Citation

Cabello E, Conde C, Diego IM, Moguerza JM, Redchuk A. Sensors (Basel) 2012; 12(11): 14711-14729.

Affiliation

Department of Computer Architecture, University Rey Juan Carlos, Móstoles 28933, Spain. enrique.cabello@urjc.es.

Copyright

(Copyright © 2012, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s121114711

PMID

23202184

Abstract

In this paper, we describe a new framework to combine experts’ judgments for the prevention of driving risks in a cabin truck. In addition, the methodology shows how to choose 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 truck simulator in natural driving conditions. A nonparametric model, based in Nearest Neighbors combined with Restricted Least Squared methods is developed. Three experts were asked to evaluate the driving risk using a Visual Analog Scale (VAS), in order to measure the driving risk in a truck simulator where the vehicle dynamics factors were stored. Numerical results show that the methodology is suitable for embedding in real time systems.

Language: en