The Use of Interactive Simulations to Affect Driving Behaviour

Rai, Shri; Wong, Kevin

doi:10.5176/978-981-08-5480-5_102

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…Using PEM and EfTP indicators to assess potential benefits, we will use a costing model to conduct our costbenefit analysis. For example, Rai and Wong (2010) suggest that a flight simulator costs only 15% of using actual helicopters for training purposes. Drawing from their study, we have selected the following cost categories as our evaluation metrics:…”

Section: Transfer Effectiveness = (2)mentioning

confidence: 99%

“…There is an abundant literature on research dedicated to Interactive Virtual Reality (IVR) environments (Bell 1991;Rickel and Johnson 1998;Furlong, Vance et al 1999;Burdea and Coiffet 2003;Fox, Arena et al 2009;Jou and Wang 2012), IVR-based teaching and training programmes (Salzman, Dede et al 1999;Moreno and Mayer 2002;Moreno and Mayer 2007) or their application to different industries (Orlansky and String 1977;Bakken, Gould et al 1992;Filigenzi, Orr et al 2000;Deaton, Barba et al 2005;van Wyk and de Villiers 2009;Rai and Wong 2010;Schmitt, Agarwal et al 2012). Literature investigating and evaluating the impact of IVR-based training programs on safety and productivity records is far less abundant.…”

Section: Introductionmentioning

confidence: 99%

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Impact of virtual training on safety and productivity in the mining industry

Pedram

Perez

Dowsett³

2013

Piantadosi, J., Anderssen, R.S. And Boland J. (Eds) MODSIM2013, 20th International Congress on Modelling and Simulation

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Best practice in the mining industry includes extensive initial and professional training for staff involved in field operations. While changes in mining technology and operations accelerate to improve productivity, health and safety standards have to be continuously evaluated and improved, putting more pressure on training deliveries. Borrowing from Defence and Airspace industries, training in the mining industry is increasingly relying on immersive virtual reality to simulate complex operations and procedures in potentially dangerous environments. Coal Services Pty Ltd is at the forefront of modern training facilities in Australia.This paper presents a qualitative and quantitative research framework designed to analyse the impact of past and current training sessions on staff's ability to better perform their tasks, overall safety standards and mine productivity. It is relatively difficult to benchmark training techniques or programs in the mining industry as the very nature of the industry prevents from experimental comparisons with a control group. Hence, we have chosen to use diachronic methods to evaluate the effective impact of IVR-based training on worker's competences. In particular, our interviews with managers and access to relevant industry records will help us to identify two periods: before and after the introduction of IVR-based training. Another more qualitative approach will consist in interviewing personnel who have undertaken during their career at least two types of training programs, including IVR-based ones. The framework uses interviews with trainees, trainers and managers, alongside session recordings, to qualitatively evaluate levels of knowledge transfer and aptitudes to perform in a real environment. Then, a cost-benefit analysis is to be used to evaluate the added-value of virtual reality-based on technological and operational costs weighed against overall productivity of the mine being negatively affected by any safety issue.

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Section: Transfer Effectiveness = (2)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of virtual training on safety and productivity in the mining industry

Pedram

Perez

Dowsett³

2013

Piantadosi, J., Anderssen, R.S. And Boland J. (Eds) MODSIM2013, 20th International Congress on Modelling and Simulation

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“…Computational intelligence (CI) theories such as evolutionary algorithms [22,23], artificial neural networks [24], cognitive map analysis [25], Physarum solver [26][27][28], fuzzy sets [29][30][31], belief function [32][33][34], PSO [35][36][37], and so on [38], have been widely used to cope the complex problems including the permutation flow shop problem [39], supply chain network [40,41], traveling salesman problem [42], pattern recognition [43][44][45][46], power system [47], product design and manufacturing [48], and so on [49][50][51][52]. Recently, based on this progress in CI, many nature inspired approaches have been proposed to solve test selection optimization problem, such as the greedy strategy [53], the genetic algorithm [54,55], the evolutionary algorithm [56,57], and so on [58].…”

Section: Introductionmentioning

confidence: 99%

An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO

Zhou

Tang

et al. 2018

Complexity

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Sensor data-based test selection optimization is the basis for designing a test work, which ensures that the system is tested under the constraint of the conventional indexes such as fault detection rate (FDR) and fault isolation rate (FIR). From the perspective of equipment maintenance support, the ambiguity isolation has a significant effect on the result of test selection. In this paper, an improved test selection optimization model is proposed by considering the ambiguity degree of fault isolation. In the new model, the fault test dependency matrix is adopted to model the correlation between the system fault and the test group. The objective function of the proposed model is minimizing the test cost with the constraint of FDR and FIR. The improved chaotic discrete particle swarm optimization (PSO) algorithm is adopted to solve the improved test selection optimization model. The new test selection optimization model is more consistent with real complicated engineering systems. The experimental result verifies the effectiveness of the proposed method.

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Assessing the Impact of Virtual Reality-Based Training on Health and Safety Issues in the Mining Industry

Pedram¹,

Perez²,

Dowsett³

2014

Proceedings of the International Symposium for Next Generation Infrastructure

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Best practice in the mining industry includes extensive initial and professional training for staff involved in field operations. Whereas changes in mining technology and operations accelerate to improve productivity, health, and safety standards have to be continuously evaluated and improved, putting more pressure on training deliveries. Borrowing from Defence and Airspace industries, training in the mining industry is increasingly relying on immersive virtual reality to simulate complex operations and procedures in potentially dangerous environments. Coal Services Pty Ltd is at the forefront of modern training facilities in Australia. This paper presents a qualitative and quantitative research framework designed to analyse the impact of past and current training sessions on staff's ability to better perform their tasks, overall safety standards, and mine productivity. Interviews with trainees, trainers, and managers are used alongside session recordings to qualitatively evaluate levels of knowledge transfer and aptitudes to perform in a real environment. Then, a cost-benefit analysis is used to evaluate the added-value of virtual realitybased on technological and operational costs weighed against overall productivity of the mine being negatively affected by any safety issue.

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The Use of Interactive Simulations to Affect Driving Behaviour

Cited by 3 publications

References 11 publications

Impact of virtual training on safety and productivity in the mining industry

Impact of virtual training on safety and productivity in the mining industry

An Improved Test Selection Optimization Model Based on Fault Ambiguity Group Isolation and Chaotic Discrete PSO

Assessing the Impact of Virtual Reality-Based Training on Health and Safety Issues in the Mining Industry

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