Real-time high-speed train rescheduling based on a Human-Computer Interaction framework

During railway operations,trains normally run as scheduled,but the occurrence of unexpected events will disrupt traffic flow and cause train deviation from the original timetable.In order to assist dispatchers in rescheduling trains,this paper introduces an innovative Human-Computer Interaction framework.This framework enables train dispatchers to propose different timetable adjustment instructions to the original or adjusted timetable.These instructions will be processed,stored,analyzed,and digested by computer program,which finally lead to the modification and calculation of the embedded mathematical model,then a new adjusted timetable will be produced and provided to dispatchers for checking and modifying.This framework can iterate for unlimited times based on dispatchers'intentions,until the final results satisfy them.A demonstration system named RTARS(Real-time Timetable Automatic Rescheduling System)is developed based on this framework and it has been applied in Beijing Railway Administration,which shows its effectiveness in reality.

Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

Image fusion methods in high-speed railway scenes:A survey

Image fusion refers to extracting meaningful information from images of different sources or modalities,and then fusing them to generate more informative images that are beneficial for subsequent applications.In recent years,the growing data and computing resources have promoted the development of deep learning,and image fusion technology has continued to spawn new deep learning fusion methods based on traditional fusion methods.However,high-speed railroads,as an important part of life,have their unique industry characteristics of image data,which leads to different image fusion techniques with different fusion effects in high-speed railway scenes.This research work first introduces the mainstream technology classification of image fusion,further describes the downstream tasks that image fusion techniques may combine within high-speed railway scenes,and introduces the evaluation metrics of image fusion,followed by a series of subjective and objective experiments to completely evaluate the performance level of each image fusion method in different traffic scenes,and finally provides some possible future image fusion in the field of rail transportation of research.

Optimal edge-cloud collaboration based strategies for minimizing valid latency of railway environment monitoring system

Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable,and the latency contribution of each task to the system is discrepant.Hence,two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper.First,the processing resources are allocated to the tasks based on the priorities,and the tasks are processed parallly with the allocated resources to minimize the system valid latency.Furthermore,considering the differences in the data volume of the tasks,which will induce the waste of the resources for the tasks finished in advance.Thus,the tasks with similar priorities are graded into the same group,and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously.Compared with the other four strategies in four railway monitoring scenarios,the proposed strategies proved latency efficiency to the high-priority tasks,and the system valid latency is reduced synchronously.The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.

A review of high performance computing applications in high-speed rail systems

Further improving the railway innovation capacity and technological strength is the important goal of the 14th Five-Year Plan for railway scientific and technological innovation.It includes promoting the deep integration of cutting-edge technologies with the railway systems,strengthening the research and application of intelligent railway technologies,applying green computing technologies and advancing the collaborative sharing of transportation big data.The high-speed rail system tasks need to process huge amounts of data and heavy workload with the requirement of ultra-fast response.Therefore,it is of great necessity to promote computation efficiency by applying High Performance Computing(HPC)to high-speed rail systems.The HPC technique is a great solution for improving the performance,efficiency,and safety of high-speed rail systems.In this review,we introduce and analyze the application research of high performance computing technology in the field of highspeed railways.These HPC applications are cataloged into four broad categories,namely:fault diagnosis,network and communication,management system,and simulations.Moreover,challenges and issues to be addressed are discussed and further directions are suggested.

A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

基于UPPAAL仿真软件的CTCS-3级行车许可研究

行车许可是列车安全运行的行车凭证,是无线闭塞中心通过与列车、联锁系统等设备的通信获得相关的信息后,生成并发送给列车,最终车载设备根据行车许可信息计算安全防护曲线,确保列车安全运行。因此,行车许可丢失或发生错误都会影响列车运行安全,而行车许可终点计算的合理性则会影响运营效率。分别分析了列车在接车、发车、区间运行等3个阶段的正常运营情况下和非正常运营情况下对行车许可的获取及采取的相应操作,然后用UPPAAL仿真软件中的时间自动机进行仿真验证分析结果的正确性。

