传统铁道工程实训向“高铁”转型的研究与实践

文章分析了传统铁道工程实训条件的局限性,并针对高铁轨道构造及其施工与维修过程特点,提出了高职院校传统的铁道工程实训教学基地应将高铁轨道构造、施工新技术、维修新设备等引入实训建设中,围绕高铁轨道精调、无缝线路焊接及探伤、大型机械养路等方面实施"高铁"转型改造方案,构建基于当前高速铁路的铁道工程实训教学基地。     

Risk of increasing temperature due to climate change on high-speed rail network in Spain

With more than 3,200 km of track, the Spanish high-speed rail network is the longest network in Europe and the second largest in the world after China. Due to its geographical location in southern Europe, the entire network is exposed to periods of elevated temperatures that can cause disturbances and severe disruptions such as rail deformation, or in the worst case, lateral track buckling. In this study, the vulnerability of the current Spanish high-speed rail network is analysed in terms of track buckling failures with a Monte Carlo simulation. Downscaled temperature projections from a range of Global Climate Models (GCMs), under three Representative Concentration Pathways (RCP4.5, RCP6.0 and RCP8.5), were forced in a buckling model and particularized for different segments of the network. With that, the proposed methodology provides the number of rail buckles expected per year by assuming current maintenance standards and procedures. The result reveals significant increase in the occurrence of buckling events for future years, mainly in the central and southern areas of mainland Spain. However, relevant variations are found in different climates and time horizon scenarios in Spain. The anticipated buckling occurrences highlight the vulnerability of the Spanish rail network in the context of global warming scenarios. Overall, the proposed methodology is designed to be applicable in large-scale railway networks to identify potential buckling sites for the purpose of understanding and predicting their behaviour.     

Field investigation and parametric study of greenhouse gas emissions from railway plain-line renewals

Railway transportation is becoming increasingly important in many parts of the world for mass transport of passengers and freight. This study was prompted by the industry’s need to systemically estimate greenhouse gas emissions from railway construction and maintenance activities. In this paper, the emphasis is placed on plain-line railway maintenance and renewal projects. The objective of this study was to reduce the uncertainties and assumptions of previous studies based on ballasted track maintenance and renewal projects. A field-based data collection was carried out on plain-line ballasted track renewals. The results reveal that the emissions from the materials contribute more than nine times the CO₂-e emissions than the machines used in the renewal projects. The results show that extending the lifespan of rail infrastructure assets through maintenance is beneficial in terms of reducing CO₂-e emissions. Analysis was then carried out using the field data. Then the results were compared to two ballastless track alternatives. The results show that CO₂-e emissions per metre from ballasted track were the least overall, however, the maintenance CO₂-e emissions are greater than those of ballastless tracks over the infrastructure lifespan, with ballasted track maintenance emitting more CO₂-e emissions at the 30 and 60 year intervals and the end of life when compared to the ballastless track types. The outcome of the study can provide decision makers, construction schedulers, environmental planners and project planners with reasonably accurate GHG emission estimates that can be used to plan, forecast and reduce emissions for plain-line renewal projects.     

Data-driven optimization of railway maintenance for track geometry

Railway big data technologies are transforming the existing track inspection and maintenance policy deployed for railroads in North America. This paper develops a data-driven condition-based policy for the inspection and maintenance of track geometry. Both preventive maintenance and spot corrective maintenance are taken into account in the investigation of a 33-month inspection dataset that contains a variety of geometry measurements for every foot of track. First, this study separates the data based on the time interval of the inspection run, calculates the aggregate track quality index (TQI) for each track section, and predicts the track spot geo-defect occurrence probability using random forests. Then, a Markov chain is built to model aggregated track deterioration, and the spot geo-defects are modeled by a Bernoulli process. Finally, a Markov decision process (MDP) is developed for track maintenance decision making, and it is optimized by using a value iteration algorithm. Compared with the existing maintenance policy using Markov chain Monte Carlo (MCMC) simulation, the maintenance policy developed in this paper results in an approximately 10% savings in the total maintenance costs for every 1 mile of track.     

