Real-time traffic control in railway systems

Despite the constantly increasing demand of passengers and goods transport in Europe, the share of railway traffic is decreasing. One major reason appears to be congestion, which in turn results in frequent delays and in a general unreliability of the system. This fact has triggered the study of efficient ways to manage railway traffic, both off-line and real-time, by means of optimization and mathematical programming techniques. And yet, to our knowledge, there are only a few fully automated real-time traffic control systems which are actually in operation in the European railway system; in most cases such systems only control very simple lines and actually they only support the activity of human dispatchers. We describe here two recent optimization based applications to real-time traffic control which have actually been put into operation in the Italian railways. One such system has been able to fully control the trains in the terminal stations of Milano metro system. The other one will be fully operative by the end of 2012, when it will control the trains on several Italian single-track railways. Both systems heavily rely on mixed integer programming techniques to elaborate good quality timetables in real time

A communication platform demonstrator for new generation railway traffic management systems: Testing and validation

Current rail traffic management and control systems cannot be easily upgraded to the new needs and challenges of modern railway systems because they do not offer interoperable data structures and standardized communication interfaces. To meet this need, the Horizon 2020 Shift2Rail OPTIMA project has developed a communication platform for testing and validating the new generation of traffic management systems (TMS), whose main innovative features are the interoperability of the data structures used, standardization of communications, continuous access to real-time and persistent data from heterogeneous data sources, modularity of components and scalability of the platform. This paper presents the main components, their functions and characteristics, then describes the testing and validation of the platform, even when federated with other innovative TMS modules developed in separate projects. The successful validation of the system has confirmed the achievement of the objectives set and allowed a new set of objectives to be defined for the reference platform for the railway TMS/Traffic Control systems

A communication platform demonstrator for new generation railway traffic management systems: Testing and validation

\ua9 2023 The Author(s). Current rail traffic management and control systems cannot be easily upgraded to the new needs and challenges of modern railway systems because they do not offer interoperable data structures and standardized communication interfaces. To meet this need, the Horizon 2020 Shift2Rail OPTIMA project has developed a communication platform for testing and validating the new generation of traffic management systems (TMS), whose main innovative features are the interoperability of the data structures used, standardization of communications, continuous access to real-time and persistent data from heterogeneous data sources, modularity of components and scalability of the platform. This paper presents the main components, their functions and characteristics, then describes the testing and validation of the platform, even when federated with other innovative TMS modules developed in separate projects. The successful validation of the system has confirmed the achievement of the objectives set and allowed a new set of objectives to be defined for the reference platform for the railway TMS/Traffic Control systems

Adaptive Railway Traffic Control using Approximate Dynamic Programming

Railway networks around the world have become challenging to operate in recent decades, with a mixture of track layouts running several different classes of trains with varying operational speeds. This complexity has come about as a result of the sustained increase in passenger numbers where in many countries railways are now more popular than ever before as means of commuting to cities. To address operational challenges, governments and railway undertakings are encouraging development of intelligent and digital transport systems to regulate and optimise train operations in real-time to increase capacity and customer satisfaction by improved usage of existing railway infrastructure. Accordingly, this thesis presents an adaptive railway traffic control system for realtime operations based on a data-based approximate dynamic programming (ADP) approach with integrated reinforcement learning (RL). By assessing requirements and opportunities, the controller aims to reduce delays resulting from trains that entered a control area behind schedule by re-scheduling control plans in real-time at critical locations in a timely manner. The present data-based approach depends on an approximation to the value function of dynamic programming after optimisation from a specified state, which is estimated dynamically from operational experience using RL techniques. By using this approximation, ADP avoids extensive explicit evaluation of performance and so reduces the computational burden substantially. In this thesis, formulations of the approximation function and variants of the RL learning techniques used to estimate it are explored. Evaluation of this controller shows considerable improvements in delays by comparison with current industry practices

The Graphic time-table: traditional and innovative use of a cartogram for infrastructures management

