untitled
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<identifier>oai:HAL:hal-00850137v1</identifier>
<datestamp>2017-12-21</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Instrumentation and Features Selection Using a Realistic Car Simulator in Order to Perform Efficient Single-User Drunkenness Analysis</title>
<creator>Robinel, Audrey</creator>
<creator>Puzenat, Didier</creator>
<contributor>Laboratoire de Mathématiques Informatique et Applications (LAMIA) ; Université des Antilles et de la Guyane (UAG)</contributor>
<contributor>Groupe de Recherche en Informatique et Mathématiques Appliquées Antilles-Guyane (GRIMAAG) ; Université des Antilles et de la Guyane (UAG)</contributor>
<description>International audience</description>
<source>Proceedings of ACHI 2013, The Sixth International Conference on Advances in Computer-Human Interactions</source>
<source>ACHI 2013, The Sixth International Conference on Advances in Computer-Human Interactions</source>
<coverage>Nice, France</coverage>
<identifier>hal-00850137</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00850137</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00850137</source>
<source>ACHI 2013, The Sixth International Conference on Advances in Computer-Human Interactions, Feb 2013, Nice, France. pp.407-421, 2013</source>
<language>en</language>
<subject lang=en>Blood Alcohol Content</subject>
<subject lang=en>Driving</subject>
<subject lang=en>Interface</subject>
<subject lang=en>Artificial Neural Networks</subject>
<subject lang=en>Intelligent systems</subject>
<subject lang=en>Machine learning</subject>
<subject lang=en>Instrumentation</subject>
<subject>[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]</subject>
<type>info:eu-repo/semantics/conferenceObject</type>
<type>Conference papers</type>
<description lang=en>We instrumented a car simulator by gathering low level data and fed it to an artificial neural network in order to perform blood alcohol content (BAC) estimations. The results depend on the quality of the data extraction and processing, and also on the selected inputs. We explain our data extraction and processing methodology, and how we used it to generate reliable and comparable features. At last, we describe the performances of individual features and how they combine. In the end, the prototype was able to accurately estimate the BAC value of a subject after being trained with driving samples of this subject with various BAC values.</description>
<date>2013-02-24</date>
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