Communication Based Train Control System Research Articles

Developing CBTC System Safety Requirement Hierarchy through STPA Methodology

Safety-critical systems, such as the railway signal system, are subject to potentially high costs from failures, including loss of life and property damage. The use of new technology, including communication-based train control (CBTC) systems with software and computers, has changed the types of accidents that occur. Software-related issues and dysfunctional interactions between system components controlled by the software are increasingly the cause of incidents. Developing a “safe” safety-critical system requires accurate and complete safety requirements, which are the foundation of system development. Traditional hazard analysis techniques are insufficient for identifying the causes of accidents in modern railway signaling systems. Systems-Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to address these limitations. Building upon this foundation, a hierarchical approach to safety requirement development has been further developed. This approach combines STPA analysis with a hierarchical modeling approach to establish traceability links from safety requirements to specific architectures, refine and allocate system-level safety requirements to relevant subsystems, and abstract safety requirements at higher hierarchical levels to enable easy changes to lower-level implementations. This paper employs the aforementioned methodology within the context of the CBTC system, thereby enhancing risk management and hazard analysis, enabling early insights, and facilitating the generation of safety requirements of CBTC System.

A transfer learning-based intrusion detection system for zero-day attack in communication-based train control system

A transfer learning-based intrusion detection system for zero-day attack in communication-based train control system

Federated learning-based edge computing for automatic train operation in communication-based train control systems

Federated learning-based edge computing for automatic train operation in communication-based train control systems

Graph neural network‐based attack prediction for communication‐based train control systems

AbstractThe Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions. GNN‐AP is proposed, a framework utilising an alert log to predict potential attack targets. Firstly, GNN‐AP uses causality to eliminate confounding elements from the alert dataset and then uses an encoder‐decoder model to reconstruct an attack scenario graph. Based on the chronological characteristics of APT attacks, GNN‐AP identifies APT attack sequences from attack scenario graphs and integrates these attack sequences with communication‐based train control (CBTC) devices topology information to construct an Attack‐Target Graph. Based on the attack‐target graph, a graph neural network approach is used to identify the attack intent and transforms the attack prediction problem into a link prediction problem that predicts the connected edges of the attack and target nodes. The simulation results obtained using DARPA data show that the proposed method can improve the comparison methods by 4% of accuracy in terms of prediction. Furthermore, the method was applied to the CBTC system dataset with a prediction accuracy of 88%, demonstrating the efficacy of the proposed method for industrial control systems.

A Security Defense Method Against Eavesdroppers in the Communication-Based Train Control System

A Security Defense Method Against Eavesdroppers in the Communication-Based Train Control System

Joint Security and Resilience Control in IIoT-Based Virtual Control Train Sets Under Jamming Attacks

The virtually coupled train sets (VCTS) have been proposed to improve transportation efficiency, passenger satisfaction and operational capability for communication-based train control (CBTC) systems. Reliable and real-time trainto-train (T2T) wireless communications are quite desirable to ensure the stability of VCTS. Moreover, with the development of industrial Internet of Things (IIoT), an IIoT-based VCTS is proposed. Due to the physically exposed wireless environment, T2T wireless communications are vulnerable to jamming attacks (JAs), causing packets loss, time delay, and interference with the operation of VCTS systems. The distance between adjacent trains in the IIoT-based VCTS would be violate the minimum relative braking distance regulated by the traditional moving block (MB) principle if JAs were not mitigated. This is a severe safety events, which is intolerable for train control systems. In this study, we develop an event-triggered control (ETC) based resilience control method to mitigate the impact of JAs on the IIoT-based VCTS. A cooperative control approach, stable IIoT-based VCTS range and T2T communication cycle are jointly designed in the ETC-based model. The resilience control approach enables the communication cycle to be adjusted by sacrificing part of the system performance to ensure the safety and stability of VCTS systems when JAs occurs. Extensive simulation results demonstrate that the proposed ETC-based resilience control model can successfully defend against jamming attacks, and the transportation efficiency in urban rail transits can be significantly improved even under JAs.

