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Local knowledge in signaller performance

Lookup NU author(s): Dr David GolightlyORCiD

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by RSSB, 2021.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

Rail signalling is known to be highly dependent on local knowledge and local factors. Pickup et al (2013) proposed a Local Knowledge Framework to help determine the contents of and motivations behind local knowledge. In the current paper, the framework is revisited based on eight hours of observations and 15 interviews conducted at four different signalling locations representing a range of signalling control technologies. The data derived from this study extends the framework to include user worked crossings. Additionally, for level crossings (whether worked by users or signallers), local geographical conditions and knowledge of members of the public using the crossings were identified as key factors. Temporal factors were also a consideration. As a whole, the study sheds light on why local variations in practice arise, highlighting their role in the necessary trade-offs of achieving acceptable performance.


Publication metadata

Author(s): Golightly D, Young M

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 7th International Rail Human Factors Conference

Year of Conference: 2021

Print publication date: 25/06/2021

Acceptance date: 16/01/2021

Date deposited: 02/07/2021

Publisher: RSSB

URL: https://www.eventsforce.net/rssb/frontend/reg/thome.csp?pageID=38563&ef_sel_menu=599&eventID=141


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