市域铁路CBTC与CTCS-2贯通运行方案研究

[目的]为了满足市域铁路CBTC(基于通信的列车控制)信号系统与铁路CTCS-2(中国列车控制系统2级)信号系统互联互通的运行需求,特开展本研究。[方法]在现有CBTC和CTCS-2信号系统的架构基础上,提出该两种信号系统的融合方案。对两种融合方案在成本投入、影响范围、改造难度和适用范围这4个方面进行比较,最终选用车载设备同时满足两种不同信号制式地面设备的融合方案。其中,地面设备秉持“CTCS设备尽量少变,增加或修改CBTC设备”的设计原则,车载设备秉持“ATP(列车自动保护)核心设备独立,外围部件尽量共用”的设计原则;在保证系统运营效率、满足CTCS-2相关标准的前提下,提出“列车从CTCS-2线路转换至CBTC线路的转换方案”和“列车从CBTC线路转换至CTCS-2线路的转换方案”,以实现市域铁路CBTC与CTCS-2双向互联互通贯通运行。[结果及结论]研究结果表明,该选用方案的实现能够提升市域铁路运输效率,优化运输组织与管理,完善轨道交通网络化功能,促进中心城市与周边城市的协调发展。

TMIS在OS／390 SYSPLEX环境下的USS使用及HFS共享

介绍如何定义USS系统在SYSPLEX环境下的构架和文件系统共享。

使用DB2 UDB for OS／390分区型表空间的几点体会

针对DB2 UDB for OS／390分区型表空间，从分区型表空间如何改善查询响应速度、如何确定分区、如何命中分区和如何避免相关问题等几个方面对分区型表空间进行了简要的论述。

基于边缘控制逻辑的车站机电设备监控系统一体化设计

[目的]现有城市轨道交通管理模式还是以线为对象进行管理,网络化管理效能还未能充分发挥,如何更加集约、有效地对城市轨道交通网络进行管理,已成为各地城市轨道交通运营企业所面临的共同课题。以车站机电设备集中管控为目标,提出了基于边缘控制逻辑的车站机电设备监控系统一体化设计方案。[方法]分析了城市轨道交通网络化管理发展趋势以及网络化管理制约因素;提出了基于IT/OT(信息技术/运营技术)融合的边缘控制自动化发展方向;介绍了既有车站机电设备监控系统的技术架构和基于机电一体化的车站机电设备监控系统建设方案,并分析了该建设方案的技术特点和实施效果。[结果及结论]基于边缘控制器搭建车站机电设备管理系统,形成云边端架构,可实现对车站机电设备的集中管理,使控制体系更简洁、更安全、更高效、更经济。试点结果表明,基于边缘控制逻辑的车站机电设备监控系统一体化设计方案可行,可提升网络化管理能力。

标准IEEE 2839-2021《轨道交通安全计算机》正式发布

2021年9月23日,标准IEEE 2839-2021《轨道交通安全计算机》由IEEE标准协会正式发布。该标准由中车株洲电力机车研究所有限公司(简称“中车株洲所”)主导起草,是首项由中国企业制定的轨道交通领域的IEEE标准。作为轨道交通领域首个国际性安全计算机标准,其规定了轨道交通运输系统中安全计算机的功能、性能、接口和环境条件,适用于轨道交通车载和轨旁安全相关应用系统。该标准将在提高安全计算机的互换性、与应用系统的兼容性、简化系统设计以及降低全生命周期成本等方面起到积极推动作用。

RT21-ISCS综合监控系统中基于ID的模型数据合并技术

为了减轻轨道交通综合监控项目中调试阶段的实际环境对工程实施的限制,提出了一种合并多个数据库中模型数据的方法。该方法已在南京地铁2号线IMS(信息管理系统)中使用。在按照新ID重排数据的同时,维持模型之间原有的联系。实践表明,这种模型数据合并技术在工程的建模调试阶段能够提升效率和操作方便性。这种模型数据合并技术在其它工程中也具有普适性。

城市轨道交通综合监控系统顶层设计中的GWQS-ISCS理念

综合监控系统(ISCS)具有接口复杂、调试内容繁多、子系统数目庞大等特点,建设中往往会出现修正频繁、不断完善、后期接入系统时重新调整设计方案、通信协议不同导致施工难度加大等繁琐问题。ISCS的顶层设计质量关系到整个城市的轨道交通线网规划,关系到换乘站、延长线等的建设、运营问题,关系到一个城市的轨道交通建设水平。做好ISCS的顶层设计对于运营、维护、投资都有着举足轻重的作用。通过对设计目标、顶层设计、发展前景、发展愿景等方面的深入研究,提出了关于ISCS顶层设计中的绿色ISCS、智慧ISCS、品质ISCS、安全ISCS (简称GWQS-ISCS(Green,Wisdom,Quality,Security-ISCS)) 4个理念。

