Automatic Train Control System Research Articles

Prospects of autonomous railway transport development

The implementation of unmanned train control systems offers a number of advantages, such as increasing the capacity of railway lines and traffi c volumes, reducing the ‘human factor’, as well as reducing operating costs. The paper considers the challenges arising from the use of automatic train control systems, and presents the prospects for the implementation of automatic technologies in railway transport for various railway systems. The social and economic aspects of changing professional activities in railway transport are described. Grades of automation applicable to surface urban railwaytransport are presented. The issues of proving the functional safety of machine vision systems as part of the train traffic control system and determining their level of safety completeness are discussed. Examples of railway transport automation in Russia and other countries are given. Basic scenarios of automatic control system operation describing normal and abnormal situations are formulated. In conclusion, the levels of technological readiness of the reviewed solutions in the fi eld of train traffic automation are defi ned. The tasks faced by railway companies in implementing these technologies are outlined, and possible ways of overcoming obstacles to the introduction of automatic systems are proposed, taking into account the current political situation.

Прогноз случайных процессов, при наличии единичных возмущений в интеллектуальных транспортных системах

Forecasting random perturbations allows improving the control quality in intelligent transport systems and ensuring the efficient operation of diagnostic systems. Several works are known where extrapolator models based on Chebyshev polynomials orthogonal on equidistant points are presented. These models use a predictive polynomial whose coefficients are computed using the least squares criterion. Additionally, an analysis of forecast errors for random stationary input signals has been conducted. At the same time, in the case of non-stationary input signals, singular perturbations may occur, the influence of which on the extrapolator leads to significant forecast errors.
 This article presents an example of the occurrence of additive perturbations that arise in automatic train control systems. An analytical expression has been derived, and calculations of forecast error magnitudes in the presence of singular perturbations have been conducted. The analysis of the calculation results allows determining the influence of extrapolator parameters on the forecast error magnitude, highlighting the necessity of detecting singular perturbations, and excluding their influence on the forecast error magnitude.
 The article discusses an algorithm for detecting singular perturbations and their exclusion during the forecasting process. The conclusion is drawn about the effectiveness of using extrapolators for random perturbations with the exclusion of singular perturbations in intelligent systems for automatic train control in subway transportation.

An adaptive safety control approach for virtual coupling system with model parametric uncertainties

Virtual coupling attracts extensive attention from the railway communities due to its promising capacity increase and flexibility improvement. Accurate control that guarantees system safety and performance remains a problem that needs to be further studied. This paper investigates the virtual coupling train system (VCTS) safety control problem with model parameter uncertainties using an adaptive nonlinear control strategy based on urban rail transit systems. A safe automatic train control model is introduced, and a novel control framework consisting of two levels is designed to give an overall virtual coupling train control architecture. For the leading train, we deploy an automatic train control system based on dynamic programming. Then, considering parameter uncertainties, we design an adaptive nonlinear controller that ensures safety and control efficiency for the following trains. The proposed control strategy can ensure that a virtually coupled train set tracks the given speed curve and keeps inner distance while guaranteeing the string stability and safety of the platoon, considering parameter uncertainties. The simulation results show that the proposed approach leads to great performance improvement in virtual coupling train operations.

Research on Tracking Control of Urban Rail Trains Based on Improved Disturbance Observer

Urban rail transit trains operate in a complex and changing environment susceptible to uncertainties such as unknown disturbances or actuator faults. In order to ensure that the automatic train control (ATC) system can operate safely and control accurately even when the train is affected by uncertainties, the train is first subjected to force analysis, and a multiple point-mass model for the urban rail trains (URTs) is established. Secondly, an improved disturbance observer is proposed to estimate and attenuate the unknown disturbance online. The stability of the URTs system under the improved disturbance observer-based control (IDOBC) is demonstrated based on the linear matrix inequality and Lyapunov theorem. Finally, the Simulink platform is used to verify the target curves obtained after data optimization of the certain Nanchang Metro line for case verification. Compared to the traditional disturbance observer-based control (TDOBC) method, the train tracking error converges to near the zero region faster after being subjected to an external disturbance, and the mean absolute error (MAE) metric is smaller throughout the whole operation. The control strategy proposed in this paper has a more desirable control effect and can ensure the safer and more stable operation of the URTs.

