Movable railroad bridges, consisting of lift, bascule, or swing bridges have been used by American rail tracks that cross usable waterways for over a century. Although custom made, movable bridges share many common components and designs. Most of them use weight bearing towers for the movable span using electric or electro-hydraulic systems lift and/or rotate these movable spans. Automated locks hold the bridge in place as soon as the movement stops. The bridge operation, train and ship signaling systems work in synchrony for trains and waterway traffic to be granted safe passage with minimal delay. This synchrony is maintained by using custom-made control systems using Programmable Logic Controllers (PLCs) or Field Programmable Gate Arrays (FPGAs). Controllers located on the movable and the static parts of the bridge communicate using radio and/or wired underwater links sometimes involving marine cables. The primary objective of this paper is to develop a framework to analyze the safety and security of the bridge operating systems and their synchronous operations with railway and waterway systems. We do so by modeling the movable physical components and their control system with the interconnected network system and determine the faults and attacks that may affect their operations. Given the prevalence of attacks against PLCs, FPGAs and controllers, we show a generic way to determine the effect of what if scenarios that may arise due to attacks combined with failures using a case study of a swing bridge.

The highest level of automation may be achieved with traditional fixed block systems with numerous benefits. Diagnostic Data can be collected from wayside infrastructure and stored in a central depository. Diagnostics from the vehicle may also be collected, not typically in a dynamic fashion, and stored in a centralized depository. This data is not easily integrated or sequenced between the onboard and wayside. External systems are added to collect all data. This centralized system composes a Maintenance and Diagnostic Center. In addition, with CBTC systems, communication between the wayside and the vehicle include ATP information, Movement Authority, Speed Restrictions from the wayside to the vehicle and reports of train location, speed, travel direction and vehicles status. With ATO, data is also transferred between the train and wayside. Much of the vehicle reported ATO data includes vehicle and on-board controller alarms and events. This train and wayside communicated data is collected and stored in the MDC with the added benefit of being integrated between the on-board and wayside. This integrated data allows data mining to be performed to evaluate many operating aspects of the system. This presentation identifies some of the types of data collected and the analysis that may be performed on the data to identify improvements that are to be integrated in system operation, detect system components that are degrading to a point of failure to help schedule maintenance before failure and provide the capability to review events post mortem to identify the root cause of failures that occur in the system.

The data communications subsystem or DCS is an important element of a CBTC system which supports the wired and wireless data communications between a CBTC equipped train and the wayside elements such as zone controllers and the automatic train supervisory (ATS) system. A “brown field” environment (as opposed to “green field” environment) represents an existing transit system that is already in revenue service and is being re-signaled with a new CBTC system. Such an environment typically represent the most challenging deployment for CBTC a system as it must be installed, tested and integrated in such a manner as to not adversely impact the transit agencies’ ongoing revenue service. Usually, one of the first elements of a CBTC system to be designed and deployed is the DCS. This paper will examine some lessons learned related to the DCS design, deployment, testing and commissioning for CBTC projects in a “brown field” environment with a view to improving future CBTC projects.

Advanced active suspension systems has attracted considerable attention in modern railway vehicle designs in recent years. The purpose of the suspension is to attenuate the vehicle vibrations due to various rail excitations. With active suspensions it is aimed to improve the performance in some cases, while not making it worse in others. The performance-related objectives can be approximately translated in different norm bounds on certain transfer functions or impulse responses. In this paper, a multi-objective problem is formulated as a non-convex and non-smooth optimization problem for a full-car railway vehicle modelled with seventeen-degrees-of-freedom (17 DOF) and excited by random rail inputs. The controller order restricted to be less than or equal to the passive system model order. For a range of orders, controllers are synthesized by using the HIFOO toolbox.

