Automatic safety analysis of networked control system based on failure propagation model

Communication-based train control (CBTC) systems use wireless local area networks (WLANs) for train-ground transmission. Transmission delays and packet drops may cause unnecessary tractions and brakes of trains, degradation of riding comfortability, rising of energy consumption and loss of the line's capacity. In this paper, We model the system to control a group of trains in CBTC as a networked control system (NCS) with transmission delays and packet drops. We study the delays and packet drops in CBTC, analyze their effects on train's control, and propose a method to improve the performance of CBTC. Extensive simulation results are presented. We show that our proposed method has a strong tolerance for transmission delays and packet drops, and outperforms the currently adopted scheme in different channel conditions.

To obtain refined safety requirements during system architecture design stage, the traditional static fault tree analysis mothed is widely used to analyse the logical relationship between basic hazardous events leading to system hazards in railway signal system, and to identify the weak and key equipment of the system. In order to accurately characterize the dynamic behaviours of the system and improve the accuracy and credibility of analysis results, a dynamic fault tree analysis mothed of railway signal system based on failure propagation modelling was proposed. According to failure logic modelling of dynamic failure behaviours, conforming to signal system function design, component failure model was established within SimFIA platform, and fault trees of system hazards were attained by model simulation. The result of Communication-Based Train Control (CBTC) System on-board equipment case study shows that the fault tree of complex system function are generated by the dynamic fault tree analysis mothed based on Failure Propagation and Transformation Notation (FPTN) modelling, which guaranteed the safety analysis outcomes was accurate and credible.

Leaky waveguide has been adopted in communication based train control (CBTC) systems, as it can significantly enhance railway network efficiency, safety and capacity. Since CBTC systems have high requirements for the train ground communications, modeling the leaky waveguide channels is very important to design the wireless networks and evaluate the performance of CBTC systems. In the letter, we develop a finite-state Markov channel (FSMC) model for leaky waveguide channels in CBTC systems based on real field channel measurements obtained from a business operating subway line. The proposed FSMC channel model takes train locations into account to have a more accurate channel model. The overall leaky waveguide is divided into intervals, and an FSMC model is applied in each interval. The accuracy of the proposed FSMC model is illustrated by the simulation results generated from the model and the real field measurement results.

Communication-based train control (CBTC) systems are automated train control systems based on continuous and bidirectional train-ground communications. CBTC is the direction of future train control systems. Complex channel condition and frequent handoff can severely affect urban rail CBTC train-ground communication performance, and consequently affect CBTC operation efficiency. Current research regarding CBTC does not consider the impact of train-ground communications on train control performance. This paper studies the joint optimization of communication and control in CBTC systems. With the objective to minimize the optimal operation profile tracking error and energy consumption, linear quadratic cost is defined as the control performance measure. In order to ensure train operation safety, the optimization model puts constraints on train control actions related to safety. Moreover, based on the stochastic channel characteristics and the real-time train position information, handoff decision and train control policy are jointly optimized using deep reinforcement learning. Extensive simulation results based on real-field channel measurements illustrate that the proposed optimization method can significantly improve the train control performance in CBTC systems, and CBTC systems need to sacrifice part of performance to ensure system safety.

In this paper, a new approach to event-triggered H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance analysis of linear networked control systems is proposed. First, a new parametrization of event-triggering scheme is designed, in which a positive diagonal parameter matrix with n elements (corresponding to the dimension of the system under consideration) is introduced, resulting in different weights for each state component. Under this event-triggered formulation together with delay system modeling approach and a discontinuous Lyapunov functional, the criteria for H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance analysis are derived in terms of linear matrix inequalities. Finally, simulation results on a practical example are given to indicate that the proposed method has some advantages over some existing ones.

Communication based Train Control(CBTC) system, the latest train control technology, has been widely applied throughout the world, because it has a number of advantages such as improved driving headway, reduction of the maintenance cost and so on. The technical core of CBTC is to ensure the safe space between trains through the real-time train tracking. Korean Radio-based Train Control System(KRTCS) has been developed as a Korean CBTC standard since 2010. KRTCS is comprised of Automatic Train Supervision(ATS), wayside/onboard Automatic Train Protection(ATP), onboard Automatic Train Operation(ATO), Electronic Interlocking(EI) and wayside equipment such as transponder tags, precision stop maker, communication network, etc. In the paper, we present system configuration of KRTCS and design and development scheme of Automatic Train Protection(ATP) communication interface for KRTCS. Communication between each component is performed using the protocol defined in the form of variable messages. Messages are divided into periodic or non-periodic messages. This study describes onboard and wayside ATP functional design and communication message and procedure for each function.

