Automatic Train Operation System Research Articles

Study on Control Strategy of Train Automatic Speed Control System

To improve the efficiency of the automatic control in the process of train operation, reduce state transition caused by the signal interference and guarantee the safe operation of automatic train operation system, a kind of train automatic speed control strategy based on the fuzzy-predictive control algorithm is put forward. According to the dual-redundant control model, the reliability and safety of the train automatic speed control system is analyzed. Using anti-interference design, a series of model simulations have been accomplished. The results show that the system has good reliability.

The Study of Automatic Train Operation (ATO) System

As a sub-system of ATC system, the ATO subsystem is a very important part, which is the technical measure that can raise the train movement level of urban track transportation (on time, comfortably, energy-saving). Using LabVIEW embedded control system to simulate the ATO system with two levels of Fuzzy Neural Network. By studying and differencing the input data in preceding network, the best operating condition of the train in the specific position can obtain, according to which the latter network infers train's running speed under current condition.

Optimal driving strategy for traction energy saving on DC suburban railways

Energy saving on electrified railways has been studied for many years and the technical solution is usually provided by a combination of driving strategy (e.g. coasting), regenerative braking and energy storage systems. An alternative approach is for the driver (or automatic train operation system if fitted) to manage energy consumption more efficiently. A formal method for optimising traction energy consumption during a single-train journey by trading-off reductions in energy against increases in running time has been demonstrated. The balance between saving energy and running faster has been investigated by designing a fitness function with variable weightings. Energy savings were found, both qualitatively and quantitatively, to be affected by acceleration and braking rates, and, by running a series of simulations in parallel with a genetic algorithm search method, the fitness function was used to identify optimal train trajectories. The influence of the fitness function representation on the search results was also explored.

列車の自動運転制御 エキスパートシステムの自動列車運転装置への適用

Recently, the subway which required one-man operation has come to be constructed. In the Automatic Train Operation system, it is important to operate the train accurately. But the improvement of riding comfort and the energy saving are attached to importance compared with before.To achieve more highly developed operation, and to satisfy such a demand, we apply the expert system to the Automatic Train Operation system. In this discourse, Automatic train Operation Equipment with Expert system is described.

Safety checking in an automatic train operation system

Keeping the trains and tracks in a safe state is important for railway systems, which include automated control. ATO-2000 is an automated railway system that plans, operates, monitors and controls a small railway network of driver-less trains within a mine. The formal specifications, design and implementation of Checker Function (CF), a software sub-system responsible for maintaining safety in ATO-2000 are described. CF is an important component in a safety-critical, real-time, distributed, mobile computing system. The formal specifications (in Z) of the core safety requirements in ATO-2000 are presented which include a new representation of the track topology. Some fault tolerance of the data received from the field is achieved through data validation constraints. Command safety constraints conservatively validate outgoing commands so that no possible future system state is unsafe. A simple approach used to integrate formal methods in the industrial software development process is discussed. The paper concludes with a review of the lessons learnt.

Differential evolution based tuning of fuzzy automatic train operation for mass rapid transit system

Train performance of mass rapid transit systems can be improved with the use of fuzzy controllers in automatic train operation (ATO) systems. The tuning of these fuzzy controllers is presented using the algorithm of differential evolution (DE). The basic DE algorithm is modified to optimise a multiobjective function comprising punctuality, riding comfort and energy usage. Using this algorithm, the fuzzy ATO controller is tuned for each interstation train run. In operation, the controller adjusts each train's control according to the current operating conditions. A fuzzy ATO controller model was previously developed by the authors and is used to demonstrate the effectiveness of the tuning scheme.

PROGRAMMING APPROACH FOR FUZZY MODEL-BASED MULTIOBJECTIVE CONTROL SYSTEMS

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would often lose its original meaning of optimality. Nevertheless, the human operators usually perform satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation (ATO) system for the magnetically levitated vehicles (MAGLEV).

Fuzzy Control Of Automatic Train Operation System

The automatic train operation (ATO) system is a subsystem of an automatic train control system that is widely adopted in modern rapid transit systems. The function of ATO system is to regulate train riding comfort and smoothness during start, acceleration, constant speed travel, and fixed-point parking under the corresponding commands. This paper describes the dynamic model of a public rapid transit system and a predictive fuzzy controller with fuzzy control rules based on the operation concepts of a skilled human operator. The fuzzy rules decision-making is based on the predictive evaluation of performance indices, which includes electric power cost, riding comfort of passengers, traceability of target speed, and accuracy of stop gap. The simulation results for a planned railway trade of Taipei city rapid transit system show that the control performance of this fuzzy ATO system is better than that of the conventional PID controller. Stop gap control of fuzzy ATO can be executed successfully without the assistance of additional marker coils and vehicle alignment equipment.

