High Speed Trains (HST) face some of the most stringent requirements for ensuring passenger safety and comfort while operating at very high velocities. HST wireless communication systems therefore similarly require special considerations for network design, technology selection and system implementation. For infrastructure-based wireless communications, a handover occurs whenever a radio transitions from the coverage of the current base station to the next base station. The faster the train moves the shorter the time that it spends under coverage area before a handover is required. For HST this can be as short as 10–20 seconds. Furthermore, a HST moving at 220 mph experiences significant fast and small-scale wireless signal fading due to this velocity, but similarly may incur frequent connectivity losses due to the rapid transit across coverage areas. A route consisting of viaducts, bridges, tunnels or hilly regions drastically increases the need for rapid handovers since a large number of base stations are required to provide coverage and achieve acceptable Quality-of-Service (QoS) in such environments. Due to the relatively fixed amount of time needed to complete a handover, and the possibility of failed handovers, this reduces the usable time under coverage, and thus ensuring an optimal handover strategy selection is vital. Most of the routes span rural and suburban areas, which reinforces the need for a comprehensive network planning strategy, as these areas tend to be underdeveloped for cellular coverage. Given the complexity in available radio spectrum resources, detailed studies are required to aid in this technology selection process. However, with the predicted increase in the demand of railroad network data traffic generated by onboard sensors, onboard control and operation devices, passenger Internet services, etc., it becomes apparent that more resources are needed than are provided by current technologies such as LTE. Thus, including 5G New Radio for Railways (5G-NR2) in the consideration does not only provide railways a more cost-effective licensing option for frequencies, but also an opportunity to select the best possible radio access method for a given HST corridor. In this paper, we focus on the metrics related to handover and how they correlate with different radio access technologies for HST. Our results integrate the uncertainty of environmental factors to provide answers on technology selection driven by specific route, inter-site distances, and available bandwidth. Our wireless communication simulation results are driven by well recognized mathematical models that consider a variety of key parameters. The analysis of the handover performance will offer insights vital to future railroad network planning for multivariate radio access technologies, and to answer crucial questions about the potential for using frequency bands above 6 GHz in HST.

Designed for detecting train presence on tracks, track circuits must maintain a level of high availability for railway signaling systems. Due to the fail-safe nature of these critical devices, any failures will result in a declaration of occupancy in a section of track which restricts train movements. It is possible to automatically diagnose and, in some cases, predict the failures of track circuits by performing analytics on the track signals. In order to perform these analytics, we need to study the coded signals transmitted to and received from the track. However, these signals consist of heterogeneous pulses that are noisy for data analysis. Thus, we need techniques which will automatically group homogeneous pulses into similar groups. In this paper, we present data cleansing techniques which will cluster pulses based on digital analysis and machine learning. We report the results of our evaluation of clustering algorithms that improve the quality of analytic data. The data were captured under revenue service conditions operated by Alstom. For clustering algorithm, we used the k -means algorithm to cluster heterogeneous pulses. By tailoring the parameters for this algorithm, we can control the pulses of the cluster, allowing for further analysis of the track circuit signals in order to gain insight regarding its performance.

Real-time measurement of vertical wheel loads applied to the rail is commonly carried out using strain gauges. One standard approach involves measurement of shear strains at the rail neutral axis, and use of the differential shear concept. Strain gauges are typically mounted on the rail neutral axis between two adjacent ties (over the crib section). A set of four strain measurements (two each, pointed at 45 degrees up and down from the horizontal) are carried out at each end of the crib section, and the measured strains are used to calculate the shear strain magnitudes; this shear strain is in turn used to calculate the applied load. In practice, the four individual strain measurements on each end of the crib (on either face of the rail) are arranged in a single Wheatstone bridge circuit. The purpose for using this common strain measurement configuration lies in the circuits’ ability to eliminate crosstalk, or strain unrelated to the load being measured, e.g. bending strain, or strain due to lateral loading, etc. This paper will propose a new measurement approach whereby eliminating this Wheatstone bridge configuration and measuring eight independent strain signals will enable direct quantification of the vertical as well as lateral load magnitudes. Instead of having to install additional strain gauges on the rail base to measure the lateral loads, the same strain gauges mounted on the rail neutral axis can be used to measure both vertical as well as lateral loads. This proposed technique will simplify the process of vertical and horizontal wheel load detection, and may increase the applicability of these circuits to detect loads in curved sections of track as well as near special track work.