In communication-based train control (CBTC) systems, as a train travels along a track, it changes its association from one access point (AP) to another, which is referred to as a handoff. Control parameters for handoff algorithms are often set based on desired system requirements, such as outage probability, without considering the effect of the underlying propagation characteristics of the channel on the system performance. Therefore, for typical CBTC systems, conservative safety margins are introduced in order to ensure safe operations leading to potentially sub-optimal system performance. In this paper, we propose a systematic procedure for selecting a control parameter, namely the threshold value, which determines when handoffs are triggered for received signal strength (RSS) based handoff algorithms. The proposed scheme leads to the selection of threshold values that increase the safety margin in addition to reducing the number of handoffs incurred, thereby enhancing the overall CBTC system performance. These enhancements are made possible with the integration of physics-based propagation models and network design that harnesses the propagation characteristics of the underlying wireless channels.

Although there has been substantial research in system analytics for risk assessment in traditional methods, little work has been done for safety risk prediction in communication-based train control (CBTC) system, especially intelligently predicting risk caused by the uncertainty in the system operation. Risk prediction and assessment of hazards in train control systems are vital for the safety and efficiency of urban rail transit. In this paper, we propose an intelligent hazard-risk prediction model based on a deep recurrent neural network for a new communication-mode CBTC system. First, a train-to-train communication-based train control (T2T-CBTC) system is proposed to improve the drawback of CBTC in information-exchanging mode. Then we design a risk prediction feature selection and generation method and estimate a critical function feature in the T2T-CBTC system by statistical model checking. Finally, we construct our intelligent hazard-risk prediction model based on a deep recurrent neural network using a long-short-term memory (LSTM) network. The model had excellent risk prediction classification results and performance in our experiment, even for unbalanced data set. This model consistently outperforms the deep belief network trained in Accuracy, Precision, Recall and F1-score for the hazard-risk prediction problem. Specifically, the mean accuracy is 97.2% and mean F1-score is 93.9% in overall performance of model. The improvements of our model against DBN model are 8.2% for Precision, 7% for Recall and 8% for F1-score.

A common concern with Communications Based Train Control (CBTC) systems is that the wireless subsystem (usually referred to as the data communications subsystem or DCS) is susceptible to radio frequency (RF) interference from the plethora of wireless devices (especially wireless local area networks or WLANs) that generally share the same 2.4 GHz spectrum as that used by the DCS. This concern is investigated in greater detail given the operational histories of two CBTC-equipped public transit lines: NYCT’s “L” or Canarsie Line in New York City and the Las Vegas monorail. Measurements of the RF environment in both locations showed a substantial level of activity in the 2.4 GHz band from WLANs and other devices but with no obvious adverse impact on the operational performance of either line. This paper presents RF measurements at 4 locations in New York City and 1 location in Las Vegas, discusses the relative severity of the RF noise and interference environment and explores why both CBTC systems are able to perform in the presence of in-band RF noise and interference without any obvious adverse impact.

Communication-based train control (CBTC) systems use wireless local area networks (WLANs) to transmit train status and control commands. Since WLANs are not originally designed for applications with high mobility, random transmission delays and packet drops are inevitable, which could result in unnecessary traction, brakes or even emergency brakes of trains, loss of line capacity, and passenger satisfaction. In this paper, we study the packet drops introduced by random transmission errors and handovers in CBTC systems, analyze the impact of random packet drops on the stability and performances of CBTC systems, and propose two novel schemes to improve the performances of CBTC systems. Unlike the existing works that only consider a single train and study the communication issues and train control issues separately, we model the system to control a group of trains as a networked control system (NCS) with packet drops in transmissions. Extensive field test and simulation results are presented. We show that our proposed schemes can provide less energy consumption, better riding comfortability, and higher line capacity compared with the existing scheme.

