Home // ACHI 2013, The Sixth International Conference on Advances in Computer-Human Interactions // View article
Authors:
Audrey Robinel
Didier Puzenat
Keywords: Instrumentation and Features Selection Using a Realistic Car Simulator in Order to Perform Efficient Single-User Drunkenness Analysis Blood Alcohol Content; Driving; Interface; Artificial Neural Networks; Intelligent systems; Machine learning; Instrumen
Abstract:
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.
Pages: 407 to 412
Copyright: Copyright (c) IARIA, 2013
Publication date: February 24, 2013
Published in: conference
ISSN: 2308-4138
ISBN: 978-1-61208-250-9
Location: Nice, France
Dates: from February 24, 2013 to March 1, 2013