American Railroads are planning to complete implementing their Positive Train Control (PTC) systems by 2020. Safety objectives of PTC are to avoid inter-train collisions, train derailments and ensuring railroad worker safety. Under published specifications of I-ETMS (the PTC system developed by Class I freight railroads), the on-board PTC controller communicates with two networks; namely, the Signaling network and the Wayside Interface Unit network to gather navigational information such as the positions of other trains, the status of critical infrastructure (such as switches) and any hazardous conditions that may affect the train path. By design, PTC systems are predicated on having a reliable radio network operating in reserved radio spectrum, although the PTC system itself is designed to be a real-time fail safe distributed control systems. Secure Intelligent Radio for Trains (SIRT) is an intelligent radio that is customized to train operations with the aim of improving the reliability and security of the radio communication network. SIRT has two tiers. The upper tier has the Master Cognitive Engine (MCE) which communicates with other SIRT nodes to obtain signaling and wayside device information. To do so, the MCE communicates with cognitive engines at the lower tier of SIRT; namely the Cryptographic Cognitive Engine (CCE) (that provide cryptographic security and threat detection) and the Spectrum Management Cognitive Engine (SCE) (that uses spectrum monitoring, frequency hopping and adaptive modulation to ensure the reliability of the radio communication medium). We presented the architecture and the prototype development of the CCE in [1]. This paper presents the design of the MCE and the SCE. We are currently developing a prototype of the SCE and the MCE and testing the performance of our cognitive radio system under varying radio noise conditions. Our experiments show that SIRT dynamically switches modulation schemes in response to radio noise and switches channels in response to channel jamming.

Positive Train Controller (PTC) is a communication based system designed to enforce PTC safety objectives for trains such as train-to-train collisions, train derailments, and ensure railroad worker safety. Existing PTC designs consider risks due to operational environment such as location of other trains, switches, and speed limits. We propose to enhance PTC by using a multi-tiered cognitive radio network that considers multiple risks such as those due to bandwidth congestion, packet length limitations, propagation losses, detectable exploitation of Software Defined Radio vulnerabilities, and protocol vulnerabilities. Radios operating at PTC nodes (such as train, WIU and Base station) is equipped with a cognitive layer, which communicates with other nodes to create a cognitive radio network. The proposed network as a whole strives to provide spectrum management and security for the radio communication system, which can enhance the PTC functionality. Each cognitive radio in our proposed network consists of multiple tiers. The upper tier consists of a master cognitive engine that holistically evaluates the operational risks of the network and acts to mitigate them using the lower tiers. The lower tier (immediate slave tier to the master) consists of sub cognitive engines for cryptographic operations and spectrum management. The traditional PTC protocol is implemented at a lower tier module that interface with the master Cognitive Engine (CE). The master-slave communications within one radio is implemented using middleware. The proposed cognitive radio network can be modeled as a cyber-physical system by incorporating train movement dynamics, radio transmission characteristics and cryptographical computations, thereby constituting a distributed system of communicating hybrid automatons. This design enables us to verify safety and the security of the system using formal methods, which constitutes our ongoing work. We also discuss potential issues such as FRA mandated safety cases that needs to be addressed if the proposed features are to be added to the PTC systems.

Hardware-in-the-Loop (HIL) testing allows for scaled to full-scale evaluation of components without constructing full-scale vehicle prototypes. HIL is also a rapid means of performance evaluation of difficult to model components, in real-time simulation with up to full-scale components providing their own response in place of a model. HIL also provides a working tool for control algorithm refinements prior to full system integration. In hybrid and electric locomotive applications this is particularly important while choosing the battery chemistry and sizing the energy storage system. Energy storage HIL testing permits optimal sizing of battery power and energy density along with management algorithm tuning. In general, HIL provides insight into optimal locomotive powertrain design. After the development of full EV and HEV locomotive models, battery component models were replaced with real-time interfaces to lead carbon and lithium cobalt batteries, which validated the battery models and helped tune vehicle controllers for direct application onto the vehicle platform.

Often, available power from an in-vehicle energy storage system is governed by thermal limitations. Modeling of battery pack thermal response is crucial to managing its cooling system energy consumption and estimating available charge/discharge power for future locomotive tractive and regenerative effort. Active cooling through forced air flow was simulated using computer-aided design of the battery pack and its enclosure. Module scaled (series string of 54 12V batteries) testing and modeling of both air flow and temperature distribution was performed and validated for sealed lead acid carbon batteries. A controller area network and data logger collected temperature data from 218 sensors placed throughout a battery pack module during electrical loading for both switcher and over-the-road cycles while under various environmental thermal loadings. A blower on-off control algorithm was optimized to minimize energy consumption and implemented based on temperature array statistics.