Real Time Control System for Metro Railways Using PLC & SCADA

This paper proposes to adopt SCADA and PLC technology for the improvement of the performance of real time signaling & train control systems in metro railways. The main concern of this paper is to minimize the failure in automated metro railways system operator and integrate the information coming from Operational Control Centre (OCC), traction SCADA system, traction power control, and power supply system. This work presents a simulated prototype of an automated metro train system operator that uses PLC and SCADA for the real time monitoring and control of the metro railway systems. Here, SCADA is used for the visualization of an automated process operation and then the whole operation is regulated with the help of PLC. The PLC used in this process is OMRON (NX1P2-9024DT1) and OMRON’s Sysmac studio programming software is used for developing the ladder logic of PLC. The metro railways system has deployed infrastructure based on SCADA from the power supply system, and each station’s traction power control is connected to the OCC remotely which commands all of the stations and has the highest command priority. An alarm is triggered in the event of an emergency or system congestion. This proposed system overcomes the drawbacks of the current centralized automatic train control (CATC) system. This system provides prominent benefits like augmenting services which may enhance a network’s full load capacity and network flexibility, which help in easy modification in the existing program at any time.

Communication-Based Train Control with Dynamic Headway Based on Trajectory Prediction

Rail transit plays a significant role in the operation of an efficient and effective urban public transportation system. Safety and capacity are some of the most crucial objectives in railway operations. The communication-based train control (CBTC) system is a continuous and automatic train control system that realizes constant and high-capacity train ground two-way communication. In this study, a dynamic headway model of the ‘softwall’ moving-block approach is proposed for CBTC to increase the track capacity and improve dispatching efficiency based on the train trajectory prediction. For this precise trajectory prediction task, we introduce a hybrid trajectory prediction model to combine Long Short-term memory (LSTM) and Kalman Filter (KF) to extract the train’s local data features and learn the long-term dependencies, respectively. Then we present a dynamic headway model to maximize the train headway and reduce the track distance. The leading trains’ information is used to construct the iterative learning control strategy, and the predicted trajectory is input into the algorithm of the headway model. We use a simulation model of the rail network in Chengdu to demonstrate the effectiveness of our proposed approach. The results show the Mean Absolute Error (MAE) of the predicted trajectory retreated to 93.97 cm and reductions in operation headway of at least 64.33% under the dynamic headway model versus the traditional moving-block model.

Dynamic speed trajectory generation and tracking control for autonomous driving of intelligent high-speed trains combining with deep learning and backstepping control methods

The development of autonomous transportation systems has received increasing attention over the last decades. Different from existing automatic train control systems, the decision-making capability in the autonomous driving system enables a train to adapt to the complicated and dynamic circumstances. This paper in particular focuses on the decision-making problem for the autonomous driving of intelligent high-speed trains, and proposes a novel decision-making framework by combining the deep learning and backstepping control methods. By exploiting the deep learning methods, a speed trajectory generator is trained with the actual driving data, and dynamically calculates the reference speed trajectory according to the real-time driving condition. Then, a backstepping controller is designed to track the reference speed trajectory such that the separation, cohesion and alignment requirements for the autonomous driving of high-speed trains are achieved. Simulation experiments are implemented to illustrate the effectiveness of our methods.

Constrained Spatial Adaptive Iterative Learning Control for Trajectory Tracking of High Speed Train

This paper proposes a constrain spatial adaptive iterative learning controller (CSAILC) for the displacement-speed trajectory tracking of automatic train control system with unknown parametric/nonparametric uncertainties and speed constraints. First, the nonlinear dynamic model of train operation is transformed from temporal domain into spatial domain utilizing a spatial state differentiator. Besides, the displacement-related parametric/nonparametric uncertainties are updated in the iteration axis. Furthermore, a barrier function is involved to satisfy the speed constraint, and the corresponding convergence analysis of the proposed CSAILC for automatic train control (ATC) is derived based on the spatial composite energy function. In addition, numerical simulations of train tracking control are carried out, and simulation results indicate that the proposed CSAILC achieves good effectiveness in a high-speed train (HST) control system.

