Technical advances, innovation and challenges of developing high-speed rail in China

After little more than a decade of development, China’s 29 000 km high-speed railway network is by far the largest in the world. This paper describes the technological advances and innovations regarding trains, stations, ballastless track, automatic train operation and signalling that made such rapid development possible, as well as setting new global standards for safety, efficiency and reliability. The engineering challenges of building and operating high-speed railways in diverse environments are also discussed, including areas with high winds, low temperatures, underground caverns and debris flows.

On the safety assessment of an automatic train operation system

The paper examines the automatic train operation system as part of the locomotive control and protection system, the remote supervision centre’s means for control of onboard and trackside machine vision facilities. The focus is on the dependence of the system’s safety and dependability on the dependability characteristics of its components and adverse weather effects. The criteria of a system’s wrong-side and right-side failures were defined, the graph models were constructed of the safety and dependability states of an automatic train operation system. The Markovian graph method of calculating the safety and dependability of complex systems was substantiated. That allowed defining such key safety indicators of an automatic train operation system as the mean time to wrong-side failure, probability of wrong-side failure, wrong-side failure rate. The study established that the safety of an automatic train operation system primarily depends on the dependability of machine vision facilities. The growth of the system’s wrong-side failure rate is limited to half the failure rate of machine vision facilities. It was also established that the dependability of an automatic train operation system is defined by the failure rate of a locomotive control and protection system and the failure rate of machine vision facilities. The conducted analysis allows concluding that in order to achieve an acceptable level of safety of an automatic train operation system, efforts should focus on machine vision redundancy, ensuring the SIL4 functional safety of on-board and trackside machine vision facilities, as well as regular comparison of the outputs of on-board and trackside machine vision facilities, redundant output comparison, integration of the outputs in motion. Additionally, adverse weather effects are to be countered by improving the efficiency of machine learning of the machine vision software.

Notch-based speed trajectory optimisation for high-speed railway automatic train operation

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.

Optimization of Urban Rail Automatic Train Operation System Based on RBF Neural Network Adaptive Terminal Sliding Mode Fault Tolerant Control

Aiming at the problem of the large tracking error of the desired curve for the automatic train operation (ATO) control strategy, an ATO control algorithm based on RBF neural network adaptive terminal sliding mode fault-tolerant control (ATSM-FTC-RBFNN) is proposed to realize the accurate tracking control of train operation curve. On the one hand, considering the state delay of trains in operation, a nonlinear dynamic model is established based on the mechanism of motion mechanics. Then, the terminal sliding mode control principle is used to design the ATO control algorithm, and the adaptive mechanism is introduced to enhance the adaptability of the system. On the other hand, RBFNN is used to adaptively approximate and compensate the additional resistance disturbance to the model so that ATO control with larger disturbance can be realized with smaller switching gain, and the tracking performance and anti-interference ability of the system can be enhanced. Finally, considering the actuator failure and the control input limitation, the fault-tolerant mechanism is introduced to further enhance the fault-tolerant performance of the system. The simulation results show that the control can compensate and process the nonlinear effects of control input saturation, delay, and actuator faults synchronously under the condition of uncertain parameters, external disturbances of the system model and can achieve a small error tracking the desired curve.

Higher automation - methods to increase energy efficiency in railway operation

Automation is already present in many areas of the railway sector (e.g. computer-aided dispatching or electronic interlockings). In order to achieve climate goals and offer an attractive transport service, it is essential to advance automation and higher grades of automation (GoA). The four levels of automation range from supporting systems (GoA1) to automotive trains (GoA4). This paper summarises a study which outlines the impacts, requirements and potentials of higher GoA within different segments: passenger transport, freight and mixed traffic on mainlines and branch lines. The findings show that energy-efficiency and capacity can already be increased with the first two GoA for both, passenger and mixed traffic. Enhancements have an influence on costs, not to mention the customer satisfaction. The potential in freight transport, e.g. in shunting, can be exploited with intelligent freight trains (GoA4). This leads to improved safety and reduced costs. Within this study a tool to calculate energy consumption is established. It enables the depiction of various scenarios for different trains and driving behaviours. The simulation tool is validated by real measured data. The outcome of the calculation tool underpins the benefits of driver advisory systems (DAS) and automatic train operation (ATO). It can be stated that higher automation, especially on a dispositive level is essential if energy and capacity improvement are to be achieved, regardless of the type of network (electrified or non-electrified). However, operational optimisation has its limits. For non-electrified lines, alternative drives offer the opportunity to further mitigate environmental impacts.

Analysis of ATO System Operation Scenarios Based on UPPAAL and the Operational Design Domain

With the gradual maturity of the automatic train operation (ATO) system in subways, its application scope has also expanded to the high-speed railway field. Considering that the ATO system is still in the early stages of operation, it will take time to fully mature, and definite specifications of the requirements for system operation have not yet been formed. This paper presents the operational design domain (ODD) of the high-speed railway ATO system and proposes a scenario analysis method based on the operational design domain to obtain the input conditions of the system requirements. The article models and verifies the scenario of the linkage control of the door and platform door based on the UPPAAL tools and extracts the input and expected output of the system requirements of the vehicle ATO system. Combined with the input conditions of the system requirements, the system requirements of the vehicle ATO in this scenario are finally obtained, which provides a reference for future functional specification generation and test case generation.