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The purpose of this paper is to discuss the impact of organizational change on the competence of controllers in rail infrastructure operations. Controllers are a critical link in providing rail services. They guide train traffic 7/24 in real time from within control rooms by daily responding to a multitude of disturbances. Market reforms have radically changed their work conditions by unbundling and re-bundling control rooms.

Ethnographically inspired research has been performed at the work stations of controllers in both unbundled and re-bundled, both Dutch and British control rooms between 2007 and 2011. The author observed how controllers deal with moderate disturbances and discusses the nature of their underlying professional capacities, what guides their decision making in discretion. Implications are discussed how organizational change affects these capacities in case of unbundling and re-bundling control rooms.

The paper shows how to gain a more explicit understanding of what controllers, as professionals, essentially think and do. An open-interactive account of professional capacity emerges, in contrast to the private-cognitive view widespread in literature. Both conceptualizations of professional capacities have radically different implications for their susceptibility to organizational change.

This paper reveals an urgent perspective on the impact of market reforms, through the accompanying organizational change, on professional capacity at the operational level of providing public rail services.

Regenerative braking is an efficient energy saving technology in urban rail system, in which the recovery energy from braking trains is collected by some equipments and released to accelerating trains when needed. However, the high cost and low lifetime of storage devices prevent the widespread use of this technology. The purpose of this paper is to conduct thorough cost-benefit analysis to facilitate China’s urban rail companies to make decisions on the use of such technology.

To evaluate the benefit from regenerative energy storage, the authors formulate an improved integrated scheduling and speed control model to calculate the net energy consumption associated with different energy recovery rates and then define the benefit as the amount of energy saving arising from the usage of storage equipments. With the frequent charge/discharge operations on storage equipments, the energy recovery rate generally decreases which lowers the benefit, but the maintenance cost increases. By trading-off benefit and cost, the authors derive the optimal scrapping time, the maximum profit and the profitability condition for storage devices.

Simulation studies based on the Beijing Metro Yizhuang Line of China are given. The results show that compared with the current timetable and speed profile, the integrated scheduling and speed control approach with energy recovery rate of 0.5 can reduce the net energy consumption by 12.69 per cent; the net energy consumption can be well approximated as a linear function of energy recovery rate; and the maximum profit and the optimal scrapping time on regenerative energy storage devices are both positively related to the electricity price. The allowance proportion and the number of service trains such that busy lines with higher electricity price or allowance proportion have advantages to use the regenerative energy storage devices.

In this work, a linear energy recovery rate and a linear maintenance cost are used in the cost-benefit analysis process. In future research, the more accurate expressions on energy recovery rate and maintenance cost should be considered if more data on recovery rate and maintenance cost can be gathered.

The main values of this paper are to develop the integrated optimization approaches for train scheduling and speed control and, on this basis, make thorough cost-benefit analysis for regenerative energy storage to improve the operations management of urban rail transit.

This paper aims to define the concept, composition, connotation, functional technology and development path of autonomous transportation systems (ATS) and provide theoretical basis and support for the construction and development of ATS.

The research analyzes the concept and connotation of ATS, studies the composition and structure of ATS, sorts out pillar function technology system including perception, digitization, interoperability, computing and integration in ATS hierarchically, and looks forward to the future development path of ATS from human participation and systems intelligence.

This paper puts forward the concept, composition, connotation and structure of ATS, proposes the pillar functional technology system of ATS and proposes four development stages of ATS.

The research can provide a theoretical and scientific basis for the high-quality, efficient, orderly construction and development of ATS.

The purpose of this paper is to attempt to apply the theory of grey clustering evaluations in coal railway transportation on the “Datong‐Qinhuangdao” heavy haul railway line, to provide a reliable selection plan for heavy haul railway transportation.

Grey clustering evaluations are important contents of grey system. Starting from the investigation on the evaluations in coal railway transportation on the “Datong‐Qinhuangdao” line, the authors realize that the reasonable plan developed from the real equipment and wagon flow conditions for optimal organizing of trains to achieve minimum unloading time is becoming the goal of the organizing optimization. According to the theory of grey clustering evaluations, all the system parameters such as, transportation volume per year and cost of transportation, can be combined with each other through some methods. This allows the authors to apply the theory of grey clustering evaluations on the “Datong‐Qinhuangdao” heavy haul railway line, and provide a reliable selection plan for heavy haul railway transportation. The results of the statistical analysis can be used as the basic theory to serve the coal railway transportation, and are applicable to provide reliable transportation.

