Future 5G-Oriented System for Urban Rail Transit:Opportunities and Challenges

As a development direction of urban rail transit system,the train autonomous circumambulate system(TACS)can operate in a safer,more efficient,and more economical mode.However,most urban rail transit systems transmit signals through industrial,scientific,and medical(ISM)frequency bands or narrow frequency bands,which cannot meet the requirements of TACS.As a promising solution,the 5th generation(5G)mobile communication provides more services for the future urban rail transit systems,and covers the shortages of exiting communication technologies in terms of capacity and reliability.In this paper,we first briefly review the research status of current train control system and introduce its limitations.Next,we propose a novel network architecture,and present new technologies and requirements of the proposed architecture for TACS.Some potential challenges are then discussed to give insights for further research of TACS.

Optimization of train plan for urban rail transit in the multi-routing mode

The train plan of urban rail transit under multi-routing mode can be divided into three parts： train formation, train operation periods and corresponding train counts of each routing in each period. Based on the analysis of passen- ger＇s general travel expenses and operator＇s benefits, the constraints and objective functions are defined and the multiobjective optimization model for the train plan of urban rail transit is presented. Factors considered in the multi- objective optimization model include transport capacity, the requirements of traffic organization, corporation benefits, passenger demands, and passenger choice behavior under multi-train-routing mode. According to the characteristics of this model and practical planning experience, a three-phase solution was designed to gradually optimize the train formarion, train counts as well as operation periods. The instance of Changsha Metro Line 2 validates the feasibility and efficiency of this approach.

Greenhouse gas emission analysis and measurement for urban rail transit: A review of research progress and prospects

Rail transit plays a key role in mitigating transportation system carbon emissions.Accurate measurement of urban rail transit carbon emission can help quantify the contribution of urban rail transit towards urban transportation carbon emission reduction.Since the whole life cycle of urban rail transit carbon emission measurement involves a wide range of aspects,a systematic framework model is required for analysis.This research reviews the existing studies on carbon emission of urban rail transit.First,the characteristics of urban rail transit carbon emission were determined and the complexity of carbon emission measurement was analyzed.Then,the urban rail transit carbon emission measurement models were compared and analyzed in terms of the selection of research boundaries,the types of greenhouse gas(GHG)emissions calculation,and the accuracy of the measurement.Following that,an intelligent station was introduced to analyze the practical application of digital collaboration technology and energy-saving and carbon-reducing system platforms for rail transit.Finally,the urgent problems and future research directions at this stage were discussed.This research presents the necessity of establishing a dynamic carbon emission factor library and the important development trend of system integration of carbon emission measurement and digital system technology.

Urban rail departure capacity analysis based on a cellular automaton model

As an important traffic mode, urban rail transit is constantly developing toward improvement in service capacity and quality. When an urban rail transit system is evaluated in terms of its service capacity, the train departure capacity is an important index that can objectively reflect the service level of an urban rail transit facility. In light of the existing cellular automaton models, this paper proposes a suitable cellular automaton model to analyze the train departure capacity of urban rail transit under different variable factors and conditions. The established model can demonstrate the train operating processes by implementing the proposed sound rules, including the rules of train departure at the origin and intermediate stations, and the velocity and position updating rules. The properties of train traffic are analyzed via numerical experiments. The numerical results show that the departure capacity is negatively affected by the train departure control manner. In addition, （i） the real-time signal control can offer a higher train service frequency; （ii） the departure capacity gradually rises with the decrease in the line design speed to a limited extent; （iii） the departure capacity decreases with extension in the train length; （iv） the number of departed trains decreases as the train stop time increases; （v） the departure capacity is not affected by the section length. However, the longer the length, the worse the service quality of the urban rail transit line. The experiments show that the proposed cellular automaton model can be used to analyze the train service capacity of an urban rail transit system by performing quantitative analysis under various considered factors, conditions, and management modes.

