Design and modeling of communications system for interoperable positive train control

The US rail industry is charged with developing and implementing interoperable Positive Train Control (PTC) on many lines by 2015. It will be a challenge to assure the overall design safety of this next generation of train control, and there are significant issues with accommodating varying operating methods and different territories. The Federal Railroad Administration (FRA) will also require the railroads to meet the processor-based train control standards in FRA Rule 49CFR236 Sub-Part H (hereinafter FRA Rule 236H) [1], including the requirement for a comparative risk assessment, preferably quantitative. This paper provides an overview of the safety assurance process mandated by the FRA and discusses a cost-effective approach to performing risk assessments on large PTC systems. The paper also recognizes the current FRA and Railroad Safety Advisory Committee (RSAC) effort in developing the new PTC-specific FRA Rule 49CFR236 Sub-Part I to meet the recent PTC legislation requirements. The FRA Rule 236H requires railroads to use a comprehensive approach to generating a risk based, safety case for all PTC-type systems. Following the FRA Rule 236H guidelines helps ensure that all aspects of system safety are addressed, and that a safety conclusion can be successfully drawn from the documented evidence. The FRA requirements for building a safety case are based on time-tested traditional safety analyses which are enhanced to address system-wide safety. A critical new requirement of this standard is the development of a quantitative comparative risk assessment for the system as the formal mechanism for summarizing the safety argument. The FRA Rule 236H requires the comparison of the risk of the new PTC system with the historical risk of the existing system, which will be extremely challenging for the nationwide implementation of interoperable PTC where differing operating methods may be employed on multiple railroads with differing levels of appropriate historical data to reference. These factors must be carefully considered in the risk assessment approach and in the formulation of the overall system safety case argument for this Federally-mandated implementation. The risk assessment process described in this paper is uniquely different from existing quantitative safety assessment approaches that have primarily concentrated on producing a Mean Time Between Hazardous Events (MTBHE) for the various train control components in the system. In contrast to an MTBHE method, FRA rule-compliant comparative risk assessment approaches must evaluate PTC safety in the context of the overall comprehensive system operation, considering the effects of human errors, operating rules/procedures, training practices, system maintenance, equipment failures including any time/sequence dependencies, and the movement of trains and their exposure to potentially hazardous conditions. These considerations have prompted the development of a comprehensive FRA Rule 236H-compliant risk assessment methodology that goes far beyond traditional safety analyses and is well-suited for the assessment of interoperable PTC systems.

This paper presents an overview of recent and current positive train control (PTC) initiatives in North America, addressing the technologies deployed, along with concerns from economic, safety, user acceptability, and regulatory perspectives. The seemingly slow progress in utilization and acceptance of PTC systems in the North American rail environment is explained in light of both technological and institutional barriers. The role of standards-making bodies and the impact of regulatory agencies cannot be overstated. Focusing on current PTC initiatives, this treatise explores the changing perspectives of the participants in these ventures: the suppliers, end users, industry organizations, and the regulatory bodies. With a growing interest in high-speed rail transportation, the upgrading of existing right of way infrastructure is the most cost-effective means of achieving this goal. Resulting in commingled freight and passenger service, it is imperative that the safety concerns of both operating entities are adequately addressed. Equally as important is the ramification of higher speed trains approaching and traversing at-grade highway crossings. The railroad/highway interface will become increasingly complex as the requirements and expectations of a national intelligent transportation system (ITS) evolves. ITS, which has been driven from a highway-centric viewpoint, must now contend with the railroad's historic superiority and reach a consensus over functional jurisdiction. Finally, migration strategies, encompassing the technological barriers along with economic and institutional hurdles that must be crossed, interoperability standards, and cost benefit analyses, that will ultimately yield successful PTC systems, are summarized.