A proposal for cost-related and market-oriented train running charges

This paper examines some key aspects of a charging system for promoting railway transport, including charges reflecting a clear relationship with costs (transparency) and charges reflecting the quality of the infrastructure manager's service. Train running charges recover track-related costs and can help to develop a charging system that meets these requirements. To orient train running charges to the market, a method for processing track maintenance and renewal costs is proposed whereby the quality of the service provided by an infrastructure is measured according to its utility to the railway undertaking. To achieve transparency, a single indicator is used for cost planning and the subsequent levying of costs on railway undertakings. The paper includes an example of how proposed train running charges would be calculated according to data from 14 European countries. The example shows that short-distance trains generate the lowest maintenance and renewal costs, followed by long-distance trains and freight trains.     

A new Swedish railroad policy: Separation of infrastructure and traffic production

In 1988 the Swedish nationalized railway company was separated into two separate entities, the Swedish State Railways in charge of running rail transport and the National Rail Administration, responsible for investment in and maintenance of rail infrastructure. This paper describes institutional aspects of this new railway policy. It also specifies methodological and practical problems in the computation of social marginal costs for using rail as well as road infrastructure. It is furthermore made likely that present fuel charges on road vehicles, but not the new rail use charges, are insufficient to cover costs for infrastructure use.     

Multi-level condition-based maintenance planning for railway infrastructures – A scenario-based chance-constrained approach

This paper develops a multi-level decision making approach for the optimal planning of maintenance operations of railway infrastructures, which are composed of multiple components divided into basic units for maintenance. Scenario-based chance-constrained Model Predictive Control (MPC) is used at the high level to determine an optimal long-term component-wise intervention plan for a railway infrastructure, and the Time Instant Optimization (TIO) approach is applied to transform the MPC optimization problem with both continuous and integer decision variables into a nonlinear continuous optimization problem. The middle-level problem determines the allocation of time slots for the maintenance interventions suggested at the high level to optimize the trade-off between traffic disruption and the setup cost of maintenance slots. Based on the high-level intervention plan, the low-level problem determines the optimal clustering of the basic units to be treated by a maintenance agent, subject to the time limit imposed by the maintenance slots. The proposed approach is applied to the optimal treatment of squats, with real data from the Eindhoven-Weert line in the Dutch railway network.     

Rail track infrastructure ownership: investment and operational issues

As privatisation of railway systems reach the political agendas in a number of countries, the separation of track infrastructure from train operations is seen as providing the vehicle which will improve profitability within the rail industry. This paper deals with three main issues related to such separation within a freight railway focus, namely: investment appraisal; track standards and maintenance; and train operating performance. The conflicts of interest between the owners of track and their client operators are discussed in detail. Costs related to track capacity and congestion need to be taken into account, given that additional trains are likely to lead to increased risk of delays to existing services. The paper discusses the use of a travel time reliability model to estimate the additional costs imposed on the system through the introduction of specific train services.It is concluded that investment in individual elements of railway infrastructure must be integrated with the overall financial and customer service strategies of both operators and owners. As an alternative to current practices, a hybrid model of track ownership is put forward here. Under such a model, a joint-venture company with equity from the main ÒplayersÓ would be owner of track. This would allow some of the benefits of vertical integration to be retained, whilst providing fair access to new operators.     