INFORMATION ANALYSIS OF THE EXPERT SYSTEM OF AUTOMATIC TRAIN CONTROL

The expert system for automatic control of train traffic belongs to the class of information systems of automation and tele mechanics. The model, which reflects the informational links between the main goal and the characteristics of the automatic train control system, is informational. It can be used to conduct a qualitative analysis and synthesis of the system.

Contributions of vehicle dynamics to the energy efficient operation of road and rail vehicles

This review addresses efforts made within the field of vehicle dynamics to contribute to the energy efficient operation of road and rail vehicles. Selected investigations of the research community to develop technology solutions to reduce energy consumption are presented. The study explores the impact and potential of relatively mature technologies such as regenerative braking, but also recent research directions that are seeking to develop solutions such as regenerative suspensions, a concept common to both transport modes. Specifically for road vehicles, the study includes rear wheel steering, camber control and torque vectoring, and for rail vehicles active steering and light-weighting. Operationally, there would appear to be great potential for rail vehicles in the wider adoption of connected driver advisory systems, and automatic train control systems, including the application of machine learning techniques to optimise train speed trajectories across a route. Similarly, for road vehicles, predictive and cooperative eco-driving strategies show potential for significant energy savings for connected autonomous vehicles.

Safe Operations at Roadway Junctions - Design Principles from Automated Guideway Transit

<div class="section abstract"><div class="htmlview paragraph">This paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone “interlocking” at each junction location deconflicts railway traffic, affirming safe passage. The analogous AV protection safety subsystem is defined as fail-safe equipment that monitors roadway intersections and junctions, communicates traffic signal status, perceives and communicates alerts and signals to AV connected vehicles concerning potential unsafe conditions, and performs related primary safety functions. Conclusions are drawn that the AV protection roadway intersection functions must be performed by local roadside equipment dedicated to protecting each roadway intersection and junction. Further, it is concluded that the communications technology connecting the infrastructure with the vehicle to perform this vital, fail-safe protection should meet specific functional and performance criteria.</div></div>

Application of OFDM transmission method for railway signalling system via track circuit

At present, railway signalling systems in which control information is transmitted via track circuits (rails) have been deployed in many applications, such as automatic train control (ATC) systems in Japan. In these systems, it is difficult to increase the transmission speed due to the transmission characteristics of rails. To overcome this problem, we have proposed a new transmission method using orthogonal frequency division multiplexing (OFDM) and evaluated a configuration in which data judgment using majority decision was applied for improving the bit error rate (BER) characteristics. In this paper, we describe an FPGA implementation of our proposed method and the performance of the implemented devices.

An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks

Railways are a well-recognized sustainable transportation mode that helps to satisfy the continuously growing mobility demand. However, the management of railway traffic in large-scale networks is a challenging task, especially when both a major disruption and various disturbances occur simultaneously. We propose an automatic rescheduling algorithm for real-time control of railway traffic that aims at minimizing the delays induced by the disruption and disturbances, as well as the resulting cancellations of train runs and turn-backs (or short-turns) and shuntings of trains in stations. The real-time control is based on the Model Predictive Control (MPC) scheme where the rescheduling problem is solved by mixed integer linear programming using macroscopic and mesoscopic models. The proposed resolution algorithm combines a distributed optimization method and bi-level heuristics to provide feasible control actions for the whole network in short computation time, without neglecting physical limitations nor operations at disrupted stations. A realistic simulation test is performed on the complete Dutch railway network. The results highlight the effectiveness of the method in properly minimizing the delays and rapidly providing feasible feedback control actions for the whole network. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article aims at contributing to the enhancement of the core functionalities of Automatic Train Control (ATC) systems and, in particular, of the Automatic Train Supervision (ATS) module, which is included in ATC systems. In general, the ATS module allows to automate the train traffic supervision and consequently the rescheduling of the railway traffic in case of unexpected events. However, the implementation of an efficient rescheduling technique that automatically and rapidly provides the control actions necessary to restore the railway traffic operations to the nominal schedule is still an open issue. Most literature contributions fail in providing rescheduling methods that successfully determine high-quality solutions in less than one minute and include real-time information regarding the large-scale railway system state. This research proposes a semi-heuristic control algorithm based on MPC that, on the one hand, overcomes the limitations of manual rescheduling (i.e., suboptimal, stressful, and delayed decisions) and, on the other hand, offers the advantages of online and closed-loop control of railway traffic based on continuous monitoring of the traffic state to rapidly restore railway traffic operations to the nominal schedule. The semi-heuristic procedure permits to significantly reduce the computation time necessary to solve the rescheduling problem compared with an exact procedure; moreover, the use of a distributed optimization approach permits the application of the algorithm to large instances of the rescheduling problem, and the inclusion of both the traffic and rolling stock constraints related to the disrupted area. The method is tested on a realistic simulation environment, thus still requires further refinements for the integration into a real ATS system. Further developments will also consider the occurrence of various simultaneous disruptions in the network.