Cab signaling enforces the separation between trains as well as enforcing trains to reduce speed as the train approaches signals displaying STOP. Cab signaling allow for and provides a safe way to eliminate the number of wayside automatic signals while the number of controlled speeds can be increased. Light Rail Transit (LRT) systems today are built completely with cab signaling and only fixed wayside signals are placed at interlockings for routing information. Experimental cab signaling systems began in the United States in the 1920s, kicked off by the Interstate Commerce Commission (ICC) ruling that required some form of Automatic Train Control (ATC) be installed on one passenger division by 1925. This paper will begin with examining the initial ATC designs (intermediate and continuous), the first experimental installations, the testing challenges and the overall enhancements that pioneered cab signaling systems in the US. The focus will include the teaming of the Pennsylvania Railroad with Union Switch and Signal (US&S) to develop, build and successfully test the continuous cab signaling system which later became the de facto standard. The early systems implemented used two (2) speeds, methods on adding a third speed and how the system became integrated with the existing automatic block signaling. How Pennsylvania Railroad (currently Amtrak) is still using the technology that started 100 years ago on the North East Corridor. It will also introduce how Light Rail systems operate on speed commands using cab codes.

An Overload and Imbalance Load Detection (OID) system monitors rolling stock on the railroad tracks, and identifies and alarms on improperly loaded vehicles. In China, OID systems have been installed near train stations close to the railroad signals and curves. The location and condition of the track in the area of the OID system can affect the weighing performance. In recent years, the dedicated high-speed passenger lines have freed up a great deal of train capacity on the freight tracks, enabling freight train speed to increase from 60km/h to 80∼120km/h. It has become necessary to install OID systems on freight mainline between stations. The authors of this paper discuss the prospect and hurdles of two OID technologies on China railways.

Factual evidence from locomotive event data recorders (EDR), locomotive image data recorders, accident site surveys, witness marks, rail equipment, track structure, photographs, video cameras, AEI readers, hot wheel or hot bearing detectors, wayside signal bungalows, train consist documents, and radio communication is integrated, validated, and visualized in a three-dimensional model environment. The goal is to build a physics-based, data-driven model of train position as a function of time to enhance the documentation, investigation, understanding, and analysis of in-service train derailments. Methods to construct, validate, and interrogate time-accurate, interactive visualizations of train movements for partial and complete train consists are discussed and demonstrated. In-service freight train derailments that occurred in Hoxie, Arkansas (offset frontal collision between opposing freight trains), Casselton, North Dakota (unit grain train derailment with car fouling opposing mainline track and subsequent crude oil unit train head-on collision), and Graettinger, Iowa (unit ethanol train derailment) are used to illustrate the accident reconstruction method. Similar vehicle path reconstructions for recent highway, aviation, and marine investigations are also presented.

Railways have a substantial contribution to the economy of the United States. However, a train accident can result in casualties and extensive damages to infrastructure and the environment. Most of the prior research focused on derailments or grade-crossing accidents rather than the study of train collisions. The Federal Railroad Administration (FRA) identifies over 300 causes for all types of accidents, among which we aim to recognize the major factors that cause train collisions. Evaluating how collision frequency and severity vary with the accident cause is the key part of this research, in order to identify, evaluate and mitigate transportation risk. This paper presents a statistical analysis of passenger and freight train collisions in the United States from 2001 to 2015 to statistically analyze train collision frequency, severity, accident cause, and safety risk. The analysis finds that human errors and signal failures are among the most common causes of train collisions in U.S. in the 15-year study period. There is a significant decline in the overall train collision frequency by year. By observing these trends with respect to train collisions, possible accident prevention strategies could be developed and implemented accordingly.