The North American freight railroad network is projected to experience rising transportation demand in the coming decades, leading to increased congestion along many rail corridors. Increased interest in expanded passenger service on shared rail corridors will also create additional capacity demand. However, the nation’s rail lines are still predominantly single track with passing sidings, making double track installation a vital capacity upgrade measure to sustain future volumes. Since increasing capacity through double track installation requires significant capital investment, the second main track must be allocated along a line in an optimal manner to provide maximum return on investment. An approach of investing in the least costly segments first may yield good results, but only if the benefits for each segment are equal. This research seeks to identify if the benefit of double track varies between bottleneck segments, and if there are compounding benefits of double track between adjacent passing sidings. Previous research has explored the allocation of double track on an idealized line with evenly spaced passing sidings. Due to numerous physical and engineering constraints, existing lines often exhibit a mixture of siding spacing with single-track bottleneck sections of varying length. To investigate the incremental capacity of adding double-track segments to a route with variable siding spacing, several build-out strategies are tested on a representative subdivision under random, mixed freight and passenger traffic via Rail Traffic Controller simulation software. The presented results highlight the most effective method, based on train delay, of incremental single to double track expansion and the potential differences in benefit between strategies. The linear delay reduction characteristics of single-to-double track mainlines vary based on the initial spatial arrangement of passing sidings and amount of second main track installed. These results further the understanding of relationships between infrastructure location and freight delay, thereby serving as a guideline for the sustainable expansion of existing rail corridors in anticipation of future demands. While railroads must consider many factors in selecting capital expansion projects, these guidelines can streamline the decision process by helping to quickly identify the projects with the most potential for more detailed engineering evaluation. The methodology presented can eventually be incorporated into analyzing the progressions from double to triple track lines.

Recent railway industry campaigns have highlighted the relative average fuel efficiency of freight and passenger trains as a key benefit of the railway transportation mode. These efficiencies are anticipated to increase rail market share as rising energy costs make less efficient competing modes less attractive. However, the fuel consumption and energy efficiency of a specific passenger or freight rail system, and even individual trains, depend on many factors. Changes in these factors can have various effects on the overall fuel consumption and efficiency of the system. One of these factors is the amount of congestion and delay due to increased traffic on the line. Thus, it is possible that the additional traffic anticipated to shift to the rail mode due to its energy benefits may increase congestion and actually have a negative impact on overall network energy efficiency. Such a case would tend to dampen the future shift of traffic to the rail mode. While simple train performance calculators can evaluate the energy efficiency of a train for an ideal run, more powerful train dispatching simulation software is required to simulate the performance of trains in realistic operating scenarios on congested single-track lines. Using this software, the relative impact of congestion on efficiency can be analyzed and compared to changes in factors related to fuel consumption. In this study, several factors affecting the efficiency of both passenger and freight rail systems were selected for analysis. Rail Traffic Controller (RTC), a train dispatching software, simulated representative single-track rail subdivisions to determine the performance of specific passenger and freight trains under different combinations of factor level settings. For passenger rail, the effects of traffic volume and station spacing on fuel consumption were analyzed while the effects of traffic volume and average speed were analyzed for freight rail. Each system was analyzed on level track and on territory with grades. Preliminary results suggest that passenger trains, if given priority, maintain their efficiency until large numbers of passenger trains are present on the network, while freight trains experience degradation in energy efficiency as congestion increases. These results will be used to develop a factorial experiment to evaluate the relative sensitivity of freight and passenger rail efficiency to congestion and other system parameters. The paper concludes with a brief discussion of possible technologies to improve efficiency and offset potential losses due to future congestion.

