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Combination and Selection of Traffic Safety Expert Judgments for the Prevention of Driving Risks

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Resumen

In this paper, we describe a new framework to combine experts’ judgments forthe prevention of driving risks in a cabin truck. In addition, the methodology shows how tochoose among the experts the one whose predictions fit best the environmental conditions.The methodology is applied over data sets obtained from a high immersive cabin trucksimulator in natural driving conditions. A nonparametric model, based in NearestNeighbors combined with Restricted Least Squared methods is developed. Three expertswere asked to evaluate the driving risk using a Visual Analog Scale (VAS), in order tomeasure the driving risk in a truck simulator where the vehicle dynamics factors werestored. Numerical results show that the methodology is suitable for embedding in real timesystems.

Palabras clave
driving risks
fusion of judgments
selection of experts
regression
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Esta obra se publica con la licencia Creative Commons Attribution 4.0 International (BY 4.0)

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