Prevention of railroad bearing failures, which may lead to catastrophic derailments, is a central safety concern. Early detection of railway component defects, specifically bearing spalls, will improve overall system reliability by allowing proactive maintenance cycles rather than costly reactive replacement of failing components. A bearing health monitoring system will provide timely detection of flaws. However, absent a well verified model for defect propagation, detection can only be used to trigger an immediate component replacement. The development of such a model requires that the spall growth process be mapped out by accumulating associated signals generated by various size spalls. The addition of this information to an integrated health monitoring system will minimize operation disruption and maintain maximum accident prevention standards enabling timely and economical replacements of failing components. An earlier study done by the authors focused on bearing outer ring (cup) raceway defects. The developed model predicts that any cup raceway surface defect (i.e. spall) once reaching a critical size (spall area) will grow according to a linear correlation with mileage. The work presented here investigates spall growth within the inner rings (cones) of railroad bearings as a function of mileage. The data for this study were acquired from defective bearings that were run under various load and speed conditions utilizing specialized railroad bearing dynamic test rigs owned by the University Transportation Center for Railway Safety (UTCRS) at the University of Texas Rio Grande Valley (UTRGV). The experimental process is based on a testing cycle that allows continuous growth of railroad bearing defects until one of two conditions are met; either the defect is allowed to grow to a size that does not jeopardize the safe operation of the test rig, or the change in area of the spall is less than 10% of its previous size prior to the start of testing. The initial spall size is randomly distributed as it depends on the originating defect depth, size, and location on the rolling raceway. Periodic removal and disassembly of the railroad bearings was carried out for inspection and defect size measurement along with detailed documentation. Spalls were measured using optical techniques coupled with digital image analysis, as well as, with a manual coordinate measuring instrument with the resulting field of points manipulated in MatLab™. Castings were made of spalls using low-melting, zero-shrinkage bismuth-based alloys, so that a permanent record of the spall geometry and its growth history can be retained. The main result of this study is a preliminary model for spall growth, which can be coupled with bearing condition monitoring tools that will allow economical and effective scheduling of proactive maintenance cycles that aim to mitigate derailments, and reduce unnecessary train stoppages and associated costly delays on busy railways.

This paper begins with examining the fundamental nature of wayside signals and considers the first know signaling practices used to communicate the condition of the track ahead to the train engineer. The principle of wayside signals is to keep trains separated and to provide knowledge of the conditions ahead; speed and routing information. Most railways have gone through many different evolutions of signals and practices some driven by railway mergers which drove the operating rules. This consistently required changes within the training of locomotive engineers assigned operate trains within their territory. This paper will focus on a few transitions between signal types, the specific makeups and effectiveness of wayside signals since the beginning of railway signals in the early 1830s. Starting with the term “High Ball” not related to a popular drink known today, but a raising of a large ball into the air that could be seen from afar instructing a train his status to train operating schedule. Later, signals were developed to provide the train engineer the status of the track ahead by dividing the track into short sections. This allowed the track section to be labeled as “occupied” a train present or “un-occupied”, train not present within the track section. Wayside signals continued to be advanced such that today’s standards, aspects (mimicking the wayside signals) are displayed within the operating cab providing the indication directly to the engineer. As we continue forward, wayside signals have been reduced and in the future, they may be only in a museum next to the cassette player.

Crude oil and ethanol unit train derailments sometimes result in the release of large volumes of flammable liquids which ignite and endanger the safety of persons, property, and the environment. Current methods to reduce the probability and mitigate the consequences of High-Hazard Flammable Train (HHFT) derailments include operational speed constraints, enhanced tank car design/build requirements, improved car and track inspection and maintenance, and use of advanced braking systems. The train brake system can dissipate more energy in a derailment scenario if the brake signal propagation rate is increased, the brake force against the wheel tread is increased, or a combined approach is used. This paper describes a simplified energy conservation model used to determine the emergency braking stopping distance and energy dissipation benefits available for three advanced train braking systems. A 3×3 matrix of brake configurations was defined by three brake signal propagation rates and three car net braking ratio (NBR) values. The brake signal propagation rate was modeled for trains with conventional head-end locomotive power, pneumatic car braking, and no two-way end-of-train device (CONV); locomotive distributed power with pneumatic car braking (trailing DP); and locomotive power with electronically-controlled pneumatic (ECP) braking. Car NBR values of 10, 12.8, and 14 percent were selected to reflect the expected brake force range available from older equipment in the existing tank car fleet (10% NBR) to the maximum acceptable value for new or rebuilt cars (14% NBR). Various in-train emergency brake application scenarios for loaded unit trains were modeled while accounting for the gross effects of derailment/collision blockage forces. Empirical data from four trailing distributed power train derailment events were used to estimate an average derailment/collision blockage force (ADF) and simulate the trailing consist braking performance. The ADF results were subsequently used in a more general tank car unit train parametric study to evaluate the effects of train speed, track grade, and in-train derailment position for each brake configuration in the matrix. The simplified energy conservation model was used to 1) quantify the number of trailing consist cars expected to stop short of the derailment location and 2) compare the car-by-car energy state of each car in the trailing consist that was calculated to reach the derailment location. Results for the empirical and parametric study cases are compared graphically and observations are discussed relative to two assumed baseline brake configurations.