The year 2015 will be a landmark year in locomotive technology in the United States. Effective January 1st of that year, newly-manufactured U.S. line-haul and switch service (freight-and-passenger) locomotives must be manufactured to meet the fifth level of U.S. Environmental Protection Agency (EPA) emissions regulations since 2000. Achieving those emission levels will require aftertreatment technology in some form. Also effective December 31st of that year, U.S. railroads will be required to have in operation (on much of the rail network)1 a federally-mandated Positive Train Control (PTC) technology for collision avoidance. Class I U.S. freight railroads2 by the end of 2015 will have invested an estimated $5.8 billion in PTC technology, with a major emphasis on interoperability of PTC-equipped locomotives between different railroads. An estimated 17,000 locomotives will be retrofitted or equipped with PTC by the end of 2015 and most if not all newly-manufactured locomotives will be PTC equipped after 2015. For perspective, the U.S. freight railroad investment in PTC is roughly what the Class I railroads have spent the past 4–5 years combined on capital expenditures related to infrastructure expansion. This convergence of two new complex locomotive technologies in 2015 will create a large challenge, especially in locomotive maintainability, for freight railroads. Locomotive builders and aftertreatment suppliers must work together to provide Tier 4 locomotives with minimal impact on railroad operations. U.S. diesel locomotives share a common internal combustion engine technology with most Class 8 over-the-road diesel trucks, but the railroad and locomotive environment is very different from the highway truck environment, and a “cookie cutter” approach to replicating diesel truck aftertreatment on locomotives should be avoided. New EPA Tier 4 diesel locomotives should not be viewed as “Tier 2 or Tier 3 locomotives with truck-type exhaust aftertreatment added”. Baseline reliability of current locomotive designs must also be improved to compensate for the added complexities of both exhaust aftertreatment and PTC. This paper is focused toward educating (1) aftertreatment technology manufacturers and system integrators and (2) locomotive design engineers. The emphasis is on assisting them in understanding the operating and maintenance expectations for Tier 4 aftertreatment-equipped line-haul locomotives, from the perspective of a major freight railroad.

Positive Train Control (PTC) for railway safety in the United States: Policy developments and critical issues

Positive train control (PTC) technology refers to a system of functional requirements for the monitoring and control of train movements to provide increased safety. Once implemented, PTC serves as a set of redundant controls that help ensure safety of its operations and would be systematically activated in the event of operator failure. In response to concerns regarding the safety of commuters, pedestrians, railway workers, and the general public, legislation was passed in 2008 requiring the implementation of PTC technologies for all Class 1 railways across the USA by a deadline of December 31, 2015. The following paper provides background on the topic of train safety, an overview of PTC technologies, as well as the applicable regulation and governance of implementation efforts. This report also discusses the operations management aspects of the design, implementation and ongoing operation of PTC technologies, as well as an update on the current status of implementation activities.

The purpose of this analysis was to quantify the business benefits of Positive Train Control (PTC) for the Class I freight railroad industry. This report does not address the safety benefits of PTC. These were previously quantified by the Rail Safety Advisory Committee (RSAC), which identified nearly a thousand "PPAs" (PTC-preventable accidents) on U.S. railroads over a 12-year period, and determined the savings to be realized from each avoided accident. The RSAC finding was that avoidance of these PPAs was not, by itself, sufficient (from a strictly economic point of view) to justify an investment in PTC. Examples of potential business benefits include: * Line capacity enhancement * Improved service reliability * Faster over-the-road running times * More efficient use of cars and locomotives (made possible by real-time location information) * Reduction in locomotive failures (due to availability of real-time diagnostics) * Larger "windows" (periods during which no trains operate and maintenance workers can safely occupy the track) for track maintenance (made possible by real-time location information) * Fuel savings This paper presents the results of the analysis. It is important to recognize, however, that the state of the art in making these estimates is not sufficiently mature to make exact answers feasible. Presented here are the best estimates now possible, with observations as to how better information may be developed. Benefits were estimated in the above areas and the cost of deploying PTC on the Class I network (99,000 route miles and 20,000 locomotives) were calculated. The conclusions of the analysis were as follows: * Deployment of PTC on the Class I railroad network (99,000 route miles, 20,000 locomotives) would cost between $2.3 billion and $4.4 billion over five years * Annual benefits, once the system was fully implemented, were estimated at $2.2 billion to $3.8 billion * Internal rate of return was estimated (depending on timing and cost) to be between 44% and 160%