Optimising train movements through coast control using genetic algorithms

A genetic algorithm (GA) is proposed to optimise train movements using appropriate coast control that can be integrated within automatic train operation (ATO) systems. The coast control output for a train changes with the interstation distances and gradient profiles, and the current operating conditions of the mass rapid transit (MRT) system, namely, (i) train schedules, (ii) expected passenger loads and (iii) expected track voltages. The algorithm generates an optimum coast control based on evaluation of the punctuality, riding comfort and energy consumption. Before the train sets off to the designated station, a coast control table is generated that will be referenced by the train at runtime for deciding when to initiate coasting or resume motoring control. Each coast control table is encoded into variable length chromosomes with each gene representing the relative position between stations where coasting should be initiated or terminated. Each generation is evolved from mating of the paired equal-length chromosomes with possibilities of crossover, mutations, gene duplications and gene deletions. The key feature of this method is that it has a solid mathematical foundation. Effectively, the implementation provides good, credible and reasonably fast solutions for this variable dimensional and multiobjective optimisation problem. The algorithm has the potentials for on-line implementation for producing the coast control lookup table for each interstation run before the train sets off. The results, although preliminary, suggest that the method is promising.

The Application of Fuzzy Control To Automatic Train Operation

This paper reflects an attempt to apply a novel method of fuzzy logic control to Automatic Train Operation (ATO) system through directly modelling the behavior of a skilled driver, which is based on the idea of Partition of Complex Process & Hierarchical Intelligent Control (PCP&HLC). A new method to determine the Firing strength of fuzzy rule - weighted sum of membership of input variables - is also proposed. The simulation results have shown the effectiveness and feasibility of what proposed.

A Model Predictive Pattern Tracking Control Algorithm for Automatic Train Operation System.

Automatic Train Operation (ATO) system is a system to control a train running automatically. It is required to operate a train to run satisfying some constraints concerned with distance, time, speed limit, and to run with little energy and riding comfort. The ATO system in this paper calculates how to run (running pattern) for a train concerned about these conditions before running as a reference, and controls a train to run along the running pattern while running.Amodel predictive pattern tracking control algorithm for this type of ATO system is described in this paper. It is an algorithm to control notch switching to cancel effects of condition variances and disturbances during running, , and to make a train run tracking a reference running pattern with riding comfort.This algorithm predicts how a train runs in future and selects times to switch notches leading smaller error between the train running and a reference running pattern. It realizes comfortable running with few times of notch switchings and accurate stopping of a train, a non-linear and discrete system, by adjusting notch switching times of the reference running pattern using Simulation-based Model Predictive Control.

Docklands Light Railway. A revolution in railway engineering

The Docklands Light Railway, which opened in August 1987, is the first railway specifically designed for distributed-microprocessor control. The capability of light-rail vehicles to run around tight curves is fully exploited as is their ability to climb steep gradients. At present there are 11 vehicles, nine are in service and two are on standby. The operation of the railway depends on two automatic systems: the automatic train operation (ATO) system drives the train from station to station and the automatic train protection system supervises the railway, ensuring that trains observe speed limits and only proceed when safe to do so.

Fuzzy Control for Automatic Train Operation System

A fuzzy control that uses rules based on a. skilled human operator’s experience is applied to automatic train operations. Essentially, train operation is a nonlinear control function. Up to now, this system has been developed by linearlized control using a target pattern. However, it was difficult to control the train in a manner similar to a human operator. In this paper, a fuzzy control which uses linguistical control rules is proposed. Furthermore, an automatic train operation system which evaluates safety, comfort, traceability of target velocity, and the accuracy of a stop cao has been developed. According to the result of the simulation, our newly developed automatic control system having the fuzzy control realizes a comfortable and accurate stop control, and its control rules are easy to understand and are connected to the performance indices. Therefore, system performance can be directly adjusted as desired.