From the original “steam trumpet” built for locomotives in 1832 by the Leicester and Swannington Railway to modern air-pressure horns, train warning signals have not changed significantly in nearly 200 years. The effectiveness of train warning signals has been of particular concern for trespassers listening to music with headphones. The authors have conducted research as part of a Federal Railroad Administration program to design and assess the effectiveness of candidate new emergency warning signal (EWS) sounds. This paper summarizes a literature review to understand the needs for a new EWS sound and principles of audible signal detection. Acoustic measurements were conducted of headphones to understand in-ear music levels and active and passive sound attenuation. Candidate EWS sounds were developed with a goal of maintaining the identification of a train approaching and increasing the sense of urgency and response time for trespassers to vacate the tracks. Testing of candidate EWS sounds was conducted in an audio booth and on-board a moving locomotive. The research results have shown that a new EWS sound can maintain the association of a train approaching, increase the sense of urgency, reduce the reaction time for trespassers to vacate the tracks and improve safety on railroad corridors.

There is a growing trend for transit agencies to evolve from wayside and cab-based signal systems to Communication Based Train Control (CBTC). With the complexity of CBTC, a failure of CBTC component could bring a transit system to a standstill. Implementing a secondary signal system can serve to minimize the consequences of a CBTC failure. It is paramount for a transit system to continue to operate, and axle counter technology can be a suitable candidate for use as a secondary signal system. Axle Counter technology has not been widely used in the U.S., but has been used for many years in Europe and the rest of the world. This paper will review and analysis the following: 1. Train Detection Systems; Track circuits vs. axle counters and the basic Principles of Axle Counting; check-in and check-out. 2. Implementing Electromagnetic Compatibility and the EMI standards used in European with previous testing of various axle counter systems, and the frequencies that have been selected, and the proper usage of these frequencies. 3. Testing of radiated emissions using existing guidelines and methods to analyze existing wayside and vehicle Electromagnetic Interferences (EMI), environment conditions, and the limitations of installing axle counters in an existing rail or transit system. 4. Recommendations for improving vehicle and wayside specifications and standards within the U.S. for dealing with installation of axle counter equipment and with failures and EMI emissions between railway devices.

The University of California at San Diego (UCSD), under a Federal Railroad Administration (FRA) Office of Research and Development (R&D) grant, is developing a system for high-speed and non-contact rail defect detection. A prototype using an ultrasonic air-coupled guided wave signal generation and air-coupled signal detection, paired with a real-time statistical analysis algorithm, has been realized. This system requires a specialized filtering approach based on electrical impedance matching due to the inherently poor signal-to-noise ratio of air-coupled ultrasonic measurements in rail steel. Various aspects of the prototype have been designed with the aid of numerical analyses. In particular, simulations of ultrasonic guided wave propagation in rails have been performed using a Local Interaction Simulation Approach (LISA) algorithm. The system’s operating parameters were selected based on Receiver Operating Characteristic (ROC) curves, which provide a quantitative manner to evaluate different detection performances based on the trade-off between detection rate and false positive rate. The prototype based on this technology was tested in October 2014 at the Transportation Technology Center (TTC) in Pueblo, Colorado, and again in November 2015 after incorporating changes based on lessons learned.

This paper identifies and explores possible safety implications of RoHS (Restriction of Hazardous Substances) compliance on railway equipment, with the purpose of presenting this topic for further consideration in North American industry standards, e.g. AREMA (American Railway Engineering and Maintenance-of-Way Association) guidelines. Of specific interest is the topic of tin whiskers, which are known to grow in electric circuits that are Lead free. Tin whiskers have the ability to bridge the gap between two vital signals in a circuit, creating the possibility for a potentially hazardous scenario to occur in a safety-critical system. As rail transportation technologies become progressively more dependent on safety critical electronics that are RoHS compliant, the subject of tin whiskers merits its due consideration in the industry. There are verified incidents of tin whiskers having adverse impact in the automotive and aerospace industries; examples are provided in the paper. If precautionary measures are not respected, it is possible that a short circuit resulting from tin whiskers may lead to an undesirable incident in the rail industry also. Research has shown that there are proven techniques which can inhibit tin whisker growth to an acceptable level. Mitigating measures and their effectiveness in deterring whisker growth are discussed in this paper. Awareness is essential in prevention of a hazard. Railroads and Transit agencies that recognize hazards posed by metal whisker growth will be in a better position to evaluate the safety of RoHS compliant products provided by system integrators, who, in turn, must account for the issues presented in this paper in their internal quality processes. In due course, the safety implications of RoHS transitioning should be considered in an industry-wide guideline such as AREMA, laying the foundation for future RoHS compliant railway equipment that is safeguarded against safety concerns from tin whisker growth.