Safety as the key quality property among RAMS (reliability, availability, maintainability, and safety) demonstrates the most stringent performance in correspondence with the safety requirements and performance standards like EN 50126. Meanwhile, GNSS (Global Navigation Satellite Systems) are penetrating the railway now widely in non-safety related applications as passenger information, fleet management, etc. GNSS also have great potential for safety-related applications in railway such as the train location determination function, which the safety performance needs to be assured through hazard analysis and risk assessment process. The train location determination by satellite-based localization system is elevating the train control to the next level. The European Train Control System (ETCS) has being trying to implementing Level 3, the Chinese Train Control System (CTCS) has been implementing CTCS Level 3 low cost especially for secondary lines, and the U.S. is implementing train control systems under Positive Train Control (PTC) requirements. The train control system needs GNSS to provide more accurate location information of trains, more flexible and condensed trains on tracks with the consistency of still keeping the current safety level or even improve safety. Some researchers are trying to understand the performance of GNSS (GPS / EGNOS / Beidou) for railway applications from the fundamental accuracy level. A satellite-based train localization unit (SaLuT) as the entity to perform the train location determination function is to bring the GNSS accuracy evaluation up to safety integrity according to the safety requirements and standards for risk assessment. One of the key consequential result derived from the train location is the adequate safety margin. The safety margin, which can also be called as “safe braking distance”, is a margin indicated to rail traffic that would allow the train to stop with the application of normal service braking. The safety margin estimation quality and the risk of the safety margin shows the hazard rate for the safety margin estimation function performed by the designed localization unit SaLuT. This paper discusses the safety margin estimation method considering both GNSS accuracy and integrity assessment aspects of SaLuT, in accordance of the settled safety requirements of location determination function. To analyze the hazard of the safety margin estimation, a formal method is applied to model the SaLuT behavior and functions. The formal method based on stochastic Petri net enables the modeling process to include the GNSS receiver collected real data on the test track into it. The safety margin estimation method together with the risk assessment method using the real data can generate quantitative indicators to represent the localization function and safety margin estimation quality. The data used for the analysis is collected in the Qinghai-Tibet railway line from Golmud station to Ganlong station by SaLuT installed on a locomotive along the track. With the stochastic Petri net model and the systematic equation using the real collected data to estimate the safety margin based on the GNSS technologies, the SaLuT can be validated and verified for its hazard rates, which provides information for the safety cases in order to meet the industrial normative requirements.

Modeling Risk for Positive Train Control (PTC) Systems

The Australian Rail Track Corporation (ARTC) is developing its advanced train management system to provide positive train control (PTC) for Australia. Lockheed Martin is currently applying advanced technologies and proven systems development techniques to develop a PTC system for the ARTC known as the advanced train management system (ATMS). The ATMS is designed to meet current and future needs of the ARTC by supporting ARTC's objectives of improving train service availability and transit times while enhancing rail safety and system reliability. The ATMS will obviate the need for ARTC to replace its aging conventional signaling systems infrastructure throughout much of its national rail network.

Demands for very reliable and robust communications systems are becoming commonplace, and this is true for air-to-ground (AG) systems, which are seeing increased usage, particularly for unmanned aircraft. Available spectrum exists for AG communications systems in the L-band (960–1164 MHz). Two robust L-Band Digital Aeronautical Communication Systems (L-DACS) were recently defined, LDACS1 and LDACS2. The L-DACS1 scheme employs a fairly broadband (0.5 MHz) transmission using Cyclic-Prefix Orthogonal Frequency-Division Multiplexing (CP-OFDM) together with adaptive coding and modulation. In this paper we propose a new AG communication system based on OFDM-OQAM filter bank modulation, using features similar to those of the L-DACS1 physical layer, and show how better subcarrier filtering can improve spectrum efficiency in AG channels. Channel estimation (CE) in OFDM-OQAM systems must employ a pilot method completely different from classical pilot-based CP-OFDM systems, since in OFDM-OQAM the pilots should remove pilot subcarrier interference from neighboring subcarriers. We employ a low complexity pilot-based CE on the OFDM-OQAM signal, and show BER results for L-DACS1 and for comparable OFDM-OQAM based systems in an example AG channel. The AG channel we employ is one based upon a recent extensive measurement campaign. We also estimate channel throughput and mean square error (MSE) for these two systems, and show that for similar BER performance, both channel estimation and throughput of the new system are better than that for L-DACS1.

