Signal Wake Model (SWM)
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1982-03-01
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By Welch, Norma
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Abstract:In the late 1970s, traffic volumes were predicted to double on Canadian National Railway's already congested single track main line. In support of a plant expansion program, a transportation planning research team developed two "what-if" simulation models: the Signal Wake and Route Capacity Models to evaluate the relative effect of the many factors influencing main line capacity. When used together, they predict train delay under various track and signal designs, operating methods, and traffic scenarios. The team then proposed a package of cost-effective improvements for capacity expansion, which included closely spaced inter mediate signals and strategically located sections of double track. In 1985, Canadian National Railways (CN) received the prestigious Franz Edelman Award for Management Science Achievement for their project titled "Expansion of Canadian National Railways' Line Capacity". (Interfaces, 16(1), 51–64. https://www.jstor.org/stable/25060783)
The Signal Wake Model (SWM) is a detailed computer simulation model which allows analysis of the effect of a signal system on the movement of following trains. Specifically, the simulation moves a fleet of trains over a given signal plant as close together as the signal system allows. Minimum train headways are determined at each signal location. SWM is often used in conjunction with the Route Capacity Model (RCM) for analyzing the capacity of a CTC rail line. Specifically, RCM implements a simulation of train movements based on the headways provided to it by the SWM. This report outlines the capabilities of the CN Signal Wake Model (SWM) and describes the design of the model from a user perspective.
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Content Notes:Please cite as: Welch, N., “ Signal Wake Model (SWM),” Transport Research Dept., Canadian National Railways, Montreal, Canada, March, 1982.
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Main Document Checksum:urn:sha-512:ad47e61371ebfb1b73bd7a4d69a2babcd082efaa5660d692438b65fb6610b99d38cec86c3952db5c181d584bd9816732e02a504d6f5056237d56cc5fc3f10753
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