Optimization method of urban rail train operational plan based on O-D time-varying demand

Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.Design/methodology/approach–The authors optimize the train operational plan in a special network layout,i.e.an urban rail corridor with dead-end terminal yard,by decomposing it into two sub-problems:train timetable optimization and rolling stock circulation optimization.As for train timetable optimization,the authors propose a schedule-based passenger flow assignment method,construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm.For the optimization of rolling stock circulation,the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.Findings–The case study shows that the train operational plan developed by the study’s approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.Originality/value–The example verifies the efficiency of the model and algorithm.

Urban rail transit disruption management: Research progress and future directions

Urban rail transit (URT) disruptions present considerable challenges due to several factors: i) a high probability of occurrence, arising from facility failures, disasters, and vandalism;ii) substantial negative effects, notably the delay of numerous passengers;iii) an escalating frequency, attributable to the gradual aging of facilities;and iv) severe penalties, including substantial fines for abnormal operation. This article systematically reviews URT disruption management literature from the past decade, categorizing it into pre-disruption and post-disruption measures. The pre-disruption research focuses on reducing the effects of disruptions through network analysis, passenger behavior analysis, resource allocation for protection and backup, and enhancing system resilience. Conversely, post-disruption research concentrates on restoring normal operations through train rescheduling and bus bridging services. The review reveals that while post-disruption strategies are thoroughly explored, pre-disruption research is predominantly analytical, with a scarcity of practical pre-emptive solutions. Moreover, future research should focus more on increasing the interchangeability of transport modes, reinforcing redundancy relationships between URT lines, and innovating post-disruption strategies.

基于车车通信列控系统的城市轨道交通列车运行效率分析

[目的]城市轨道交通T2T(车车通信)列控系统是一种新型的信号系统,其通过资源化管理方式对轨旁设备进行管控。为了验证该系统的优越性,需对该系统下的列车运行效率进行分析。[方法]针对T2T列控系统,基于资源管理层面和安全防护原理的特点,在折返工况下,将原本由联锁控制的双动道岔转变为两个单动道岔,并基于列车精确自定位实现ATP(列车自动防护),提高了岔区线路资源的使用能力;在区间和车站追踪工况下,通过前后车对于车速、加速度、所处线路位置等信息的实时互传,利用相对速度安全防护原理进一步缩小了列车的追踪间隔。通过上述两方面的技术革新,结合城市轨道交通线路的实际数据,对站后交叉渡线折返、站前单渡线折返、区间与车站追踪等运营场景进行了模拟仿真计算,确定了T2T列控系统的折返能力和区间追踪能力。[结果及结论]相较传统的CBTC(基于通信的列车控制系统),T2T列控系统在折返能力、追踪能力等方面均有着显著提升,更加适应于超大运量的城市轨道交通线路;T2T列控系统架构简单,轨旁设备少,尤其适合城市轨道交通的大修改造项目。

城市轨道交通超长隧道双车追踪模式下火灾烟气控制与人员安全疏散研究

[目的]城市轨道交通发车间隔一般较短,在超长隧道内会出现同方向行驶两列列车的情况,一旦发生火灾容易造成重大财产损失和人员伤亡,因此需对超长隧道双车追踪模式下的火灾烟气蔓延规律和人员安全疏散策略进行研究。[方法]采用FDS(火灾动力学模拟)软件和Path-finder软件,建立超长隧道火灾模型和人员安全疏散模型,对双车追踪模式下的火灾烟气蔓延规律,以及人员疏散进行仿真分析。[结果及结论]双车追踪模式下,前车尾部着火,通过临界风速纵向通风可保证前车火灾安全;火源下游烟气前锋的蔓延速度为3.20 m/s,至600 s时烟气蔓延至后车,620 s时烟气可完全覆盖后车;烟气温度沿隧道纵向衰减很快,且温度衰减符合双指数模型规律。双车追踪模式下,减小联络通道间距可减少人员疏散总时间,对人员疏散时离开列车的时间影响不大;开启列车端门和疏散平台一侧车门,可显著减少人员疏散时间。在超长隧道双车追踪的最不利火灾场景下,人员疏散存在困难,可通过减小联络通道间距保障人员疏散安全。