Next-Hop Relay Selection for Ad Hoc Network-Assisted Train-to-Train Communications in the CBTC System

In the communication-based train control (CBTC) system, traditional modes such as LTE or WLAN in train-to-train (T2T) communication face the problem of a complex and costly deployment of base stations and ground core networks. Therefore, the multi-hop ad hoc network, which has the characteristics of being relatively flexible and cheap, is considered for CBTC. However, because of the high mobility of the train, it is likely to move out of the communication range of wayside nodes. Moreover, some wayside nodes are heavily congested, resulting in long packet queuing delays that cannot meet the transmission requirements. To solve these problems, in this paper, we investigate the next-hop relay selection problem in multi-hop ad hoc networks to minimize transmission time, enhance the network throughput, and ensure the channel quality. In addition, we propose a multiagent dueling deep Q learning (DQN) algorithm to optimize the delay and throughput of the entire link by selecting the next-hop relay node. The simulation results show that, compared with the existing routing algorithms, it has obvious improvement in the aspects of delay, throughput, and packet loss rate.

Research on Train-to-Train Communication Resource Allocation for Urban Rail Transport

As communication technology improves and urban rail communication system develops, the new CBTC (Communication-Based Train Control) system built upon train – train(T2T) communication has become the mainstream of future rail transit signaling systems. In the future train-centered CBTC system, Train-to-Ground (T2G Train-to-Ground) mode may coexists with T2T communication mode. To reduce the interference and ensure the reliable transmission of information and system security, a joint channel allocation and power control communication resource distrbution method is proposed, which firstly allocates channels to users by the Hungarian algorithm, and then make use of sparrow search algorithm to coordinates the user’s transmit power. Obtained by simulation results, this suggested strategy not only reduces interferences caused by resource sharing and satisfies the dependability of the system, but also significantly improves the throughput of the system.

A Cross-Layer Defense Method for Blockchain Empowered CBTC Systems Against Data Tampering Attacks

Due to the high integration of wireless communication and networking technologies, the communication-based train control (CBTC) systems are exposed to additional cyber-attack surfaces, allowing sophisticated attackers to combine cyber attack vectors with physical attack means to achieve malicious goals. Notably, the decentralized authentication features are missing in existing communication protocols which make the CBTC be easily compromised by data tampering attacks, and lead to serious operational accidents. With outstanding advantages in decentralized authentication, blockchain provides new effective solutions for decentralized identity authentication in CBTC. Consequently, it is critical to study the complex physical consequences of cyber breaches from a cross-layer defense perspective. In this paper, we propose a novel cross-layer defense method for cyber security in blockchain empowered CBTC against data tampering attacks. In the physical layer, the joint Kalman filter and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\chi ^{2} $ </tex-math></inline-formula> detector is proposed for the train state estimation and detection. In the cyber layer, an asymmetric encryption-based secure communication protocol with identity authentication and the blockchain-based distributed key management system with the adaptive consensus mechanism are designed for data communication security. Considering the unavailable direct observation of the CBTC cyber security states, a partially observable Markov (POMDP) decision model is constructed to derive the optimal adaptive consensus strategies for balancing cyber security and efficiency. Extensive simulation results show that the proposed blockchain empowered CBTC cross-layer defense method can effectively improve the cyber security protection capability and minimize the impact of data tampering attacks on the train operation.

A Comprehensive Resilient Control Strategy for CBTC Systems Through Train-to-Train Communications Under Malicious Attacks

In recent years, intelligent transportation systems and automatic train control technologies have been developed rapidly. The communication-based train control (CBTC) system through train-to-train communications is very important in the intelligent transportation system and it uses wireless communication links to transmit the train control commands. However, the CBTC system is sensitive to information security attacks. Therefore, a comprehensive resilient control strategy is proposed for the CBTC system under Denial of Service (DoS) attacks. As a cyber physical system, the CBTC system includes two layers. In the communication layer, a strongly robust train-to-train communication topology is proposed which adopts a bidirectional communication strategy and a three times communication protocol to achieve the goal of resisting multi-channel DoS attacks. In the physical layer, an observer-based distributed intrusion detection method is firstly proposed to detect the attack. Further, a resilient control method based on a distributed state observer of the leader train is proposed to avoid triggering the train safety protection mechanism frequently. Finally, simulation results prove that the proposed comprehensive resilient control algorithm is effective in the CBTC system.

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.