L’orario grafico è un particolare tipo di cartogramma, a sviluppo bidimensionale spazio-temporale, da tempo impiegato nella rappresentazione di fenomeni trasportistici, nel controllo e nella programmazione di flussi di traffico ferroviario. Lo strumento ha visto, negli ultimi decenni, una sempre maggiore diffusione nella gestione dei flussi con l’ausilio di sistemi informatizzati che realizzano le rappresentazioni cartografiche in tempo reale. Più recentemente, per la prima volta in Italia, lo strumento è stato impiegato anche per la programmazione della gestione centralizzata di idrovie durante lo studio di fattibilità relativo a progetti per la realizzazione di nuove infrastrutture fluviali in Lombardia.The graphic time-table is a special kind of cartogram, developing in two dimensions (space and time), used in the representation of transport matters, in the control and managing of traffic flows. The cartogram has increased its diffusion in recent decades in the management of the railway traffic flows, supported by computerized systems that perform cartographic representations in real time. More recently, for the first time in Italy, the instrument was also used for programming the centralized management of waterways during the preliminary studies of new river infrastructures construction in Lombardy

A Highly Reliable Propulsion System with Onboard Uninterruptible Power Supply for Train Application:Topology and Control

Providing uninterrupted electricity service aboard the urban trains is of vital importance not only for reliable signaling and accurate traffic management but also for ensuring the safety of passengers and supplying emergency equipment such as lighting and signage systems. Hence, to alleviate power shortages caused by power transmission failures while the uninterruptible power supplies installed in the railway stations are not available, this paper suggests an innovative traction drive topology which is equipped by an onboard hybrid energy storage system for railway vehicles. Besides, to limit currents magnitudes and voltages variations of the feeder during train acceleration and to recuperate braking energy during train deceleration, an energy management strategy is presented. Moreover, a new optimal model predictive method is developed to control the currents of converters and storages as well as the speeds of the two open-end-windings permanent-magnet-synchronous-machines in the intended modular drive, under their constraints. Although to improve control dynamic performance, the control laws are designed as a set of piecewise affine functions from the control signals based on an offline procedure, the controller can still withstand real-time non-measurable disturbances. The effectiveness of proposed multifunctional propulsion topology and the feasibility of the designed controller are demonstrated by simulation and experimental results

Precise vehicle location as a fundamental parameter for intelligent selfaware rail-track maintenance systems

The rail industry in the UK is undergoing substantial changes in response to a modernisation vision for 2040. Development and implementation of these will lead to a highly automated and safe railway. Real-time regulation of traffic will optimise the performance of the network, with trains running in succession within an adjacent movable safety zone. Critically, maintenance will use intelligent trainborne and track-based systems. These will provide accurate and timely information for condition based intervention at precise track locations, reducing possession downtime and minimising the presence of workers in operating railways. Clearly, precise knowledge of trains’ real-time location is of paramount importance. The positional accuracy demand of the future railway is less than 2m. A critical consideration of this requirement is the capability to resolve train occupancy in adjacent tracks, with the highest degree of confidence. A finer resolution is required for locating faults such as damage or missing parts, precisely. Location of trains currently relies on track signalling technology. However, these systems mostly provide an indication of the presence of trains within discrete track sections. The standard Global Navigation Satellite Systems (GNSS), cannot precisely and reliably resolve location as required either. Within the context of the needs of the future railway, state of the art location technologies and systems were reviewed and critiqued. It was found that no current technology is able to resolve location as required. Uncertainty is a significant factor. A new integrated approach employing complimentary technologies and more efficient data fusion process, can potentially offer a more accurate and robust solution. Data fusion architectures enabling intelligent self-aware rail-track maintenance systems are proposed

Energy efficiency and integration of urban electrical transport systems: EVS and metro-trains of two real European lines

Transport is a main source of pollutants in cities, where air quality is a major concern. New transport technologies, such as electric vehicles, and public transport modalities, such as urban railways, have arisen as solutions to this important problem. One of the main difficulties for the adoption of electric vehicles by consumers is the scarcity of a suitable charging infrastructure. The use of the railway power supplies to charge electric vehicle batteries could facilitate the deployment of charging infrastructure in cities. It would reduce the cost because of the use of an existing installation. Furthermore, electric vehicles can use braking energy from trains that was previously wasted in rheostats. This paper presents the results of a collaboration between research teams from University of Rome Sapienza and Comillas Pontifical University. In this work, two real European cases are studied: an Italian metro line and a Spanish metro line. The energy performance of these metro lines and their capacity to charge electric vehicles have been studied by means of detailed simulation tools. Their results have shown that the use of regenerated energy is 98% for short interval of trains in both cases. However, the use of regenerated energy decreases as the train intervals grow. In a daily operation, an important amount of regenerated energy is wasted in the Italian and Spanish case. Using this energy, a significant number of electric vehicles could be charged every day