The communications system architecture of the North American Advanced Train Control System

Coll, D.C.; Sheikh, A.U.H.; Ayers, R.G.; Bailey, John H.

doi:10.1109/25.131006

Cited by 20 publications

(7 citation statements)

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“…Or at a frequency of 1200 MHz for GLONASS. The use of GPRS technology on RWT has led to a significant increase of the transmission capacity of data transmission channels [1,16,17].…”

Section: Models and Methodsmentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Yerkeldessova¹,

Akhmetov²,

Issaikin³

et al. 2019

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The paper analyzes the prospects for the formation and implementation of digital data transmission technologies on railways of Kazakhstan, taking into account the potential for the development of high-speed railway transport (HSRWT), as well as new approaches for solving the development problems of advanced automated dispatch control systems (ADCS). It was shown that the solution of these problems is possible by automatization of the train traffic coordination based on the use of the potential of the GPRS data transmission technology. The work further developed models and algorithms used in ADCS of the railway transport. There has been carried out the formalization of the tasks of navigation data transmission for ADCS and for the subsystems of the railway rolling stock movement coordination, including HSRWT using GPRS data transmission technology. Also, the article describes a modernized algorithm for simulation of the GPRS channels operation in ADCS. The proposed algorithm differs from the existing ones by the ability to make predictive estimates for determination of the railway rolling stock location. Also, the developed algorithm provides opportunities for coordination of the trains movement, taking into account the optimization of the GPRS resources use.

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“…Or at a frequency of 1200 MHz for GLONASS. The use of GPRS technology on RWT has led to a significant increase of the transmission capacity of data transmission channels [1,16,17].…”

Section: Models and Methodsmentioning

confidence: 99%

International Journal of Electronics and Telecommunications

Yerkeldessova¹,

Akhmetov²,

Issaikin³

et al. 2019

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“…The use of centralized simulators, operating sequentially on a uniprocessor computer, to model real-world transportation systems constitutes the logical evolution beyond pure analytic modelling. Examples include the North American advanced train control system (ATCS) [1], where information from all trains is collected at a central dispatcher which, in turn, determines the movement decisions for every train, and the traffic management centre (TMC) in Minneapolis which receives traffic data from 142 CCTV cameras, located along the highways and connected through fibre optics, and then exercises control through 354 ramp meters. However, for large-scale transportation problems, consisting of a significant number of subsystems that are geographically dispersed over large distances, centralized simulations may be agonizingly slow and the accuracy of the simulation results may be low.…”

Section: Scientific Validation Of Transportation System Designs Through Modelling and Simulationmentioning

confidence: 99%

“…The availability of computing engines fuelled the second major revolution in transportation systems, wherein fast and precise computers were exploited efficiently to control and coordinate the transport of goods and people across the system. Excellent examples of computer usage in transportation, in use today, include the centralized control for railways [1], centralized air traffic controllers and traffic management centres [2] for automobiles. For simplicity, ease of comprehension and the desire to maintain consistent control, the coordination and control functions, from the beginning, have been consolidated into centralized units and this continues to dominate to this day.…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents the basic principles pertaining to travel-related decision-making which includes coordination, control and routing. These principles constitute the core of all transportation systems, including railways [1], passenger air travel, highways, air freight, personalized rapid transit [4], etc., and have been utilized successfully to develop systems for railways [5,6] and vehicles [2].…”

Section: Introductionmentioning

confidence: 99%

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Fundamental issues in intelligent transportation systems

Ghosh

1999

Proceedings of the Institution of Mechanical Engineers, Part F:

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The notion of transportation refers to the movement of people and goods across non-trivial geographical distances. Its history is as old as our civilization and its importance and scope are enormous, ranging from people walking on the earth's surface to carts and chariots driven by animals, automobiles, trains, airplanes and ships. To date, the discipline of transportation has experienced two major revolutions. Prior to the discovery of electromagnetic communication, information on the transport of goods and people was propagated along with the transported material and, in essence, their transit speeds were identical. The use of electromagnetic communication, the first major revolution in the discipline of transportation, made the propagation of information about the movement of goods and people significantly faster than the actual transport of the material at limited speeds. This resulted in superior planning as well as tracking of the movement of material through the transportation network. The availability of computing engines fuelled the second major revolution in transportation systems wherein fast and precise computers were exploited efficiently to control and coordinate the transport of goods and people across the system. For a number of reasons, including simplicity and the desire to maintain consistent control, the information and guidance providers of the transportation systems evolved as centralized units. A central control collected information about every entity within a specific transportation system and provided guidance and information to them as necessary. Today, the transportation discipline is on the brink of experiencing the third major revolution and possibly the most complex-the transformation from the centralized paradigm to the asynchronous, distributed paradigm which will integrate fast computers and high-performance computer networks through novel computer algorithms. This paper presents fundamental issues and principles underlying today's and tomorrow's intelligent transportation systems, including railways, highways, air travel, cargo networks and personalized rapid transportation systems. These principles have been utilized successfully in developing systems for railways and vehicles that have been reported in the literature. The paper also presents motivations for further research into the key areas of modelling and simulation and visualization of intelligent transportation systems.

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“…The results were inefficiency and high costs, caused by slow sequential processing, the need to propagate data and information from geographically-dispersed sites to the central computer , and relay the decisions back to the sites. Examples include the Centralized Traffic Control (CTC) (Compton 1993) and the ATCS (Coli , 1990) , both for railway networks. In these systems, the destination of every train is known a priori by the dispatchera uniprocessor computer.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Virtual Versus Physical Process-Migration Strategies for Distributed Modeling and Simulation of Mobile Computing Networks

Han

Ghosh

1996

Distributed Platforms

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This paper focuses on the high level principles that underlie the distributed modeling and accurate simulation of mobile computing networks on a parallel processing testbed. The testbed consists of a network of workstations configured as a loosely-coupled parallel processor and it closely resembles reality. A key issue is the representation of the stationary and mobile entities of the mobile computing network through concurrent and interacting processes in the testbed. The nature of the representation will influence the accuracy and performance of the simulation. This paper first reviews a process representation technique that has been proposed in the literature for modeling railway networks and then analyzes its limitations. This strategy is referred to as Virtual Process Migration (VPM). The paper then proposes a new strategy, termed Physical Process Migration (PPM) , that aims to address the limitations of VPM. It details the software techniques underlying both approaches , describes their implementations on a realistic testbed, and then contrasts their performance under different representative scenarios. While VPM is capable of modeling modest to large-scale mobile computing networks on a testbed consisting of a few processors, the number of processors of the testbed in PPM must correspond to the number of stationary and mobile entities of the mobile computing network size that is being modeled. Analysis of the sim ulation results reveals that both VPM and PPM are highly effective and very useful strategies under different circumstances. For a given number of mobile and stationary entities, simulation under PPM is fast when every mobile entity requires significant computation. On the other hand, VPM exhibits superior performance relative to PPM when the number of data elements exchanged by each mobile entity at each hop is significantly high.

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The communications system architecture of the North American Advanced Train Control System

Cited by 20 publications

References 1 publication

International Journal of Electronics and Telecommunications

International Journal of Electronics and Telecommunications

Fundamental issues in intelligent transportation systems

A Comparative Analysis of Virtual Versus Physical Process-Migration Strategies for Distributed Modeling and Simulation of Mobile Computing Networks

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