Many railroads are installing new Communications Based Train Control (CBTC) systems and replacing their relay based signaling equipment with solid state equivalents. When installing new signaling and train control equipment on a property, laboratory Electromagnetic Compatibility (EMC) testing is an important part of the qualification process. Much of the new train control equipment is designed and manufactured overseas and Commercial Off The Shelf (COTS) equipment is frequently incorporated into subsystem designs. It is, therefore, important that the railroads and system providers understand the railroad EMC requirements, and that the equipment being installed is tested to the appropriate standards in the laboratory in order to ensure that it will operate as intended in the field. The two main equipment level laboratory qualification testing standards referenced in railway signaling contract specifications are the Military Standard MIL STD-461F and the CENELEC (European Committee For Electrotechnical Standardization) Standard EN 50121 (IEC equivalent IEC 62236). Although the two standards are similar, there are some key differences that can lead to costly delays if not properly understood and addressed. This paper will provide a comparison of these two standards, including the different test methodologies, specific test procedures, and test limits.

Reliability, Availability and Maintainability (RAM) engineering has been applied successfully for decades in many industries such as military electronics for aerospace [1] [2], nuclear power stations [3], and oil field services [4]. Several standards applying to train control have also been produced recently, for instance the IEEE recommended practice on Communication Based Train Control (CBTC) testing [5], the international standard for Reliability Availability Maintainability Safety (RAMS) in railway applications [6] and the European version [7]. Better Reliability and Availability (RA) involves a larger capital investment cost but results in lower maintenance cost and fewer system impacting delays. RAM engineering is used to define the optimal level of reliability and availability to minimize those two costs. This paper introduces CBTC technology, including typical architectures of the subsystems which need to be modeled for the RA analysis. Basic RAM definitions and methods which can be applied to any system, including train control equipment, are presented. Then, the application of RA methods on CBTC system is discussed in terms of requirements, analysis, testing and methods to choose spare parts quantity.

Model reference adaptive control (MRAC) is developed to control the electrical excitation frequency of AC traction motors under various wheel/rail adhesion conditions during dynamic braking. More accurate estimation and control of train braking distance can allow more efficient braking of rolling stock, as well as spacing trains closer together for Positive Train Control (PTC). In order to minimize the braking distance of a train, dynamic braking forces need to be maximized for varying wheel/rail adhesion. The wheel/rail adhesion coefficient plays an important role in safe train braking. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and rail, or may lead to large coupler forces, possibly causing derailment or broken components. In this study, a multibody formulation of a locomotive and three railcars is used to develop a model reference adaptive controller for adjusting the voltage excitation frequency of an AC motor such that the maximum dynamic braking is achieved, without locking up the wheels. A relationship between creep forces, creepages, and motor braking torque is established. This relationship is used to control the motor excitation frequency in order to closely follow the reference model that aims at achieving maximum allowable adhesion during dynamic braking. The results indicate that MRAC significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during dynamic braking.

Long term demand for rail transportation in North America is projected to increase considerably in the coming decades. A significant portion of the routes in the United States are single track with passing sidings. Eventually, the second mainline track will become necessary to maintain network fluidity. However, the full funding for the second track may not be available all at once; subsequently the track can be phased in over time creating a hybrid track configuration. Depending upon the traffic characteristics, traffic will transition from a delay characteristic of single track to a delay characteristic of double track. A response surface model was developed that tested various factors including the amount of second main track added, traffic volume, traffic composition, and the speed differential between train types. Design of experiments software (JMP) was used in conjunction with railway simulation software (Rail Traffic Controller) to conduct the analysis. The benefit of full double track can be realized for high priority trains with partial double-track. However, the low priority traffic may not experience double-track-like performance until nearly the entire second mainline track is installed. The results suggest a linear relationship between miles of second mainline track added and reduction in train delay. The maximum speed of the freight train has a great impact on train delays in a congested network. These results further the understandings of key mainline interactions between passenger and freight trains. In addition the models presented will facilitate the development of an optimal incremental upgrade model for capacity expansion. Also, the methodology presented can be adopted to analyze the progression from double to triple track.

