Real time drunkenness analysis in a realistic car simulation - Archive ouverte HAL Access content directly
Conference Papers Year : 2012

Real time drunkenness analysis in a realistic car simulation

Abstract

This paper describes a blood alcohol content estimation method for car driver, based on a comportment analysis performed within a realistic simulation. An artificial neural network learns how to estimate subject's blood alcohol content. Low-level recording of user actions on the steering wheel and pedals are used to feed a multilayer perceptron, and a breathalyzer is used to build the learning examples set (desired output). Results are compared with a successful previous work based on a simple video game and demonstrate the ''complexity scalability'' of the approach.
No file

Dates and versions

hal-00850136 , version 1 (03-08-2013)

Identifiers

  • HAL Id : hal-00850136 , version 1

Cite

Audrey Robinel, Didier Puzenat. Real time drunkenness analysis in a realistic car simulation. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2012, Bruges, Belgium. pp.85-90. ⟨hal-00850136⟩

Collections

UNIV-AG LAMIA
113 View
0 Download

Share

Gmail Facebook X LinkedIn More