智能铁路施工监测关键技术研究与发展

从绿色、技术、信息互联3个层面,分析智能铁路施工监测的监测需求。同时,基于文献分析,从研究的数量趋势、主题分布、应用方向3个维度,阐述国内外文献研究概况,识别出北斗卫星导航、5G、人工智能、大数据、物联网、云计算、边缘计算、区块链、AR/VR等关键技术,进一步按照监测设备与通信技术、数据识别与分析方法、监测管理平台三大应用方向,分析关键技术研究现状。然后,基于关键技术特点,展开分析智能铁路施工监测关键技术赋能机制,从基础研究薄弱、融合深度不足、工业化范例缺乏等方面指出关键技术应用障碍,并基于技术发展趋势展望智能铁路施工监测发展。结果表明,智能铁路施工监测关键技术支撑体系在我国已初具雏形,并仍在深化基础研究和促进成果转化中。

基于Flume和Flink的轨道交通智能运维数据接收解析系统

随着轨道交通智能运维技术的不断发展,越来越多的车载设备将数据通过车载无线通信设备下发至地面服务器进行存储、分析以及可视化显示。通过研究相关大数据技术,提出一种基于日志收集框架Flume和流数据处理引擎Flink的智能运维数据接收解析系统,可在高吞吐量的基础上保证稳定性与实时性。

城市轨道交通智慧乘务综合服务系统

[目的]为实现司乘管理由人工方式向智能方式转变,实现智能排班、自动派班等功能,进而提升管理效能,提出了适用于城市轨道交通运营管理的智慧乘务综合服务系统。[方法]定义了智慧乘务综合服务系统的系统架构和功能需求,分析了该系统的内外部接口要求,给出了该系统各子模块的技术方案,介绍了该系统在上海轨道交通10号线的示范应用情况。[结果及结论]应用表明,该系统可提高司机生产率,降低人车比,有助于实现乘务管理提质增效。

我国海铁联运信息平台构建模式

我国海铁联运信息平台经过多年的发展,各联运市场主体已实现了部分数据与信息交换和业务协同,但各类海铁联运业务平台信息未充分整合且标准不一,仍未能向托运人提供“一站式”的运输服务,也未能向多式联运经营人提供足够海铁联运公共信息。针对我国现有海铁联运信息平台以及多式联运经营人发展现状与问题进行分析,提出构建以联盟链技术为核心的区块链海铁联运信息共享平台。在阐述区块链技术基本特征的基础上,从平台构建主体和服务对象、公共信息管理、平台应用层等方面对平台建设进行探讨,并根据海铁联运运输特点探究区块链技术中信息调用机制、共识机制、智能合约在海铁联运业务的应用,为我国海铁联运信息平台升级转型提供研究支撑。

地铁列车冲突不确定性的预测模型及验证方法

地铁运营中,精准高效的列车间冲突预测是调度员行车调整的依据和基础。因此,精准高效地预测列车之间对行车资源请求的冲突一直是行业内持续研究的问题。列车实际运行状态的动态性导致列车间冲突的不确定性。针对目前普遍对于列车间冲突确定性的预测方式,引入地铁列车间冲突不确定性的预测方式,利用样本平均近似法(SAA)对列车运行状态的不确定性进行描述,继而表述列车之间对行车资源请求冲突的不确定性,然后提出一种列车间冲突不确定性的预测模型,并针对模型的预测结果设计验证其预测精度的方案。最后,利用南京地铁3号线列车运行实绩数据进行算例验证,验证结果表明模型预测结果具有较高的准确性。

城市轨道交通数字化转型若干问题思考

[目的]城市轨道交通数字化转型已成为行业未来发展的趋势。不同于制造业的数字化转型,城市轨道交通作为基于传统技术架构体系下的大规模运营服务系统,受制于管理理念、管理模式、技术体系、行业壁垒以及对传统业务的理解等,在数字化转型过程中面临诸多挑战,因此需对相关问题进行深入研究。[方法]从顶层设计、场景设计、设备监控、业务划分、网域划分,以及数据价值与管理要求等方面分析了城市轨道交通企业在数字化转型中面临的问题,并在此基础上提出了数字化发展的策略和要求。[结果及结论]城市轨道交通企业的数字化转型是一项系统性工程,其广度和深度超越了智能运维生产体系,涵盖了企业后台管理等更高层级的业务。这种转型不仅难度和复杂度高,而且是一个不断迭代和优化的过程,要清晰规划思路、设定明确目标、构建顶层架构、进行系统筹划,然后再稳步推进实施,以确保转型过程的科学性、高效性和平稳性。