Overview of signalling and train control systems

2006 ◽  
Author(s):  
null
Keyword(s):  
Control Systems ◽  
Train Control

New Concepts for High-Level Petri Nets in the Application Domain of Train Control Systems

2000 ◽  
Vol 33 (9) ◽  
pp. 125-132 ◽  
Author(s):  
J. Padberg ◽  
P. Schiller ◽  
H. Ehrig
Keyword(s):  
Petri Nets ◽  
Control Systems ◽  
Application Domain ◽  
Train Control ◽  
New Concepts ◽  
High Level

scholarly journals The Study of Interoperability Test for Onboard Control System in Railway Condition

2011 ◽  
Vol 2-3 ◽  
pp. 785-790
Author(s):  
Jong Hyen Baek ◽  
Yong Kyu Kim ◽  
Jae Ho Lee ◽  
Hyen Jung Jo
Keyword(s):  
Control System ◽  
Control Systems ◽  
Data Systems ◽  
Test Results ◽  
Simulation Environment ◽  
Train Control ◽  
Interoperability Test ◽  
Critical Characteristics ◽  
Site Test ◽  
Onboard Equipment

For the purpose of improving the future domestic train control systems and securing interoperability, according to the global development trends of train control systems, it is presented that the test results of interoperability between wayside train control systems installed in existed line, and the onboard train control system. Due to the safety-critical characteristics of train systems, the site test in the section where the wayside equipment is installed may lead to a danger against safety. Therefore, by way of constructing a simulation environment of train control systems, the T/R data systems of the equipment for interoperability are confirmed and the interoperability test are obtained by applying these systems to onboard equipment.

Statistical Safe Braking Analysis

2011 ◽  
Author(s):  
David F. Thurston
Keyword(s):  
Control Systems ◽  
System Capacity ◽  
Worst Case ◽  
Stopping Distance ◽  
Train Control ◽  
Classic Theory ◽  
Braking Distance ◽  
Prime Determinant ◽  
Worst Case Approach

The main objective in optimizing train control is to eliminate the waist associated with classical design where train separation is determined through the use of “worst case” assumptions that are invariant to the system. In fact, the worst case approach has been in place since the beginning of train control systems. Worst case takes the most conservative approach to the determination of train stopping distance, which is the basis for design of virtually all train control. This leads to stopping distances that could be far more that actually required under the circumstances at the time the train is attempting to brake. Modern train control systems are designed to separate trains in order to provide safety of operation while increasing throughput. Calculations for the minimum distance that separates trains have traditionally been based on the sum of a series of worst case scenarios. The implication was that no train could ever exceed this distance in stopping. This distance is called Safe Braking Distance (SBD). SBD has always been calculated by static parameters that were assumed to be invariant. This is, however, not the case. Parameters such as adhesion, acceleration, weight, and reaction vary over time, location or velocity. Since the worst case is always used in the calculation, inefficiencies result in this methodology which causes degradation in capacity and throughput. This is also true when mixed traffic with different stopping characteristics are present at the same time. The classic theory in train control utilizes a SBD model to describe the characteristics of a stopping train. Since knowledge of these conditions is not known, poor conditions are assumed. A new concept in train control utilizes statistical analysis and estimation to provide knowledge of the conditions. Trains operating along the line utilize these techniques to understand inputs into their SBD calculation. This provides for a SBD calculation on board the train that is the shortest possible that maintains the required level of safety. The new SBD is a prime determinant in systems capacity. Therefore by optimizing SBD as describes, system capacity is also optimized. The system continuously adjusts to changing conditions.

scholarly journals THEORETICAL FUNDAMENTALS OF ESTIMATABILITY ASSESSMENT OF TRAIN SITUATION SIGNS FOR WORK OF INTELLECTUAL LOCOMOTIVE CONTROL SYSTEMS

2021 ◽  
Vol 1 (38) ◽  
pp. 223-231
Author(s):  
O. Gorobсhenko
Keyword(s):  
Control Systems ◽  
Random Search ◽  
Information Value ◽  
Train Control ◽  
Relative Value ◽  
Basic Parameters ◽  
Control Decision ◽  
Definition Of

The article is devoted to the problem of implementation of intelligent control systems in transport. An important task is to assess the information parameters of the control systems. In the existing works the question of definition of one of the basic parameters of functioning of locomotive control systems - information value of separate signs of a train situation is not considered. This does not make it possible to determine the order of signal processing at the input and assess their contribution to the adoption of a control decision. Moreover, informativeness is a relative value, which is expressed in the different information value of a particular feature for the classification of different train situations. Also, the informativeness of the feature may depend on the type of decisive rules in the classification procedure. The quality of recognition of a train situation in which the locomotive crew is, depends on the quality of the features used by the classification system. The decisive criterion for the informativeness of the features in the problem of pattern recognition is the magnitude of losses from errors. To determine the range of the most informative features of train situations, the method of random search with adaptation was used. The results of the work make it possible to optimize the operation of automated and intelligent train control systems by reducing the amount of calculations and simplifying their algorithm.

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