Experiment and theoretical analysis of electromagnetic interference on communication systems in multi-rails environment

Purpose Electromagnetic interference (EMI) on communication systems of unban rail transit can hardly be clarified because of complicated factors around railways. This paper aims to target this issue and extend experimental and theoretical analysis. Design/methodology/approach This paper take the Nanjing Dashengguan Bridge as an example, because it carries the most tracks in the world and bears three kinds of trains running through, providing a perfect complex environment. First, it investigates the three communication systems, terrestrial trunked radio, communications-based train control (CBTC) and passenger information system (PIS) that Nanjing Metro uses, and select appropriate devices accordingly. Second, it establishes a system level platform and conduct three tests to analyze their respective operating principles and performance difference under common electromagnetic environments. Third, it adopts theoretical formula to verify test results. Findings The experiment results and theoretical analysis mutually corroborate each other and present practical recommendations: an 8 m or more distance between two tracks will ensure no obvious EMI created by a passing train on communication systems; two certain communication systems should not share the same frequency band; interference level is more related to field strength than weathers and building materials; and CBTC DSSS waveguide mode as well as PIS LTE mode are preferred. Originality/value This research also provides a practical method of investigating EMI for other complex situations.

Joint Security and Train Control Design in Blockchain-Empowered CBTC System

The communication-based train control (CBTC) system ensures the high efficiency and orderliness of trains and is widely used in urban rail transit networks. The adoption of wireless communication and network techniques makes the CBTC systems more vulnerable to cyber attacks. Identity authentication is an effective approach to improve system security. The existing identity authentication mechanisms in CBTC adopt a centralized key management system sensitive to single-point failures. To improve system security, in this article, we deploy a blockchain in CBTC systems. The client that runs the blockchain program not only acts as blockchain nodes to provide distributed key management for the CBTC system but they also work as a relay node to authenticate the communication between train control nodes in CBTC systems. Based on the blockchain-empowered distributed security scheme, the block producer selection and onboard blockchain client handoff decision problem are studied. With the objective to minimize the impact of the key updating process on CBTC system performance and keep the system security under a reasonable level, we formulate the block producer selection and onboard blockchain client handoff decision problem using the deep reinforcement learning approach. Extensive simulation results illustrate that the proposed blockchain-empowered security scheme can significantly improve the CBTC system security, and CBTC systems need to sacrifice part performance to ensure system security.

A CPN-Based Approach for Studying Impacts of Communication Delays on Safety and Availability of Safety-Critical Distributed Networked Control Systems

With the great advances in computer science and communication technology, more and more control systems are implemented as distributed networked control systems (DNCSs). Due to the nature of the time delay of communication networks, it is of importance to investigate how communication delays affect the systems from different perspectives. Most of the literature by far focus on analyzing the impacts of time delays on the system stability or safety control with mathematical models (i.e., differential equations), which are of interest in the early phases of the system development (e.g., the conceptual phase). However, in the later phases of the system development (e.g., architecture design or system implementation), qualitative as well as quantitative safety analysis based on system models that describe the concrete structures, interactions between components, and state transitions of the underlying systems is desirable. Additionally, the availability of a control system is of interest from the perspective of operation. This article studies the impacts of communication delays on the safety and availability of DNCSs by a colored-Petri-net-based approach. To exemplify the proposed approach, a simplified communication-based train control system is presented.

Quantitative safety analysis of train control system based on statatistical model checking

With the rapid development of communication technology, the Train-centric Communication-based Train Control (TcCBTC) system adopting the train-train communication mode to reduce the transmission link of control information, will become the direction of urban rail transit field development. At present, TcCBTC system is in the stage of key technology research and prototype development. Uncertain behavior in the process of system operation may lead to operation accidents. Therefore, before the system is put into use, it must undergo strict testing and security verification to ensure the safe and efficient operation of the system. In the paper, the formal modeling and quantitative analysis of train tracking operation under moving block are carried out. Firstly, the structure of TcCBTC system and the train tracking interval control strategy under moving block conditions are analyzed. The subsystem involved in train tracking and the uncertain factors in system operation are determined. Then, based on the Stochastic Hybrid Automata (SHA), a network of SHA model of train dynamics model, communication components and on-board controller in the process of train tracking is established, which can formally describe the uncertain environment in the process of system operation. UPPAAL-SMC is used to simulate the change curve of train position and speed during tracking, it is verified that the model meets the safety requirements in static environment. Finally, taking Statistical Model Checking (SMC) as the basis of safety analysis, the probability of train collision in uncertain environment is calculated. The results show that after accurately modeling the train tracking operation control mechanism through network of SHA, the SMC method can accurately calculate the probability of train rear end collision, which proves that the method has strong feasibility and effectiveness. Formal modeling and analysis of safety-critical system is very important, which enables designers to grasp the hidden dangers of the system in the design stage and safety evaluation stage of train control system, and further provides theoretical reference for the subsequent TcCBTC system design and development, practical application and related specification improvement.

