Railway Wireless Communications Channel Characterization

Railway applications are in continuous evolution with the aim of offering a more efficient, sustainable, and safer transportation system for the users. Generally, these applications are constantly exchanging information between the systems onboard the train and the trackside through a wireless communication. Nowadays, Global System for Mobile communications-Railway (GSM-R) is the technology used by European Train Control System (ETCS), but it is becoming obsolete. Therefore, alternatives for this technology have to be found for the different railway applications. Its natural evolution is to move forward with the latest technology deployed: Long-Term Evolution (LTE), which the Public Land Mobile Networks (PLMN) have already deployed. Therefore, testing the performance of this communication technology in the railway environment could be useful to assess its suitability and reduce the cost of railway network dedicated deployment. In order to do that, a methodology to characterize the communication environment is proposed. The main goal is to measure geolocated impairments of any communication channel in a railway environment being able to determine its behavior of the different communication technologies and find out possible coverage issues. Moreover, it could help in the selection of suitable communication technology for railway. This paper presents a brief description of the communication for railways and its QoS parameters for performance measuring. Afterward, the testing methodology is described, and then, the communication channel measurement campaign on a real track in Spain where the railway environment is variable is presented (tunnels, rural/urban area…). Finally, the measurements and results on this real track in Spain are shown. The results provide suitability of the 4G technologies based on the delay requirements for the implementation of ETCS over it.

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.

THEORETICAL FUNDAMENTALS OF ESTIMATABILITY ASSESSMENT OF TRAIN SITUATION SIGNS FOR WORK OF INTELLECTUAL LOCOMOTIVE CONTROL SYSTEMS

The article is devoted to the problem of implementation of intelligent control systems in transport. An important task is to assess the information parameters of the control systems. In the existing works the question of definition of one of the basic parameters of functioning of locomotive control systems - information value of separate signs of a train situation is not considered. This does not make it possible to determine the order of signal processing at the input and assess their contribution to the adoption of a control decision. Moreover, informativeness is a relative value, which is expressed in the different information value of a particular feature for the classification of different train situations. Also, the informativeness of the feature may depend on the type of decisive rules in the classification procedure. The quality of recognition of a train situation in which the locomotive crew is, depends on the quality of the features used by the classification system. The decisive criterion for the informativeness of the features in the problem of pattern recognition is the magnitude of losses from errors. To determine the range of the most informative features of train situations, the method of random search with adaptation was used. The results of the work make it possible to optimize the operation of automated and intelligent train control systems by reducing the amount of calculations and simplifying their algorithm.

Multiscenario-Based Train Headway Analysis under Virtual Coupling System

Chinese high-speed railway has implemented large-scale network operation with an urgent need for capacity improvement. The concept of virtual coupling seems to be a promising solution that provides a new operational scenario for high-speed railway, where trains are formed into a cooperative convoy and run synchronously with small train headways. The train-following principles under the virtual coupling signalling are quite different from those under conventional train control systems. Therefore, train headway analysis for different operational scenarios should be carried out to ensure railway safety and evaluate capacity benefits brought by virtual coupling. This paper proposes a potential virtual coupling architecture with reference to ETCS/ERTMS specifications. We compare blocking time models under different train control systems, and eight typical train-following scenarios are investigated for virtual coupling, including train arrival and departure cases. A detailed multiscenario-based train headway analysis is provided based on the microscopic infrastructure of the station and technological characteristics of virtual coupling. All computational outcomes are based on the train dynamic motion model. A comparative analysis of train headways under virtual coupling and CTCS-3 is provided in the case study. Results show that train headways can be substantially reduced under virtual coupling and are related to the station infrastructure layout.

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.

Impact and Protection of GNSS Interference: Resilient Positioning in Next Generation Satellite-based Railway Train Control

Background: The Global Navigation Satellite System (GNSS) has great potentials in next generation railway train control systems. Considering the fail-safe characteristics of train control, the threat from GNSS interference may result in an increasing likelihood of outages of train positioning or even safety risks to the railway system. Objective: The interference protection solutions are investigated and demonstrated for achieving the resilient train positioning using GNSS. Methods: This paper describes the main types of GNSS interference and investigates the impact on Location Determination Unit (LDU) in the GNSS-based train control system. Specific architectures and solutions for interference detection and protection in both the position domain and measurement domain are presented. Results: Interference injection simulations are performed with both the GNSS spoofing and jamming signals, which evaluate the effects of interferences and demonstrate the protection performance of the presented solutions under GNSS attack scenarios. Conclusion: The interference protection solutions within both the position domain and measurement domain are effective and significant to mitigate the effects from the GNSS interference, which enables resilient train positioning to achieve the safe train operation.