跨线条件下城市轨道交通列车交路计划优化方法

跨线运营是城市轨道交通重点发展方向。针对跨线条件下列车交路计划编制问题,通过构造乘客出行时空网络图准确刻画复杂交路下的客流行为,建立以最小化列车走行公里与乘客出行时间成本为目标的混合整数规划模型。模型以列车交路方案、开行比例与频率为决策变量,并针对跨线交路与本线交路的行车冲突,考虑非等间隔发车,确定列车发车时刻。设计基于交路及开行频率搜索与运行间隔协调的定制分解算法。案例结果表明,列车跨线方向与乘客换乘主方向一致时,跨线交路可同时提升企业运营与乘客出行效益。换乘出行导致的断面客流量差异是跨线交路开行方案设置的主要依据。研究结论可为运营企业制定列车交路计划提供依据,有助于提高网络运输效率。

城市轨道交通列车加开计划编制模型研究

本文主要研究城市轨道交通在计划编制阶段由于客流不均衡需要在初始运行图加开列车的问题,在确保列车运行安全降低运营成本的前提下合理地加开列车实现运输能力的灵活配置。将列车运行过程形式化描述为事件-活动网络,构建了分时段多目标优化列车加开计划编制模型,提出了启发式决策规则与禁忌搜索算法相结合的两阶段求解算法。结合地铁运行实际数据,在高峰时段和平峰时段分别构建不同算例场景,验证了模型和算法的可行性和有效性。

城市轨道交通正交异性钢桥面板疲劳损伤系数研究

基于城市轨道交通正交异性钢桥面板疲劳性能的重要性,对国内多个城市的轨道交通的交通荷载进行了调研,发现各线路各时段的客流量差异较大,各线路的载客平均轴重与空车平均轴重的比值不同,比值为1.02~1.51。轨道交通因乘客流量带来的轴重比例变化相对较小,因此每一列车都对钢桥结构的疲劳有一定影响。研究了疲劳损伤系数的组成,基于不同的应力循环次数,提出了基于列车荷载作用频次的城市轨道交通桥梁的3个疲劳损伤系数。研究结果可为城市轨道交通钢桥的疲劳设计提供参考,并为规范的修订提供技术依据,对完善城市轨道交通钢桥疲劳设计具有理论意义。

考虑动态随机客流的城市轨道交通列车时刻表仿真优化

为更加精准刻画动态随机客流与列车时刻表编制间的复杂匹配过程,综合考虑乘客动态随机到达过程、列车容量限制、车内拥挤度对乘客上下车速率影响、停站时间动态调整和列车运行安全防护等重要运营特征,构建城市轨道交通列车运行离散仿真模型。在此基础上,建立以最小化乘客平均候车时间为目标的随机非线性优化模型,并设计一种基于仿真的有限差分随机逼近算法,用于优化城市轨道交通发车方案。以国内某条线路的实际运营数据为例验证仿真模型及优化方法,结果表明所构建模型及算法具有较好的优化效果和计算效率,优化后的列车实绩运行时刻能更好地适应客流需求的动态随机性,且在不增加发车频次的前提下有效降低乘客平均候车时间,提升城市轨道交通运营管理水平。