Estimating the marginal cost of railway track renewals using corner solution models

Economic theory advocates marginal cost pricing for efficient utilisation of transport infrastructure. A growing body of literature has emerged on the issue of rail marginal infrastructure wear and tear costs, but the majority of the work is focused on costs for infrastructure maintenance. Railway track renewals are a substantial part of an infrastructure manager’s budget, but in disaggregated statistical analyses they cause problems for traditional regression models since there is a piling up of values of the dependent variable at zero. Previous econometric work has sought to circumvent the problem by aggregation in some way. In this paper we instead apply corner solution models to disaggregate (track-section) data, including the zero observations. We derive track renewal cost elasticities with respect to traffic volumes and in turn marginal renewal costs using Swedish railway renewal data over the period 1999–2009. This paper is the first attempt in the literature to apply corner solution models, and in particular the two-part model, to disaggregate renewal cost data in railways. It is also the first paper that we are aware of to report usage elasticities specifically for renewal costs and therefore adds important new evidence to the previous literature where there is a paucity of studies on renewals and considerable uncertainty over the effects of rail traffic on renewal costs. In the Swedish context, we find that the inclusion of marginal track renewal costs in the track access pricing regime, which currently only reflects marginal maintenance costs, would add substantially to the existing track access charge. EU legislation requires that access charges reflect the ‘costs directly incurred as a result of operating the train service’, which should include a marginal renewal cost component. This change would also increase the cost recovery ratio of the Swedish infrastructure manager, thus meeting a policy objective of the national government.     

Infrastructure maintenance,regeneration and service quality economics: A rail example

This paper proposes a formalized framework for the joint economic optimization of continuous maintenance and periodic regeneration of rail transport infrastructure taking into account output consisting not only in traffic levels but also in track service quality. In contrast with much optimization work pertaining to spatially contiguous maintenance works, its principal economic emphasis and objective focus are centered on the optimal allocation of current maintenance and periodic renewal expenses, on their yearly distribution among large network partitions, and on infrastructure pricing. The model equations are based on very simple assumptions of infrastructure degradation laws and on a manager's objective function optimized through optimal control procedures. Equations are tested on national French rail track segment databases using Box–Cox transformations and match rail regeneration and maintenance practices prevailing in France. More generally, the paper makes a broad contribution to capital theory, on the optimal maintenance and renewal of equipment, and defines a method applicable not only to other transport infrastructure but to a wide range of capital goods, including housing, cars and industrial machines.     

Design and evaluation of railway corridors based on spatial ecological and geological criteria

Transport infrastructure is closely linked to several sustainability issues of main policy relevance, and significant impacts on biodiversity as well as resource use and construction costs relate to the corridor design and location in the landscape. The aim of this study was to develop methods for railway corridor planning, in which corridor design and location would be based on important ecological and geological sustainability criteria. The method, an MCA framework including both spatial and non-spatial MCA, was demonstrated on a railway planning proposition in an urbanising area north of Stockholm, Sweden. Alternative spatial alignments for 6 railway corridors were derived based on criteria representing biodiversity, resource efficiency and costs, developed from ecological and geological knowledge, data and models. The method identified a study area specific positive synergy between ecological and geological sustainability criteria. The evaluation part of the methodology could furthermore identify uncertainties in the input data and assumptions and conflicts between ecological criteria. In order to arrive at a well-informed decision support system, the criteria as well as the decision rules employed could be further elaborated. Other relevant sustainability issues would also need to be integrated, such as cultural landscapes, recreation, and other ecosystem services. Still, arriving at a corridor design informed by the ecological and geological conditions in the planned area, as demonstrated by this study, could improve the sustainability performance of transport infrastructure planning.     

Are railways really that bad? An evaluation of rail systems performance in Europe with a focus on passenger rail

With a large number of railway development projects in Europe and worldwide, which once completed will be serving rail passengers of the future, this paper aims to take a step back and evaluate current railway systems performance. The objectives are to compare statistical data on various passenger-related parameters of the railway system in a number of selected European countries and draw conclusions on the level of their performance when compared to the European average.Analyses of publically available statistical data, extracted from the Eurostat service at a European level will allow for a comparison of various indicators which influence the performance of the railway systems from an infrastructure and operational perspectives. The analyses will also allow identifying key performance indicators for the accurate assessment of the rail systems.The paper will highlight case studies for various parameters which are important to stakeholders of the railways, including infrastructure managers, rail operators, policy makers and the end users. This knowledge will be to the benefit of today’s railway industry as well as the rail systems of the future, as it will show trends drew upon existing data which might continue in the future.     