This paper presents the theory of grey clustering evaluations in coal railway transportation on “Datong‐Qinhuangdao” heavy haul railway line. The convincing results of the grey classes are reported, and can be used as the basic theory to provide reliable transportation.

The method exposed in the paper can be used at each company's level for providing a reliable selection plan for heavy haul railway transportation. The results can also be used as the basic theory to provide reliable transportation.

The paper succeeds in providing a reliable selection plan for heavy haul railway transportation by using one of the newest developed theories: grey systems theory.

The purpose of this paper is to generate line plan in emergencies for railway networks to complete the passenger transportation.

The authors first build a mathematical model, focusing on the frequency setting and stops setting. Then, considering the OD passenger flow data, the authors first propose the method to solve the train frequency setting problem of different types. Genetic algorithm is designed to solve the stops setting problem. The approach is tested with the data from Beijing-Shanghai high-speed railway and its neighbour existing railway.

The authors find that the model is suitable to generate line plan in emergencies for railway networks and the algorithm has good calculating performance.

The new algorithms to generate line plan proposed in this paper can be embedded in the decision support system for railway operators.

Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.

To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.

Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.

This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

Train re-scheduling remains a longstanding challenge in railway operation. To design high-quality timetable in fuzzy environment, the purpose of this paper is to study train re-scheduling problem under the fuzzy environment, in which the fuzzy coefficients of the constraint resources have the fuzzy boundaries.

Based on the improved fuzzy linear programming, the train re-scheduling model is constructed. Aiming at dealing with the fuzzy characteristics of the constraint coefficients value range boundaries, the description method of this kind of objective function is proposed and the solving approach is presented. The model has more adaptability to model a common train re-scheduling problem, in which some resources of the constraints are uncertain and have the characteristics of fuzziness and the boundaries of the resources are fuzzy.

Two numerical examples are carried out and it shows that the model proposed in this paper can describe the train re-scheduling problem precisely, dealing with the fuzzy boundaries of the fuzzy coefficients of the constraint resources. And the algorithm present is suitable to solve the problem. The approach proposed in this paper can be a reference for developers of railway dispatching system.

It is the first time to study train re-scheduling problem under the fuzzy environment, in which the fuzzy coefficients of the constraint resources have the fuzzy boundaries.

This paper aims to propose an enhanced densely dehazing network to suit railway scenes’ features and improve the visual quality degraded by haze and fog.

It is an end-to-end network based on DenseNet. The authors design enhanced dense blocks and fuse them in a pyramid pooling module for visual data’s local and global features. Multiple ablation studies have been conducted to show the effects of each module proposed in this paper.

The authors have compared dehazed results on real hazy images and railway hazy images of state-of-the-art dehazing networks with the dehazed results in data quality. Finally, an object-detection test is taken to judge the edge information preservation after haze removal. All results demonstrate that the proposed dehazing network performs better under railway scenes in detail.

This study provides a new method for image enhancing in the railway monitoring system.

This paper aims to reschedule the freight train timetable in case of disturbance to restore the train services as soon as possible.

Hence, an integer linear programming model for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The proposed model based on the alternative graph at the microscopic level depicts the freight train movements in detail. Multiple dispatching measures such as re-timing and re-ordering are taken into account. Moreover, two objective functions, namely, the total final delays and the consecutive delays, are minimized in the freight trains dispatching problem.

Finally, a real-world computational experiment based on the Haolebaoji-Ji’an freight heavy-haul railway is implemented. The results of all disrupted cases are obtained within 10 s. The results give insight into that the consecutive delays are more than the total final delays when the same disrupted situation and the consecutive or total final delays increase as the primary delays increase.

An integer linear programming model based on the alternative graph for the real-time freight heavy-haul railway traffic management is developed in case of large primary delays caused by the delayed cargos loading. The method can be developed as the computer-aided tool for freight train dispatchers.