利用A2C-ac的城轨车车通信资源分配算法

在城市轨道交通列车控制系统中,车车(T2T)通信作为新一代列车通信模式,利用列车间直接通信来降低通信时延,提高列车运行效率。在T2T通信与车地(T2G)通信并存场景下,针对复用T2G链路产生的干扰问题,在保证用户通信质量的前提下,该文提出一种基于多智能体深度强化学习(MADRL)的改进优势演员-评论家(A2C-ac)资源分配算法。首先以系统吞吐量为优化目标,以T2T通信发送端为智能体,策略网络采用分层输出结构指导智能体选择需复用的频谱资源和功率水平,然后智能体做出相应动作并与T2T通信环境交互,得到该时隙下T2G用户和T2T用户吞吐量,价值网络对两者分别评价,利用权重因子β为每个智能体定制化加权时序差分(TD)误差,以此来灵活优化神经网络参数。最后,智能体根据训练好的模型联合选出最佳的频谱资源和功率水平。仿真结果表明,该算法相较于A2C算法和深度Q网络(DQN)算法,在收敛速度、T2T成功接入率、吞吐量等方面均有明显提升。

城市轨道交通乘务交路方案编制的禁忌搜索优化方法

针对城市轨道交通普遍采用轮乘制、日班和两头班混合等特点,对城市轨道交通乘务交路方案编制问题进行研究,旨在降低乘务成本并提高乘务效率.首先,通过分析城市轨道交通乘务交路方案的构成要素,考虑值乘时长、值乘片段接续时间和接续地点等要求,构建值乘片段、值乘任务构成和乘务规则约束,由此建立以乘务组数量和总接续时间等综合指标最小化为目标函数的多目标0-1整数规划模型.然后,针对该模型设计禁忌搜索(Tabu Search,TS)算法进行求解,以先到先走(First-In-First-Out,FIFO)的就近指派原则得到初始解,并设计4种邻域变换策略,以提高邻域解的多样性,并构建基于多邻域结构的禁忌搜索求解算法,实现对乘务交路方案的优化.最后,以广州地铁7号线的乘务交路方案为例进行实例验证.研究结果表明:优化方案较实际运营方案的乘务作业段数和总接续时间分别降低了20%和4.94%,每个乘务作业段值乘列车数量从8.2列增加到10.3列,有效驾驶时间从5.4 h增加到5.8 h,优化方案的各项指标均得到显著提升.研究成果可以为城市轨道交通乘务计划编制提供理论和方法支持.

基于乘客服务水平和安全的城市轨道交通扣车方案评价

[目的]扣车是城市轨道交通发生长时间初始延误条件下经常采用的列车运行方案。为了评价该方案的合理性,需构建基于乘客服务和安全的扣车方案评价模型,并对扣车方案进行评价。[方法]考虑到乘客出行规律的复杂性和特殊性,制定了城市轨道交通扣车方案。构建了基于最大发车间隔、列车总延误时间、列车均衡性、终到延误列车数、滞留乘客数及乘客总旅行时间的扣车方案评价模型。选取上海某条轨道交通线路的4个区间,以早高峰小时的实际OD(起讫点)客流量为例进行计算。[结果及结论]计算表明,方案6下的综合评价指标最小,为最优扣车调整方案。该方案可以有效提高列车运行图的均衡性,减少滞留乘客的数量,降低车站的安全隐患。

基于滑模控制的虚拟编组列车追踪控制策略

[目的]现有的基于移动闭塞的列车控制系统中,相邻列车之间存在较大的安全裕度,在面对潮汐客流现象时,区段的运输效率同区段的实际运力需求无法匹配。虚拟编组列车能够提高线路的运力,同时能更好地适应不平衡的通勤客流。因此,需研究适用于虚拟编组列车的高精度追踪控制策略。[方法]针对虚拟编组列车运行控制问题,提出了一种基于滑模控制的虚拟编组运行控制策略。建立了列车动力学模型和虚拟编组列车运行控制模型;设计了非奇异终端滑模控制器,并对所设计的控制器进行了仿真测试。[结果及结论]在所提出的虚拟编组控制策略下,虚拟编组列车的位置跟踪误差和速度跟踪误差能够沿滑模面在有限时间内渐近收敛到零。在仿真验证的4列列车中,当首列列车运行状态发生改变时,虚拟编组中的其余列车会在很短的时间内跟踪期望的速度轨迹,验证了所提出的控制策略对虚拟编组列车追踪控制的有效性。

