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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
12.05.2020
DOI
https://doi.org/10.7307/ptt.v32i3.3241
ISSUE
2020 (Vol 32), Issue 3
LICENSE
Copyright (c) 2024 Bobo Zhao, Tao Tang
Creative Commons 4.0 logo
This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

Evaluating the Learning Performance of Emergency Procedures for Operators in Metro Based on a Cognition Model

Authors:

Bobo Zhao
National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University

Tao Tang

Keywords:cognitive modelling, emergency procedures, human performance modelling, rail transit system, levels of automation, trust in automation

Abstract

With the rapid development of the automated metro, valid emergency procedures play a significant role for operators in metro emergency response and recovery. Also, the operators have a challenge to learn different emergency procedures under different automation grades of the metro. Hence, the paper aims to evaluate the learning performance of emergency procedures with regard to the operator. Based on the ACT-R cognitive theory, two decision patterns of the operators are proposed to predict the operator’s learning process for emergency procedures, and a cognition model including 16 production rules and 32 chunks to realize the perceptual encoding and the corresponding determining parts is built. After that, an experiment is further implemented to validate the model results.

References

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How to Cite
Zhao, B. (et al.) 2020. Evaluating the Learning Performance of Emergency Procedures for Operators in Metro Based on a Cognition Model. Traffic&Transportation Journal. 32, 3 (May. 2020), 335-345. DOI: https://doi.org/10.7307/ptt.v32i3.3241.

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