Computational Model of Situation Awareness for Decision Making in Driving

Mustapha, Rabi; Yusof, Yuhanis; Aziz, Azizi Ab

doi:10.1166/asl.2018.10725

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are three driving scenarios set up based on the external factors that are in line with the three simulated scenarios in a simulation environment using MATLAB. The three driving scenarios set up are good driving conditions (low risk), average driving conditions (moderate risk) and bad driving conditions (high risk) [12,13]. The three different driving scenarios consist of different conditions in driving environment that includes road, traffic, obstacles, car condition and visibility.…”

Section: Mapping Driving Scenarios With Awareness Factors Of the Rdt Model And The Simulator Featuresmentioning

confidence: 99%

Validation of Computational-Rabi’s Driver Training Model for Prime Decision-Making

Mustapha

Ahmed

Ahmad

2021

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

This paper explains the validation of Computational-Rabi's Driver Training (C-RDT) model for Primed Decision-making. To prove the workability of this model, evaluation using validation is indispensable. Hence, validation is a method used to ensure the logical correctness of the model. Therefore, evaluating the model by validation method is yet to be achieved in literature. Hence, this study bridged this gap by providing it, and it serves as the novelty of this study. To validate the C-RDT model, experimental method was adopted whereby an experiment was conducted using human. An adapted game driving simulator features were mapped with the external factors of the awareness component of the model, and the instrument used for the validation was also designed based on the external and temporal factors of the training component of the model. Only a post-test experiment involved to examine the effectiveness of the model factors. The experiment determines the effect of the training with the game simulator on the automaticity of the driver to make effective prime decision. For the experiment, participants were divided into control and experimental groups. The experimental group were trained while the control group were not trained. Two hypotheses were set based on the outcomes of training: H0 and H1. The results obtained has shown that the experimental group participants have better decision-making skill as compared to control group. This supports the alternative hypothesis (H1), which implies that training factors in the model improved the driver's prime decision-making during emergency and this proved the validity of the model.

show abstract

Section: Mapping Driving Scenarios With Awareness Factors Of the Rdt Model And The Simulator Featuresmentioning

confidence: 99%

Validation of Computational-Rabi’s Driver Training Model for Prime Decision-Making

Mustapha

Ahmed

Ahmad

2021

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

show abstract

Mathematical Verification of Hybrid Model for Prime Decision-Making in Driving

Mustapha

Ahmad

Ahmed

et al. 2021

International Conference on Emerging Applications and Technologies for Industry 4.0 (EATI’2020)

View full text Add to dashboard Cite

Computationally aware systems: Recommended features through a review of 188 definitions and its relevance to advanced simulation

Irani

Monfared

Kazemifard

et al. 2021

Int. J. Model. Simul. Sci. Comput.

View full text Add to dashboard Cite

In this paper, 188 definitions of aware, awareness, conscious, and consciousness, classified in different categories including cognitive science, computation, medicine, neurology, and philosophy, are reviewed. Based on this systematic review, desirable features of computationally aware systems (CASs) are gleaned and reported. A discussion about the relevance of computational awareness to advanced simulation is also outlined.

show abstract

Computational Model of Situation Awareness for Decision Making in Driving

Cited by 3 publications

References 0 publications

Validation of Computational-Rabi’s Driver Training Model for Prime Decision-Making

Validation of Computational-Rabi’s Driver Training Model for Prime Decision-Making

Mathematical Verification of Hybrid Model for Prime Decision-Making in Driving

Computationally aware systems: Recommended features through a review of 188 definitions and its relevance to advanced simulation

Contact Info

Product

Resources

About