基于可预知大客流的城市轨道交通列车加开计划调整模型与算法

[目的]节假日、大型文体活动等事件会导致城市轨道交通线路产生可预知大客流,需在确保列车运行安全的前提下,根据客流预测情况在已有列车运行图中加开列车,以期在运营成本、运营组织复杂度和乘客服务水平之间取得平衡。[方法]采用事件-活动网络,对列车运行过程进行了形式化描述,建立了3个目标函数及相关的约束条件,进而构建了独立运用策略下列车加开计划调整模型、套跑混合运用策略下列车加开计划调整模型。在此基础上,提出了基于混合遗传禁忌的搜索算法。结合深圳地铁11号线的实际运营数据,在高峰时段和非高峰时段分别建立了不同的算例场景,以验证所建模型和算法的有效性。[结果及结论]所建模型支持不同运营时段、不同运行交路、不同车底接续策略下列车加开需求,在可预知大客流的运营调整上具有适用性。在车辆资源相对有限的情况下,为有效缓解高峰时段的客流压力,可灵活采用大小交路套跑混合运用策略,使线路的运输能力最大化。

基于加线技术的轨道交通临客开行计划优化模型

基于运行图加线技术构建适于计划性临客开行的运行线铺画方法.以运力与客流匹配度最大化、对原运行图调整最小化为优化目标,考虑行车安全、临客加线位置、开行时间域等约束,构建临客运行线铺画非线性整数规划模型,并对其线性转换以提高求解效率.以北京地铁8号线某大型活动散场大客流为场景进行案例分析,结果表明:所构建方法能够在既有运行图上有效铺画临客运行线,满足不同行车密度及停站模式下的临客开行需求.建议在较高密度行车条件下不采用“空车直达”停站模式.

城轨项目数智化造价管理应用研究

城轨建设是一项庞大复杂的工程,其特点是投资大、建设周期长、参建单位多,虽然经济效益低,但社会效益显著。住建部明确提出要加强工程造价数据积累,推行清单计量,建立工程造价数据库,坚持市场在资源配置中的决定性作用等要求,在“十四五”规划中也提出迎接数字时代,激活数据要素潜能,所以数字造价管理转型迫在眉睫。文章通过介绍城轨造价管理面临的现实困境,提出分别从创建标准化技术经济指标体系,建立智能化投资测算模型,BIM模型与造价信息同步集成,形成标准化的工程量清单体系,搭建城轨造价数据库,构建造价管理共享平台等6大应用路径,实现数智化造价管理,从而提升造价管理体系,促进城轨行业高质量发展。

城市轨道交通列车轮轨垂向力测量方法

[目的]城市轨道交通运营中通常会出现大量的隧道病害,列车轮轨力是各种病害的主要成因,因此,需在不影响城市轨道交通列车正常运营的条件下,对列车轮轨垂向力的测量方法进行研究。[方法]以成都地铁7号线茶店子站—一品天下站下行区间道床剥离病害为研究对象,基于弯矩差法理论,采用ANSYS有限元软件建立了静荷载及动荷载作用下的钢轨有限元模型,并对其进行了数值模拟分析。在室内对1根长2 m、3跨布置的钢轨进行了标定试验。[结果及结论]静荷载数值模拟分析表明,钢轨测点可选择在钢轨跨中轨底上表面边缘两侧位置;当钢轨跨中位置受到垂向力作用时,该点沿钢轨方向的应变最大,且应变随垂向力线性增加。通过标定试验测得的标定系数为0.6260×10^(6)kN,而数值模拟测得的标定系数为0.6441×10^(6)kN,两者偏差仅2.8%,可通过静荷载标定试验确定标定系数。轮轨垂向力的测量方法可以更好地评估轨道结构和列车运行的安全性,及时发现安全隐患,并采取相应措施进行修复和改进。