This paper describes how railway signaling systems are computerized equipment that are vital for the guarantee of the safe running of trains. Because of the computerization of railway signaling systems, the importance of a networking interface between these pieces of equipment is increasing. Thus, it is important to have a reliable and safe communication link between signaling equipment. Recently, network technologies have been applied in a real-time industrial control system, and also there are several studies applying computer network technology in vital control systems such as railway signaling systems. To deploy these computer network related studies in railway signaling systems, implementation costs, transmitted reliability, safety assurance technique and compatibility etc, are considered. The computer network protocol for railway signaling systems has an important advantage over the widely used Ethernet in terms of deterministic characteristics. This paper proposes computer network technology, especially the Ethernet, for railway signaling systems. The computer network characteristics of real-time industrial control systems and vital railway signaling systems are presented in this paper. This algorithm presented is based on switched Ethernet technology with a redundancy scheme. Also the paper demonstrates the experimental results of the proposed network algorithm.

Communication-Based Train Control (CBTC) systems use wireless communication to confirm safe train operation for train-ground transmission. CBTC consists of four subsystems, and the Data Communication System (DCS) is one of the most important parts, which plays a vital role in train-ground transmission. Many devices are exposed to the environment in DCS, trains operation in bad weather easily leads to a series of hardware failures. When DCS occurs one mistake, it will threaten the efficiency of CBTC and even the safety of passengers. Since DCS occurs failures inevitably, it is necessary to analyze and identify the mistakes more quickly and accurately. This paper proposes a GAN-Bert based edge-to-edge model to identify DCS faults. Bidirectional Encoder Representations from Transformers (BERT) extracts text features from fault diagnosis with Masked Language Model(MLM) and Next Sentence Prediction(NSP). Meanwhile, Generative Adversarial Network (GAN) is used to perform DCS fault diagnosis. At the same time, edge-to-edge collaboration contributes to training a better model. We use raw DCS logs and compare prediction results between the GAN-Bert and Bert-only models. The simulation results represent that the GAN-Bert based model presents higher accuracy.

Communication-Based Train Control (CBTC) system is a critical signal system to ensure rail transit’s safe operation. Compared with the train-ground CBTC system, the train control system based on train-to-train (T2T) communication has the advantages of fast response speed, simple structure, and low operating cost. As the core part of the train control system based on T2T communication, the reliability of the data communication system (DCS) is of great significance to ensure the train’s safe and efficient operation. According to the T2T communication system requirements, this paper adopts Long-Term Evolution-Unlicensed (LTE-U) technology to design the DCS structure and establishes the reliability model of the communication system based on Deterministic and Stochastic Petri Nets (DSPN). Based on testing the real line’s communication performance parameters, the DSPN model is simulated and solved by π -tool, and the reliability index of the system is obtained. The research results show that the LTE-U-based T2T communication system designed in this paper meets the train control system’s needs for communication transmission. This paper’s reliability evaluation method can complete the reliability modeling of train control DCS based on T2T communication. The research in this paper will provide a strong practical and theoretical basis for the design and optimization of train control DCS based on T2T communication.

The paper summarises the evolution of rail signalling system from track-circuit signalling to advanced Communication-Based Train Control (CBTC) systems, highlighting the differences, benefits and challenges with regard to improving performance while ensuring safety. It describes the evolution of such systems over the last three decades; from wayside signals to cab signals, to profile-based systems, to communications-based train control systems for an effective means of overcoming the fundamental limitations of the conventional track-circuit based system. CBTC allows trains to operate with much closer headways while ensuring safe train separation and better train control flexibility. Not only do CBTC systems determine the position of the train with a higher degree of accuracy independently of the track circuits, but also offer bidirectional train/wayside communication to enhance train operations and supervision. Operational and performance benefits realised with the newer technology systems are discussed, together with the challenges of implementing such systems. Standardisation for Communication Based Signalling System initiatives is also described and industry trends presented.

Distributed control systems are crucial for regulating manufacturing processes by controlling field devices. Delays in device operation can significantly impact the time response of the process control system, affecting overall stability. To enhance network performance and process time response, it is essential to study the inherent delays of field and network devices. This paper examines process control loops involving a 3-layered network based on the OSI model’s physical, network, and application layers. The proposed networked control system assesses time delays within and between field devices configured through these layers, which are essential for control loops, including open, closed, and cascade loops. Analyzing these time delays enables effective control loop configuration, improving the process control time response and overall stability.