Enhancing Dependability Analysis Provisioning in CBTC Wireless Communication System With Age of Information

As a crucial part of the communication-based train control (CBTC) system, the wireless communication subsystem is responsible for transmitting safety-critical information, which directly affects the safe and efficient operation of the urban rail transit. The dependability analysis method for wireless communication in CBTC is critical and necessary to ensure the stable transmission of safety-critical information. However, most of the existing researches in CBTC lack a unified evaluation index to analyze the wireless communication dependability. In this paper, the dependability of wireless communication system in CBTC is established. To be specific, timeliness, integrity, security, and safety are used to describe the dependability of CBTC wireless communication system in our definition. The age of information (AoI) is used to quantitatively analyze the dependability in the CBTC wireless communication system. To verify the effectiveness of the proposed dependability analysis method, we quantitatively introduce the dependability of wireless communication system in CBTC with different scenarios, including packet-drop, re-transmission, handoff, and cyber-attack. Simulation results show that the designed dependability analysis method with quantized AoI can efficiently describe the dependability of CBTC wireless communication system in different scenarios.

Ultra-safe and reliable enhanced train-centric communication-based train control system

Ultra-safe and reliable enhanced train-centric communication-based train control system

Intelligent train control for cooperative train formation: A deep reinforcement learning approach

Considering the intelligent train control problem in long-term evolution for metro system, a new train-to-train communication-based train control system is proposed, where the cooperative train formation technology is introduced for realizing a more flexible train operation mode. To break the limitation of centralized train control, a pre-exploration-based two-stage deep Q-learning algorithm is adopted in the cooperative train formation, which is one of the first intelligent approaches for urban railway formation control. In addition, a comfort-considered algorithm is given, where optimization measures are taken for providing superior passenger experience. The simulation results illustrate that the optimized algorithm has a smoother jerk curve during the train control process, and the passenger comfort can be improved. Furthermore, the proposed algorithm can effectively accomplish the train control task in the multi-train tracking scenarios, and meet the control requirements of the cooperative formation system.

Robust Cooperative Control of Networked Train Platoons: A Negative-Imaginary Systems’ Perspective

By virtue of the wide implementation of communication-based train control (CBTC) systems and moving-block signaling systems, cooperative control for trains shows great potential in improving line utilization, passenger comfort, and operation flexibility. However, the operation of train platoons faces great challenges induced by model uncertainties, unpredictable resistances, and time-varying disturbances. To address these problems, consensus-based robust cooperative control schemes are presented in this article for both homogeneous and heterogeneous train platoons. Taking the physical connection between carriages into consideration, each train in the platoon is modeled as a negative-imaginary (NI) system, and the NI property is rigorously proved in this article. In the foundation of cooperative control theories of NI systems, robust strictly NI controllers considering the network topology are utilized to track a predefined motion reference. The proposed controllers are robust to both mass uncertainties and external disturbances. Moreover, the line utilization for the railway system and the ride comfort for the passengers are improved using the proposed control schemes. Numerical simulations are given to showcase the effectiveness and robustness of the proposed controllers.

A Resilience-Based Security Assessment Approach for CBTC Systems

With the rapid development of urban rail transit systems, large amounts of information technologies are applied to increase efficiency of train control systems, such as general computers, communication protocols, and operation systems. With the continuous exposure of information technology vulnerabilities, security risks are increasing, and information is easy to use by malicious attackers, which can bring huge property and economic losses. The communication-based train control (CBTC) system is the most important subsystem of urban rail transit. The CBTC system ensures safe and efficient operation of trains, so the quantitative assessment of cyber security is quite necessary. In this paper, a resilience-based assessment method is proposed to analyze the security level of CBTC systems based on indicators of both the cyber domain and the physical domain. The proposed method can demonstrate the robustness and recovery ability of CBTC systems under different security attacks. Based on the structural information entropy, the fusion of different indicators is achieved. Two typical attacking scenarios are analyzed, and the simulation results illustrate the effectiveness of the proposed assessment approach.