Position synchronization for track geometry inspection data via big-data fusion and incremental learning

Track geometry inspection data is important for managing railway infrastructure integrity and operational safety. In order to use track geometry inspection data, having accurate and reliable position information is a prerequisite. Due to various issues identified in this research, the positions of different track geometry inspections need to be aligned and synchronized to the same location before being used for track degradation modeling and maintenance planning. This is referred to as “position synchronization”, a long-standing important research problem in the area of track data analytics. With the aim of advancing the state of the art in research on this subject, we propose a novel approach to more accurately and expediently synchronize track geometry inspection positions via big-data fusion and incremental learning algorithms. Distinguishing it from other relevant studies in the literature, our proposed approach can simultaneously address data exceptions, channel offsets and local position offsets between any two inspections. To solve the Position Synchronization Model (PS-Model), an Incremental Learning Algorithm (IL-Algorithm) is developed to handle the “lack of memory” challenge for the fast computation of massive data. A case study is developed based on a dataset with data size of 18 GB, including 58 inspections between February 2014 and July 2016 over 323 km (200 miles) of tracks belonging to China High Speed Railways. The results show that our proposed model performs robustly against data exceptions via the use of multi-channel information fusion. Also, the position synchronization error using our proposed approach is within 0.15 meters (0.5 feet). Our proposed data-driven, incremental learning algorithm can quickly solve the complex, data-extensive, position synchronization problem, using an average of 0.1 s for processing one additional kilometer of track. In general, the data analysis methodology and algorithm presented in this paper are also suitable to address other relevant position synchronization problems in transportation engineering, especially when the dataset contains multiple channels of sensors and abnormal data outliers.     

Standardization of capacity unit for headway-based rail capacity analysis

Determining the required capacity upgrades to accommodate future demand is a critical process in assisting public and private financing of capacity investments. Conventional railway systems usually operate multiple types of trains on the same track. These different types of trains can exert substantially different capacity impact, and can cause serious operational conflicts. In the past, rail line capacity is commonly defined as the maximum number of trains that can be operated on a section of track within a given time period. However, a specific unit (trains/hr or trains/day) does not reflect the heterogeneity of train types. According to the concept of base train equivalents (BTE) and base train unit (BTU), this study developed headway-based models to determine BTE for transforming different train types into a standard unit (i.e., BTU). An approximate method for lines with three and more types of trains was also proposed to compute BTEs for non-base trains. Results from the case studies demonstrate that this method enables the standardization of rail capacity unit, facilitates assessment of the impact from heterogeneous trains, and allows comparison and evaluation of the capacity measurements from different lines and systems.     

Infrastructure based approach for roadway departure risk assessment

This paper presents a warning device to prevent the roadway departure of light vehicles while cornering. The proposed risk assessment methodology is based on recent works from the authors (Rey et al., 2011b,a; Rey, 2010). Given the random variability arising from the driver, the vehicle and the infrastructure at the entrance to the curve, a probabilistic strategy is adopted to assess the roadway departure risk. The infrastructure-based methodology enables the real curve characteristics to be considered and an alarm triggering decision to be made. Two safety criteria are tested and the potential safety benefits of the proposed warning device are evaluated. Contrary to existing roadway departure warning systems, the proposed approach does not require extra equipment for vehicles; it only requires that the measuring and warning devices be part of the road infrastructure, which is a great advantage in terms of economic cost.     