Розвиток залізничних цифрових систем та технологій у контексті інженерії 4.0

. The article deals with the problems of the further development of information management systems and information computer - integrated technologies using the “Industry 4.0” approaches and tools - cloud computing, artificial intelligence, machine learning. The most acute unresolved issues in their development are identified, one of which is the practical absence of a dialogue mode of the system with an operator. Considered the feasibility of using cloud services, where the computer is an ordinary terminal connected to the network and is a cloud. Analyzed the deployment model of cloud computing and offered the most profitable options for their use, taking into account the available resources of JSC Ukrzaliznytsya. The use of such an approach and the introduction of a digital signature creates the possibility of actually excluding a person from the information exchange as a person performing the transfer and processing of information. The modes of operation of automated train control systems are considered taking into account normal operation and operation in the case of authorized and unauthorized interference with their operation. The interrelation of the process of operating the system by operating personnel with the quality of technological maintenance and repair has been established. A model has been developed for making decisions about the performance of the system and the possibility of its safe operation based on a comparison of the above factors. Using the proposed model allows you to create information - control systems with the ability to analyze your own performance indicators and actions of operational and technical personnel and on the basis of this to adjust your own functioning algorithm.

Reliability Analysis of Next-Generation CBTC Data Communication Systems

Communication-based train control (CBTC) systems are automated train control systems using wireless communications. The normal operation of CBTC systems depends on a reliable data communication system. The existing CBTC data communication system are based on train-to-ground communication, which suffers from too many subsystem interfaces and makes ground equipment extremely complicated. In next-generation CBTC systems, train-to-train communication is adopted with the advantages of higher efficiency and briefer system structure. Although train-to-train communication based CBTC systems has been implemented in urban rail systems. The data communication system reliability has not been studied before. In this paper, the next generation CBTC data communication system reliability is modeled with Deterministic and stochastic Petri nets (DSPNs). We design a next generation CBTC data communication system using LTE technologies, and set up laboratory test environment to test system performance. The performance data is converted as DSPN model parameters to evaluate system reliability. With the tested system performance measures, we evaluate the reliability of data communication scenarios, which includes the reconnection and handoff scenarios. Extensive simulation results are then given to illustrate the system reliability, which considers both the train to train communication link and train to ground communication link.

Technical and organizational and legal conditions relating to the power supply of a railway vehicle equipped with automatic train control system

Technical and organizational and legal conditions relating to the power supply of a railway vehicle equipped with automatic train control system