North American freight railroads are expected to experience increasing capacity constraints across their networks. To help plan for this increased traffic, railroads use simulation software to analyze the benefits of capacity expansion projects. Simultaneous operation of heterogeneous traffic further increases delay relative to additional homogenous traffic. Additional passenger trains can cause more delays to freight trains than additional freight trains. Rail Traffic Controller (RTC) was used to run simulations with varying mixes of unit freight and passenger trains operating at various speeds on a double track configuration. Basic assumptions on the relative difference in priority between train types lead to drastically different results on the impact of adding higher priority trains. This assumption dictates whether the track in the opposing direction should be used for overtake maneuvers. Also, higher speed differentials between train types can result in higher delays as faster trains catch up to slower trains more quickly. These analyses will help planners improve their understanding of the tradeoff in capacity due to operation of different types of trains at different priorities and speeds.

Model Reference Adaptive Control (MRAC) is developed to control the amount of current through the traction motors under various wheel/rail adhesion conditions while braking. More accurate estimation and control of train braking distance will allow the trains to be run with closer spacing. In order to minimize the braking distance of a train, dynamic braking forces need to be maximized while maintaining good wheel/rail adhesion. Wheel/rail adhesion coefficient plays an important role in safe train braking. Excessively large dynamic braking can cause wheel lockup that can damage the wheels and the rail. In addition, it can cause large buff loads that cause derailment or coupler damage. Dynamic braking force is directly proportional to the current supplied to the traction motors. In this study, a multibody formulation of a locomotive and three railcars is used to develop a model reference adaptive controller for adjusting the current provided to the traction motors such that the maximum dynamic braking is achieved, without wheel lockup. Aerodynamic drag and air brake forces are included in the model. The coupler forces are also considered in the control model to ensure that they remain within acceptable levels. The results indicate that the MRAC system significantly improves braking distance while maintaining better wheel/rail adhesion and coupler dynamics during braking.

The Wisconsin Department of Transportation (WisDOT) contracted HNTB Corporation (HNTB) to utilize the Rail Traffic Controller™ (RTC™) computer simulation software developed by Berkeley Simulation Software to analyze the rail capacity requirements for high speed (110 mph maximum) Chicago to Milwaukee to Madison passenger rail service. The purpose of this study was to determine whether sufficient capacity exists in the corridor to accommodate the projected growth in intercity passenger rail service as well as growth in freight and commuter rail service. Where capacity constraints were identified, the model was also used to evaluate the benefits of proposed infrastructure improvements. HNTB and WisDOT worked with Illinois DOT, the Canadian Pacific Railway, Metra and Amtrak to identify and test rail improvements that will provide sufficient capacity for projected future high speed, commuter and freight rail services in the corridor. The modeling results are shown through string lines and tables comparing the impacts of each case on the performance of each type of train. Metrics used include: • Average speeds. • Delay minutes per 100 miles. • On Time Performance (for passenger trains). RTC is a very useful tool for the simulation of current and proposed rail operations. It has helped identify bottlenecks and analyze the effectiveness of proposed improvements. The model results from this study are a critical component in WisDOT’s negotiations with CP over the extent and location of capacity improvements for high speed operations. The RTC model output also supported WisDOT’s application for federal stimulus funding for the corridor improvements.

Track clearance green phases are used at railroad preempted intersections to provide time to clear the railroad tracks of highway vehicles before a train arrives. This paper describes preemption performance measures developed in Indiana that use high resolution, real-time traffic signal event data, and a gate-down confirmation circuit at an active railroad crossing. These performance measures are used to quantitatively assess the synchronization of the track clearance phase with the railroad gate position. Performance measure plots from over 4,000 preemption events over six months are presented. The lessons learned from the assessment of these performance plots are described along with changes made to the test site during the study period. The paper concludes with recommendations for incorporating a highway-railroad synchronization performance measure using the start of railroad active warning time as a surrogate gate-down confirmation circuit.

