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Computational-rabi's driver training model for prime decision-making in driving

Recent development of technology has led to the invention of driver assistance systems that support driving and help to prevent accidents. These systems employ Recognition-Primed Decision (RPD) model that explains how human make decisions based on prior experience. However, the RPD model does not in...

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Main Authors:	Mustapha, Rabi, Yusof, Yuhanis, Ab. Aziz, Azizi
Format:	Article
Language:	English
Published:	JATIT 2019
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://repo.uum.edu.my/26357/1/JTAIT%2097%2013%202019%203540%203558.pdf http://repo.uum.edu.my/26357/ http://www.jatit.org/volumes/ninetyseven13.php
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id	my.uum.repo.26357
record_format	eprints
spelling	my.uum.repo.263572019-09-03T02:38:14Z http://repo.uum.edu.my/26357/ Computational-rabi's driver training model for prime decision-making in driving Mustapha, Rabi Yusof, Yuhanis Ab. Aziz, Azizi QA75 Electronic computers. Computer science Recent development of technology has led to the invention of driver assistance systems that support driving and help to prevent accidents. These systems employ Recognition-Primed Decision (RPD) model that explains how human make decisions based on prior experience. However, the RPD model does not include necessary training factors in making prime decision. Although, there exist an integrated RPD-SA model known as Integrated Decision-making Model (IDM) that includes training factors from Situation Awareness (SA) model, the training factors were not detailed. Hence, the model could not provide reasoning capability. Therefore, this study enhanced the IDM by proposing Computational-Rabi’s Driver Training (C-RDT) model that includes improvement on RPD component of the IDM. The C-RDT includes 18 additional training factors obtained from cognitive theories that make a total of 24 training factors that facilitate driver’s prime decision-making during emergencies. The designed model is realized by identifying factors for prime decision-making in driving domain, designing the conceptual model of the RDT model and formalizing it using differential equation. To demonstrate the designed model, simulation scenarios based on driver’s training and awareness has been implemented. The simulation results are found to support related concepts found in literature. The results also provide insight into the robustness nature of the model. The computational model realized in this study practically can serve as a guideline for software developers on the development of driving assistance systems for prime decision-making process. Also, the computational model when combined with support components can serve as an intelligent artefact for driver’s assistance system. Moreover, the C-RDT model offers reasoning ability that allows backtracking on why certain prime-decision has been made. JATIT 2019 Article PeerReviewed application/pdf en http://repo.uum.edu.my/26357/1/JTAIT%2097%2013%202019%203540%203558.pdf Mustapha, Rabi and Yusof, Yuhanis and Ab. Aziz, Azizi (2019) Computational-rabi's driver training model for prime decision-making in driving. Journal of Theoretical and Applied Information Technology, 97 (13). pp. 3540-3558. ISSN 1992-8645 http://www.jatit.org/volumes/ninetyseven13.php
institution	Universiti Utara Malaysia
building	UUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Utara Malaysia
content_source	UUM Institutionali Repository
url_provider	http://repo.uum.edu.my/
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Mustapha, Rabi Yusof, Yuhanis Ab. Aziz, Azizi Computational-rabi's driver training model for prime decision-making in driving
description	Recent development of technology has led to the invention of driver assistance systems that support driving and help to prevent accidents. These systems employ Recognition-Primed Decision (RPD) model that explains how human make decisions based on prior experience. However, the RPD model does not include necessary training factors in making prime decision. Although, there exist an integrated RPD-SA model known as Integrated Decision-making Model (IDM) that includes training factors from Situation Awareness (SA) model, the training factors were not detailed. Hence, the model could not provide reasoning capability. Therefore, this study enhanced the IDM by proposing Computational-Rabi’s Driver Training (C-RDT) model that includes improvement on RPD component of the IDM. The C-RDT includes 18 additional training factors obtained from cognitive theories that make a total of 24 training factors that facilitate driver’s prime decision-making during emergencies. The designed model is realized by identifying factors for prime decision-making in driving domain, designing the conceptual model of the RDT model and formalizing it using differential equation. To demonstrate the designed model, simulation scenarios based on driver’s training and awareness has been implemented. The simulation results are found to support related concepts found in literature. The results also provide insight into the robustness nature of the model. The computational model realized in this study practically can serve as a guideline for software developers on the development of driving assistance systems for prime decision-making process. Also, the computational model when combined with support components can serve as an intelligent artefact for driver’s assistance system. Moreover, the C-RDT model offers reasoning ability that allows backtracking on why certain prime-decision has been made.
format	Article
author	Mustapha, Rabi Yusof, Yuhanis Ab. Aziz, Azizi
author_facet	Mustapha, Rabi Yusof, Yuhanis Ab. Aziz, Azizi
author_sort	Mustapha, Rabi
title	Computational-rabi's driver training model for prime decision-making in driving
title_short	Computational-rabi's driver training model for prime decision-making in driving
title_full	Computational-rabi's driver training model for prime decision-making in driving
title_fullStr	Computational-rabi's driver training model for prime decision-making in driving
title_full_unstemmed	Computational-rabi's driver training model for prime decision-making in driving
title_sort	computational-rabi's driver training model for prime decision-making in driving
publisher	JATIT
publishDate	2019
url	http://repo.uum.edu.my/26357/1/JTAIT%2097%2013%202019%203540%203558.pdf http://repo.uum.edu.my/26357/ http://www.jatit.org/volumes/ninetyseven13.php
_version_	1646016532310917120
score	13.211869

Computational-rabi's driver training model for prime decision-making in driving

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