Impact of Train Drivers’ Cognitive Responses on Rail Accidents

Despite the innovations in automatic train control (ATC) systems to reduce the risk of driver error, many rail accidents still occur due to defects in these systems, emphasizing the essential role of the driver in preventing rail accidents and proper control of the train. This paper studies the influence of drivers’ cognitive performance, including attention and visual perception, on the occurrence of rail accidents. The research is conducted using so-called Ex-Post facto method on a random sample of 56 train drivers with a minimum of three years of experience. The research instruments included drivers’ cognition test system including WAFV (perception and attention function) sustained attention test, COG (cognitrone) selective attention test, LVT (visual pursuit) visual perception test, demographic questionnaire, and drivers’ safety history. Results of this research showed that there is no significant relationship between age and education level of train drivers, and rate of occurrence of rail accidents. A comparison on train drivers’ cognitive characteristics, between drivers with accident record(s) and those without, showed that the drivers who had experienced rail accident(s) had lower levels of sustained attention. However, no significant difference was found between the two groups in selective attention and visual perception. Investigating the association of drivers’ ages with their levels of sustained attention, the drivers with high levels of sustained attention were found to be significantly older than other drivers. According to practical implications of these findings, cognitive rehabilitation courses are recommended for train drivers to attenuate the risk of rail accidents.

Characteristics of event recorders in Automatic Train Control systems

The development of railway transport in the current times is very noticeable, it is connected with the growing needs of movement as well as the development of information engineering. The increase in the demand for transport requires the implementation of solutions that increase the efficiency of the transport system. Both long-distance, agglomeration and metro railways can use different systems due to their specificity. Nevertheless, there is a noticeable trend in the development of systems supporting or even replacing the driver by the automation of selected activities. Such systems allow to reduce trains headway and thus increase the capacity of the line. CBTC class systems (Communications-based train control) belong to automatic train systems and are based on wireless transmission. The main purpose of using such systems is to increase the frequency of running trains while maintaining the level of safety. Computers that are on the system equipment record, process and analyse very large amounts of data. An essential element of such systems are recording units. The parameter recorders can be divided into technical and legal ones. However, for CBTC class systems, there is no obligation or requirement to use legal recorders as it is in the case of ETCS. However, it is necessary to use event recorders, and these are subject to the requirements set out in the PN-EN 62625-1: 2014 standard. The recorders are a very important component of safety systems, which is why they were analysed in this article. Both the driver, the vehicle and the infrastructure should be subject of continuous monitoring. The occurrence of an adverse event (not necessarily leading to an incident or accident) should be analysed and used to improve safety procedures. Currently, automatic systems are still developing and we are not able to accurately assess what the causes and effects of certain events may be, which is why data collection and analysis is particularly important. The article presents the general specification of the CBTC system. The parameters and properties of driving recorders should be presented. This article is co-financed by the European Union POIR.01.01.01-00-0276/17

A design strategy for obtaining reliable controllers for critical mechanical systems

The development of reliable controllers can be a complex task, mainly because there is no well-established systematic methodology developed specifically for this purpose, considering all range, from requirements analysis till code implementation in real controller and considering real-time implementation issues. This paper introduces a design strategy as a proposal for obtaining reliable controllers for critical mechanical systems, which is based on the integrated application of four analysis techniques usually used in dependable systems development: modeling, simulation, formal verification and conformance testing. The paper demonstrates, by means of a case study, that the adequate integrated implementation of such techniques results in a systematic concurrent approach for the development of reliable automatic control systems. The case study consists of a detailed application of the proposed approach in the synthesis of the automatic train control (ATC) system of an automated people mover (APM) operating in accordance within the concept of communication-based systems (CBTC - Communication-Based Train Control). This case study is used to illustrate the method, presenting and discussing the steps necessary to implement the proposed design strategy in the development of a typical piece of control software for critical mechanical systems.

ВОЛОКОННО-ОПТИЧЕСКИЕ ТЕХНОЛОГИИ В СИСТЕМАХ УПРАВЛЕНИЯ ДВИЖЕНИЕМ ПОЕЗДОВ И КОНТРОЛЯ СОСТОЯНИЯ ОБЪЕКТОВ ИНФРАСТРУКТУРЫ

ВОЛОКОННО-ОПТИЧЕСКИЕ ТЕХНОЛОГИИ В СИСТЕМАХ УПРАВЛЕНИЯ ДВИЖЕНИЕМ ПОЕЗДОВ И КОНТРОЛЯ СОСТОЯНИЯ ОБЪЕКТОВ ИНФРАСТРУКТУРЫ