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Quantitative modelling in cognitive ergonomics: predicting signals passed at danger

Quantitative modelling in cognitive ergonomics: predicting signals passed at danger
Quantitative modelling in cognitive ergonomics: predicting signals passed at danger
This paper shows how to combine field observations, experimental data, and mathematical modeling to produce quantitative explanations and predictions of complex events in human-machine interaction. As an example we consider a major railway accident. In 1999 a commuter train passed a red signal near Ladbroke Grove, UK, into the path of an express. We use the Public Inquiry Report, "black box" data, and accident and engineering reports, to construct a case history of the accident. We show how to combine field data with mathematical modelling to estimate the probability that the driver observed and identified the state of the signals, and checked their status. Our methodology can explain the SPAD (“Signal Passed At Danger”), generate recommendations about signal design and placement, and provide quantitative guidance for the design of safer railway systems speed limits and the location of signals
1366-5847
Moray, Neville
510d52a8-bb3b-4df6-bae4-504c350c166c
Groeger, John
e8d5529b-dcc5-4586-83ca-972b2272c24b
Stanton, Neville
351a44ab-09a0-422a-a738-01df1fe0fadd
Moray, Neville
510d52a8-bb3b-4df6-bae4-504c350c166c
Groeger, John
e8d5529b-dcc5-4586-83ca-972b2272c24b
Stanton, Neville
351a44ab-09a0-422a-a738-01df1fe0fadd

Moray, Neville, Groeger, John and Stanton, Neville (2016) Quantitative modelling in cognitive ergonomics: predicting signals passed at danger. Ergonomics. (doi:10.1080/00140139.2016.1159735). (PMID:27097331)

Record type: Article

Abstract

This paper shows how to combine field observations, experimental data, and mathematical modeling to produce quantitative explanations and predictions of complex events in human-machine interaction. As an example we consider a major railway accident. In 1999 a commuter train passed a red signal near Ladbroke Grove, UK, into the path of an express. We use the Public Inquiry Report, "black box" data, and accident and engineering reports, to construct a case history of the accident. We show how to combine field data with mathematical modelling to estimate the probability that the driver observed and identified the state of the signals, and checked their status. Our methodology can explain the SPAD (“Signal Passed At Danger”), generate recommendations about signal design and placement, and provide quantitative guidance for the design of safer railway systems speed limits and the location of signals

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More information

Accepted/In Press date: 24 February 2016
e-pub ahead of print date: 20 April 2016
Organisations: Transportation Group

Identifiers

Local EPrints ID: 393037
URI: http://eprints.soton.ac.uk/id/eprint/393037
ISSN: 1366-5847
PURE UUID: fd668f94-7a37-4adb-aa59-ff73ad477c31
ORCID for Neville Stanton: ORCID iD orcid.org/0000-0002-8562-3279

Catalogue record

Date deposited: 06 Jun 2016 10:25
Last modified: 15 Mar 2024 05:30

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Contributors

Author: Neville Moray
Author: John Groeger
Author: Neville Stanton ORCID iD

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