列车上行时,空调开启、压力波保护阀正常启用状态下,车内任意3 s内压力变化幅值相对于压力波保护阀打开未启用时减少了16%,下行时,减少了28%,空调压力波保护阀能够有效降低车外压力波动对车内气压变化的影响。本文研究成果可为快速地铁线路设计、地铁列车运营及地铁气密性优化提供参考依据。

基于建筑信息模型技术与智慧工地理念的地铁施工人员安全管理系统

[目的]人员的不安全行为是导致轨道交通工程施工安全事故的重要因素。为解决现存的视频图像监控系统依赖人工识别、安全质量问题发现不及时、不能及时报警等问题,需要对地铁施工人员安全管理系统展开研究。[方法]从整体架构、采集模块的设备安装、BIM(建筑信息模型)的建立及软件平台等方面,阐述了地铁施工人员安全管理系统的搭建方案。分析了地铁施工人员安全管理系统在具体工程试点的应用情况,进而验证该系统的智能识别准确性。[结果及结论]施工现场应用情况表明,地铁施工人员安全管理系统能智能识别未佩戴安全帽、进入禁止区域、睡岗离岗等人员不安全行为并自动报警,且报警正确率超过98%,大幅提高了安全隐患识别的精度和效率。相关人员通过交互终端即可实时查阅监控视频,实时接收报警信息,快速定位隐患发生位置并处置。

基于改进YOLOv8的地铁列车焊缝缺陷轻量化检测方法

针对现有的地铁列车车体焊接质量检测技术存在检测模型较大、检测精度和效率较低的问题,提出一种基于改进YOLOv8的焊缝缺陷轻量化检测方法。首先,利用相控阵超声波检测仪采集对接焊缝内部缺陷图像,通过图像预处理制作成焊缝缺陷数据集。然后,在YOLOv8模型基础上,利用Inner-SIoU优化原有损失函数、采用C2f-PConv替换C2f模块、引入大型可分离核注意力(LSKA)模块和挤压激励(SE)注意力机制,建立了基于改进YOLOv8的地铁列车车体焊缝缺陷质量检测模型,以提高焊缝缺陷特征提取和多尺度特征融合的能力。最后,利用改进的YOLOv8模型对焊缝缺陷数据集进行训练和测试。结果表明,改进的YOLOv8模型大小为7.91 M,对于焊缝缺陷的检测精度达到98.30%,检测速度达到138.9帧/s,与YOLOv8原始模型相比,模型更小,检测精度更高。

成都地铁基坑围护桩大变形原因分析及对策研究

[目的]周边环境及地质条件复杂的地铁基坑施工稍有不慎易导致基坑事故的发生。需分析基坑围护桩大变形原因,并提出针对性加固措施。[方法]以成都某近接老旧建筑物的桩锚支护结构地铁车站基坑为工程背景,分析了基坑施工过程中围护桩体发生大变形的原因,提出控制围护桩变形的加固措施。通过Harding-soil二阶高级本构模型研究了围护桩发生变形后,坑内采用反压堆载、基坑坑外坡体采用钢管桩及再次开挖前加强两道锚索措施的可行性。[结果及结论]模拟计算结果及现场实测结果表明,围护桩累计位移为77.77 mm;围护桩产生大变形后采用加固措施,可将围护桩水平位移控制在53 mm以内;根据模拟计算结果及现场实测结果,二者桩体水平位移曲线变化规律一致。实际施工结果表明,采取加固措施后,基坑变形控制效果明显,后续施工过程中未发生大范围变形。

地铁入口空间布局对室内空气质量的影响研究

城市地铁地处繁华地区,结构封闭,周边环境污染源较多,室内易积累污染物。本研究重点关注地铁口空间布局对室外颗粒物进入的影响,在调研中选取地铁站入口方向、顶棚形态、入口高宽比3个形态指标作为影响因子,经过实测验证CFD模型的可行性后,选择RNG k-ε模型模拟不同风速下各地铁口形态的室内污染情况。结果表明:(1)侧向比正向入口颗粒拦截率高一倍;(2)入口高宽比小于1∶1时入口宽度越大,地铁站整体空气质量越好;(3)顶棚形态对室内颗粒物的消减排列为:斜顶>平顶>无顶;(4)地铁口空间形态对不同直径的颗粒拦截效果不同。形态设计可以改善站内颗粒物进入情况,通过空气对流、回流减少室外污染物的直接灌入。