Fuzzy制御による列車定位置停止制御

A predictive fuzzy control system that uses rules based on the experience of a skilled human operator is proposed and applied to achieve automatic stop operation for trains. In recent years, automatic train operation (ATO) systems using microcomputers to replace human operators have been developed for new transit systems, including subways, monorails and new public transit systems. Because the train operation is a typical uncertain nonlinear system, improvement of performance indices such as safety, riding comfort of passengers, and accuracy of the stopgap is great challenge to ATO. Up to now, ATO systems have been developed using linear control of the target pattern. However, it is difficult to control a train automatically in a manner similar to control by a human operator using linear control. In this paper, we propose a predictive fuzzy control system that selects the most likely control rule from a set of control rules. The system is described as follows: ”If (u is C → x is A and y is B) then u is C.”. The proposed fuzzy control system is applied to a train automatic stop control system that takes into account passenger comfort, accuracy of a stopgap and running time. Simulation results of this newly developed fuzzy control system indicate that the system can directly adjust system performance as desired in a manner similar to control by a skilled operator and thereby stop the train comfortably and accurately.

BART's hardware¿from bolts to computers

In 1965 BART began the Mt. Diablo Test Track. Three laboratory cars were built and used to test new technology. The testing program included reduction of sound and vibration, propulsion equipment and power supply, transit vehicle trucks, automatic train operation, rails and rail support, and aerial structures, tubes, and tunnels. Five propulsion system were tested, and dc chopper control was selected. The Rohr built transit cars, 250 of them, feature cantilever seat construction, noise suppression, air conditioning, and glare free lighting. The car trucks are equipped with derail detectors connected into the automatic train operation system. On aerial structures and in tunnels, rail is fastened directly to the concrete slab or tunnel invert. For the Berkeley Hills tunnel, which crosses the Hayward Fault, rails were mounted on timber ties to permit speedy realignment. The Trans Bay Tube contains both horizontal and vertical curvature. Fifty-seven prefabricated sections were floated into position, then sunk. The Trans Bay Tube terminates in a ventilation building at each end. Cathodic protection is used. Welded rail was used, and the second pour technique for concrete. BART purchases power at 34.5 kvac. This power system has seven sections. An I section steel third rail provides strength and the top running surface for overrunning pickup shoes. Aluminum inserts carry the current. A J shaped cover protects against accidental contact. Automatic train operation handles speed regulation, programmed station stops, and train door operation. Line supervision provides best possible service schedules. Train protection maintains the safety of the operation.

Teito rapid transit authority's automatic train operation

The traffic congestion in and around Tokyo has become intensified year after year, and the subway has come to be looked upon as the most effective way of eliminating it, or alleviating it to an appreciable extent at least. The Teito Rapid Transit Authority (TRTA) in Japan has had an automatic train control (ATC) system in operation for many years to ensure safety adequately while fully exploiting its service efficiency. In the face of ever-increasing population and transport demand, the Authority in its quest for higher efficiency and safety in train operation pioneered in developing an automatic train operation (ATO) system and has been testing it on the Hibiya Line since 1962. Under the ATO, all train functions-notch-in, power running, coasting, braking, and stopping--are performed automatically. The motorman simply presses a pushbutton to start the train, which then runs on safely under ATC and stops smoothly, accurately, and automatically at the next station. We are satisfied with the results of tests in regard to the durability, reliability, and accuracy of the system as well as in regard to riding quality. The Authority is convinced that by putting this new system into operation the ATO can carry on passenger service at a shorter headway, with greater safety and accuracy, and can expand traffic capacity to some extent. Further study is now under way to improve the system by combining a centralized traffic control system and an inductive radio system, in order to exercise group control over all the trains on the track.

Innovations in Mass Transit

After construction of rapid transit systems in several major American cities around the turn of the century, little was done to improve or develop new rolling stock until the 1950’s. A new rapid transit system in Cleveland and extensions to existing systems resulted in reductions in weight of traction motors and car bodies, cutting the weight of some 1950-1960 cars to almost half of the equipment being replaced. Starting in the early 1960’s, new interest appeared in the transit industry—existing systems required replacements for cars 40 yr to 60 yr old. San Francisco started planning a $1,000,000,000 all-new system using the latest techniques. Other cities followed suit utilizing high-speed, high-performance cars, all of them steel wheel on steel rail. Other systems have or are being proposed: rubber-tired; suspended monorail; supported monorail; medium-density systems and small four- to eight-seat units propelled by various means. High-speed (160 mph) electric and turbine-powered trains are being built for testing in 200- to 300-mile intercity service. Automatic train operation and fare collection systems are being installed on existing and new systems. Many other interesting innovations in transit systems for the mass movement of people are being explored.