State-of-the-art rail systems require reliant, redundant and critical and secure communications. Data integrity is paramount when considering the criticality that the data payload remains secure for 24/7 year-round applications. With technologies such as Communications Based Train Control (CBTC) and Positive Train Control (PTC) being implemented, considerations for data integrity in these networks must include methods to avoid internal and external vulnerabilities. Unlike traditional encryption methodologies, newer techniques involve tunneling payloads across open or closed networks; this method could include public unsecured networks. By utilizing a unique security appliance tunneled to a remotely connected network operations center, it is possible for a rail system to subscribe to a service to obtain military-grade data security capabilities and distribute secured communications throughout their operational territories via low cost data networks. This “security as a service” concept is especially useful for landlord/tenant relationships that would have previously resulted in duplicative system elements. Security-as-a-service encryption methods commercially available for rail applications typically fall into one of three color-coded categories; green, red and gray. Green networks offer a single layer solution using NSA-approved cryptographic algorithms and are completely isolated from other methods. Red networks are highly secure, utilizing diverse layers of different algorithm types. Gray networks provide a secure gateway between red and green networks to effectively manage network and operational risks. In the case of large freight territories, security as a service can help reduce network costs while improving security. For passenger rail systems, communication-based signaling systems should be strongly protected against data vulnerabilities resulting from either unintentional or malicious access to critical networks.

Recent breakthroughs in deep-learning (DL) approaches have resulted in the dynamic generation of trace links that are far more accurate than was previously possible. However, DL-generated links lack clear explanations, and therefore non-experts in the domain can find it difficult to understand the underlying semantics of the link, making it hard for them to evaluate the link's correctness or suitability for a specific software engineering task. In this paper we present a novel NLP pipeline for generating and visualizing trace link explanations. Our approach identifies domain-specific concepts, retrieves a corpus of concept-related sentences, mines concept definitions and usage examples, and identifies relations between cross-artifact concepts in order to explain the links. It applies a post-processing step to prioritize the most likely acronyms and definitions and to eliminate non-relevant ones. We evaluate our approach using project artifacts from three different domains of interstellar telescopes, positive train control, and electronic health-care systems, and then report coverage, correctness, and potential utility of the generated definitions. We design and utilize an explanation interface which leverages concept definitions and relations to visualize and explain trace link rationales, and we report results from a user study that was conducted to evaluate the effectiveness of the explanation interface. Results show that the explanations presented in the interface helped non-experts to understand the underlying semantics of a trace link and improved their ability to vet the correctness of the link.

Current train signaling systems are being replaced by advanced systems like Communications‐Based Train Control, European Rail Traffic Management System, and Positive Train Control, which rely on radio networks. However, railways operating in dense forest environments face unique challenges for wireless systems due to high levels of signal attenuation, reflection, and diffraction caused by dense vegetation. The lack of comprehensive real‐world data makes it difficult to design systems in such areas. This study presents measurements performed at 460 MHz in a dense forest environment and compares the results with predictions from two models, irregular terrain model and ITU‐R (International Telecommunication Union) P.1812, with and without adjustments for vegetation attenuation using ITU‐R P.833. Measurements were conducted in Brazil, using a transmitter antenna in a railway corridor and a mobile antenna on a moving locomotive. Our findings indicate that while predicting wireless performance in dense forests is feasible, the best model still had a mean absolute error of 7.43 dB, underscoring the challenges of accurate signal prediction in such environments.

The design of a robust downlink communication system for nanosatellites in UHF amateur radio band involves many challenges like radio spectrum constraints, time-varying Doppler, clock drifts and synchronization in a LEO satellite channel. This paper presents the system designed and implemented for IITMSAT, a student satellite project at IIT Madras, which successfully overcomes these challenges using a robust physical layer design implemented on a generic Software Defined Radio platform. The performance of the proposed design is verified through simulations as well as hardware. The communication system gives a good performance which is only about 1 dB away from theory.

This paper is concerned with the microgrid communication systems and their impact on the microgrid control system. Regardless of the control structure, a microgrid cannot exist without a communication system. An efficient and reliable communication network ensures the possibility of implementing a secure, durable and cost-effective microgrid. The configuration of the communication network depends on many factors, like the structure of the microgrid, the control objectives, the implementation costs, the maintenance costs, etc. In the case of centralized control, all relevant data from the entire system is collected and processed in a single controller. The failure of a communication link in this central controller may cause the entire microgrid to fail. Therefore, the existence of a robust and reliable communication system is vital and the creation of redundant communication links is also recommended. The situation is different in the case of decentralized control, where communication is limited to local controllers, but this leads to limited performance, therefore it is preferable for such microgrids to have at least a very basic communication system composed of simple and inexpensive communication network. In the case of distributed control, each subsystem has its own local controller (LC) with the ability to communicate with other controllers for the purpose of exchanging information. Thus, the most advantageous communication network architecture is a hybrid one that consists of a combination of centralized and decentralized control methods.