The RUNE project (Railway User Navigation Equipment) is aimed at demonstrating the use of GNSS Integrity and Safety of Life service characteristics for defining a satellite-based system to perform train location for safe railway applications. ALS-Laben is leading a consortium for the development and demonstration of the RUNE equipment, under ESA contract. The project involves both a HW-In-the-Loop laboratory set-up as well as a 3 months field-testing on-board an experimental train of the Italian train operator Trenitalia. The primary objective is to demonstrate the improvement of the train self-capability in determining its own position and velocity, with a limited or no support from the trackside, and to show that the equipment can comply with the European Railway Train Management System requirements. The RUNE technical solution is based on GNSS receivers: navigation data will come from GPS with differential EGNOS corrections (European Geostationary Navigation Overlay Service) to enable autonomous and reliable determination of train position, velocity under practically all environmental conditions. The system will offer another technological approach for the train location function: the use of GNSS signals integrated with inertial sensors and on-board odometers, in an “intelligent” system of mutual calibration, error filtering and error correction, represents a technical, industrial and operational challenge. Availability and integrity requirements are the most challenging obstacles towards an ERTMS/ETCS compliant GNSS aided railway navigation equipment. RUNE is designed to take advantage of the current EGNOS integrity and wide area differential correction service and extend its availability through an hybrid navigation system based on GPS/EGNOS, INS and Odometer data processed by a navigation EKF. The achievement of such objective would lead to the reduction of the frequency of physical balises by replacing them with virtual ones, with a significant reduction of the infrastructure costs (initial investment and recurring maintenance costs), whilst still maintaining the level of safety currently provided. This will be made possible by RUNE by producing to the onboard Train Control equipment a balise-crossing message when a virtual balise is detected. RUNE will also assist the locomotive engineer on approaching signal locations on the basis of a track map, and on controlling the train velocity on the basis of allowed velocity profiles, with resulting improvements in the safety and security of operations. In the long run, RUNE is expected to provide real time/continuous information also to the railway traffic control centre on trains position and speed. This will permit not only increased safety and security of the operations, but also possible increases in operating speeds, increases in track capacity, reductions in conventional infrastructure investments and maintenance, fuel consumption reductions, enhanced fleet management, as well as improved customer service. The RUNE equipment architecture in terms of sensors and navigation filter design were presented in previous work (see [1] and [2]). This paper will focus on safety analysis of the RUNE demonstration prototype and can be considered as the basis for the building of the safety case of future signalling systems using RUNE functions.

The Office of Research and Development of the Federal Railroad Administration (FRA) is sponsoring a revenue service demonstration of Advanced Train Systems to demonstrate new technologies for improving safety and efficiency in freight train operations. The project, which commenced in 1999, is part of the Rolling Stock Program Element in FRA’s Five-Year Strategic Plan for Railroad Research, Development and Demonstrations. The demonstration system, referred to as the On-Board Monitoring and Control System (OBMCS), features an integrated package of sensors and actuators for monitoring and controlling mechanical components on freight trains. The OBMCS includes sensors to monitor bearings, wheels, brakes and trucks and actuators (referred to as advanced components) for remotely controlling hand brakes, angle cocks, cut levers and a cushion unit lockout system to eliminate slack. The demonstration, scheduled to commence in 2005, will feature a locomotive equipped with an EMD FIRE computer system and five freight cars equipped with the OBMCS and a New York Air Brake ECP brake system. The cars will also be equipped with Sharma & Associates tri-couplers, which automatically couple the cars, the pneumatic line and the ECP brake power cable. An open system architecture based on Controller Area Network (CAN) technology provides the framework for integration and control of the advanced components. The CAN bus network is also employed to monitor bearing temperatures and the status of brake piston travel sensors. A communication protocol based on a subset of CANopen Draft Standard DS401 V2.1 [CiADS401] has been developed to facilitate integration of sensors and actuators into the OBMCS. Science Applications International Corporation and Wilcoxon Research developed the sensor and supervision platform to integrate the advanced components. The OBMCS is powered by a battery, which is recharged by a generator bearing developed by the Timken Company. Intra-train communication and control from the locomotive is over an 802.11b wireless LAN. The FIRE computer in the locomotive receives status information from the systems on each car and transmits commands to the cars to operate the advanced components. Hot bearing, derailed wheel and truck hunting events are immediately relayed to the locomotive engineer. The OBMCS is also equipped with a IXRTT cellular radio to transmit results to a central database and website. A GPS receiver provides time and location information necessary to track a car. On board sensing of mechanical defects enables car owners to track defects and pro actively schedule maintenance at an economical time and location.