The New York City Transit (NYCT) Signal Modernization Program has been ongoing since the mid-1990s. The current phase of modernization involves the procurement of Solid State Interlocking (SSI) systems that are designed to replace relay-based interlockings. SSI procurement has necessitated significant adjustments to NYCT’s system deployment processes, most notably in the areas of design, implementation, test, maintenance, and safety certification. NYCT has successfully met the challenge of applying the updated deployment processes to multiple, concurrent system procurements. The most fundamental change to the NYCT procurement approach required a shift from the traditional design-build model of acquisition for relay-based systems to a software-based development lifecycle for SSIs. The relay-based Interlocking systems’ design-build model has traditionally involved the realization of complex relay logic with well-known hardware components such as relays, trip-stops, signals and switch machines. The SSI systems’ software model however requires additional consideration of software and hardware development phases, such as designated in the V-lifecycle. V-model phases include requirement, design, implementation, and test. For SSI systems, NYCT adopted a “double” V-Life cycle approach, one V for the supplier’s SSI hardware and software (executive) platform, and one V for the SSI application (site-specific field) logic. At NYCT, the first V is dedicated to the suppliers’ executive platform. Hardware and software comprising the supplier platform are verified to meet safety and performance requirements. Safety analyses such as Fault Tree Analysis, Failure Modes and Effects Analysis, Timing Analysis, and Hazard Analysis are generated by SSI suppliers. System Safety Concepts, e.g., Numerical Assurance, Checked Redundancy, Intrinsic Fail-Safety are also assessed. NYCT’s second V is dedicated to the application software, i.e., the site-specific relay-based logic, which is implemented as Boolean logic within the SSI. For the Booleans, the process of traditional circuit checking is supplemented by Model Checking, wherein NYCT General Safety Properties are used to verify the site-specific logic. Model Checking provides assurance that safety properties are met throughout the entire interlocking design, for every system state, and does not rely on a manual review process. This paper will focus on the benefits NYCT has realized as a result of adopting Model Checking as a requirement for safety certification, along with an overview of the NYCT SSI safety certification process.

Modern track inspection technologies contribute to more efficient and reliable identification of track conditions including track geometry and sections requiring maintenance. Records of car body motion and rail conditions are also vital for derailment or track failure investigations. Doppler LIDAR technology is a tool with a vast array of utility in measuring speed of a moving target with a high degree of accuracy and precision, and has been proven by a Virginia Tech (VT) research team to record body motion and track curvature through car body speed characteristics. In the context of track maintenance, high sensitivity to rail surface deviations and signal fidelity at high speeds make LIDAR a desirable tool for collecting information on local curvature deviations and car body dynamic responses to such irregularities. Virginia Tech’s Railway Technologies Laboratory research team has completed extensive analysis on its Doppler LIDAR system’s ability to obtain train speed and track curvature profiles in terms of the system’s accuracy and dependency on car body motion during curve navigation. Due to the LIDAR system’s capability of providing curvature data from the speed profile, it follows that the LIDAR system also serves as a high-accuracy alternative to the geometry car’s IMU which also provides curvature data. Results show the LIDAR system records curves with a high correlation with ground truth measurements. The signal processing techniques used to reveal track curve and car body motion are reviewed to show that, indeed, the LIDAR system detects car body motion in addition to the track’s curvature profile. Results strongly suggest Doppler LIDAR serves as a high-accuracy alternative to multiple rail inspection instruments and provides useful data for the improvement of rail condition localization and mapping.

In response to increasing concern about railroad grade crossing safety, the Federal Railroad Administration and Department of Transportation issued Safety Advisory 2010-02 recommending in part “...that railroads conduct comprehensive joint inspections of highway traffic signal pre-emption interconnection with State and local highway authorities...” 2010-02 also recommends recording devices at interconnected highway-rail grade crossings. This paper addresses a method to facilitate these goals by enabling the highway authority to independently verify that rail equipment is functioning properly, and just as importantly, enabling the railroad to independently verify that the highway traffic signal equipment is providing adequate clearance time in advance of the arrival of the train in the crossing. The method involves adding two circuits between the rail equipment and the traffic signal equipment: a crossing island circuit, and a start of the traffic clearance phase indicator from the traffic signal to the rail equipment. This system has been implemented at two intersections in Portland, Oregon, with plans for further implementation.