Evaluation of CO2 emissions from railway resurfacing maintenance activities

This paper is the world first to investigate the CO₂ impact of railway resurfacing in ballasted track bed maintenance. Railway resurfacing is an important routine maintenance activity that restores track geometry to ensure safety, reliability and utility of the asset. This study consisted of an extensive field data collection from resurfacing machineries (diesel-engine tamping machines, ballast regulators and ballast stabilisers) including travel distances, working distances, fuel consumption and construction methodologies. Fuel consumption was converted to a kg CO₂/m using the embodied energies of diesel. Analyses showed that tamping machines emitted the highest CO₂ emissions of the resurfacing machineries, followed by ballast regulators and ballast stabilisers respectively. Tamping machines processed 4.25 m of track per litre of diesel, ballast regulators processed 6.51 m of track per litre of diesel and ballast stabilisers processed 10.61 m of track per litre of diesel. The results were then compared to previous studies and a rigorous parametric study was carried out to consider long-term resurfacing CO₂ emissions on Australian railway track. The outcome of this study is unprecedented and it enables track engineers and construction managers to critically plan strategic rail maintenance and to develop environmental-friendly policies for track geometry and alignment restoration.     

An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways’ condition,planning and cost

National railways are typically large and complex systems. Their network infrastructure usually includes extended track sections, bridges, stations and other supporting assets. In recent years, railways have also become a data-rich environment.Railway infrastructure assets have a very long life, but inherently degrade. Interventions are necessary but they can cause lateness, damage and hazards. Every day, thousands of discrete maintenance jobs are scheduled according to time and urgency. Service disruption has a direct economic impact. Planning for maintenance can be complex, expensive and uncertain.Autonomous scheduling of maintenance jobs is essential. The design strategy of a novel integrated system for automatic job scheduling is presented; from concept formulation to the examination of the data to information transitional level interface, and at the decision making level. The underlying architecture configures high-level fusion of technical and business drivers; scheduling optimized intervention plans that factor-in cost impact and added value.A proof of concept demonstrator was developed to validate the system principle and to test algorithm functionality. It employs a dashboard for visualization of the system response and to present key information. Real track incident and inspection datasets were analyzed to raise degradation alarms that initiate the automatic scheduling of maintenance tasks. Optimum scheduling was realized through data analytics and job sequencing heuristic and genetic algorithms, taking into account specific cost & value inputs from comprehensive task cost modelling. Formal face validation was conducted with railway infrastructure specialists and stakeholders. The demonstrator structure was found fit for purpose with logical component relationships, offering further scope for research and commercial exploitation.     

A Bayesian approach to detect pedestrian destination-sequences from WiFi signatures

In this paper, we propose a methodology to use the communication network infrastructure, in particular WiFi traces, to detect the sequence of activity episodes visited by pedestrians. Due to the poor quality of WiFi localization, a probabilistic method is proposed that infers activity-episode locations based on WiFi traces and calculates the likelihood of observing these traces in the pedestrian network, taking into account prior knowledge. The output of the method consists of candidates of activity-episodes sequences associated with the likelihood to be the true one. The methodology is validated on traces generated by a known sequence of activities, while the performance being evaluated on a set of anonymous users. Results show that it is possible to predict the number of episodes and the activity-episodes locations and durations, by merging information about the activity locations on the map, WiFi measurements and prior information about schedules and the attractivity in pedestrian infrastructure. The ambiguity of each activity episode in the sequence is explicitly measured.     

Train routing and timetabling problem for heterogeneous train traffic with switchable scheduling rules

This paper proposes a mathematical model for the train routing and timetabling problem that allows a train to occasionally switch to the opposite track when it is not occupied, which we define it as switchable scheduling rule. The layouts of stations are taken into account in the proposed mathematical model to avoid head-on and rear-end collisions in stations. In this paper, train timetable could be scheduled by three different scheduling rules, i.e., no switchable scheduling rule (No-SSR) which allows trains switching track neither at stations and segments, incomplete switchable scheduling rule (In-SSR) which allows trains switching track at stations but not at segments, and complete switchable scheduling rule (Co-SSR) which allows trains switching track both at stations and segments. Numerical experiments are carried out on a small-scale railway corridor and a large-scale railway corridor based on Beijing–Shanghai high-speed railway (HSR) corridor respectively. The results of case studies indicate that Co-SSR outperforms the other two scheduling rules. It is also found that the proposed model can improve train operational efficiency.