The applicability of Doppler based, Light Detection and Ranging (LIDAR) sensors for track geometry monitoring is investigated in this article. The optimum configuration of the LIDAR lenses, suitable for effective lateral track geometry measurements, is presented. In the proposed embodiment, two low-elevation LIDAR optics are employed with their beams reflected off of the rail gage face on each side to capture speed signals from both rails individually. A processing technique is developed based on the frequency bandwidth dissimilarities between the vehicle speed and track geometry irregularity to separate the two from each other. LIDAR system is body-mounted to a geometry inspection car and tests are carried out on revenue service track. The results indicate that LIDAR optics can provide a reliable track monitoring instrument for use over substantial track mileage in inclement weather and harsh track conditions with minimal operator supervision.

The primary purpose of this study is to develop a foot pulse electrical circuit that can be integrated into a LIDAR system used for measuring track speed and curvature. LI ght D etection A nd R anging (LIDAR) technology is used in a wide variety of applications because it is capable of reliably producing accurate and precise measurements. While application of LIDAR technology is vast, this particular study focuses on its ability to accurately measure velocity and track geometry of rail tracks. A research team at Virginia Tech (VT) has already developed, tested, and proven the capability of LIDAR technology to be used for railway applications [1,2]. Their analysis shows that a railcar-mounted LIDAR system can accurately measure track geometry, centerline velocity, car body dynamics, and several other useful parameters. While this system is reliable and multifunctional, the prototype used for testing is not easily upgraded to include additional features without augmenting the software currently used to analyze and record the LIDAR signal. However, the prototype LIDAR system lacks several capabilities that are desirable for integrating the system with typical commercial systems on trains. One signal that commercial train systems typically have, which the LIDAR prototype does not have, is a foot pulse. The foot pulse is usually generated by a tachometer on the wheel of the train and aims to send out a pulse every time the train has travelled a foot. This signal is used for multiple other systems on the train, so in order to simplify integration of the developed LIDAR prototype into commercial train systems, the prototype was upgraded to include additional features. Other than the foot pulse, the upgrade also included acceleration detection, direction indication, and laser-enable signals to have a more complete prototype. The upgrade was executed using an external microcontroller and accelerometer to provide proof of concept while leaving the current LIDAR prototype’s software (and already proven capabilities) untouched. This paper focuses on using the information generated by the current LIDAR system to implement the additional features in an inexpensive, reliable, and easily retrofittable manner.

The paper provides a description of the analysis of a Light Railway System for two configurations: - Rails above the ground and catenary supply - Track in a tunnel and power rail supply. Finite Element Method (FEM) analysis is compared to classical analytical approaches by Carson, Pollaczek, Bickford and Tylavsky. Reviews of methods to determine self and mutual impedance for electrified railroads are provided. The solution of finite element method (FEM) applied for the determination of impedance for the two traction rail and catenary configuration, modeled and examined, consists of computational analysis based upon minimizing the energy of electromagnetic field. The analytic impedance models are built on Carson-Pollaczek–Bickford equations, adjusted by Tylavsky, for two situations: when the ground is perfectly insulated and when considering the earth return current. The railway track – catenary is integrated in a system containing the model for traction substation(s) with DC power output and moving vehicle with induction motors, controlled using voltage inverters with pulse width modulation. The light transit train, supplied with a rectified DC power, is subjected to a significant harmonic content, which may affect the signal and control circuits. It is then shown that the power and signaling characteristics of the modelled system can predict the magnitude of the perturbation current for different frequencies, in normal operating conditions and in presence of faults as well. In many of the light transportation systems, from all types of faults, the DC short-circuit at the output of the power rectifiers used for energizing the power rail and/or catenary presents a special interest. This is because of two main reasons: the positions of the vehicle-loads are in continuous changing and, even if they operate from DC sources, the parent network is still of AC type. A key issue was the determination of the distributed parameters (resistances, inductances) of the running track and catenary, from experimental data and preliminary analytical and numerical calculations, followed by the analysis of their dependencies with the current magnitude and frequency response. A specific short-circuit study case is simulated when using a model of the traction system for the purpose of the DC fault current prediction. The paper concludes with a discussion of future developments and further work.