Automation effects on driver's behaviour when integrating a PADAS and a distraction classifier

Authors:
Fabio Tango;Luca Minin;Raghav Aras;Olivier Pietquin
Affiliations:
Centro Ricerche Fiat, Orbassano, Italy and University of Modena & Reggio Emilia, Reggio Emilia, Italy and IMS Supélec, Metz, France;Centro Ricerche Fiat, Orbassano, Italy and University of Modena & Reggio Emilia, Reggio Emilia, Italy and IMS Supélec, Metz, France;Centro Ricerche Fiat, Orbassano, Italy and University of Modena & Reggio Emilia, Reggio Emilia, Italy and IMS Supélec, Metz, France;Centro Ricerche Fiat, Orbassano, Italy and University of Modena & Reggio Emilia, Reggio Emilia, Italy and IMS Supélec, Metz, France
Venue:
ICDHM'11 Proceedings of the Third international conference on Digital human modeling
Year:
2011

Citing 2
Cited 0

Non-intrusive Detection of Driver Distraction using Machine Learning Algorithms

Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Real-Time Detection of Driver Cognitive Distraction Using Support Vector Machines

IEEE Transactions on Intelligent Transportation Systems

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Abstract

The FP7 EU project ISi-PADAS aims at conceiving an intelligent system, called PADAS, to support drivers, which intervenes continuously from warning up to automatic braking in the whole longitudinal control of the vehicle. However, such supporting systems can have some unwanted side-effect: due to the presence of automation in the driving task, less attention and reaction are needed by the drivers to intervene in the longitudinal control of the vehicle. Such a paper aims at investigating the effects of the level of automation on drivers, in particular on their Situation Awareness, when the user is supported by a specific PADAS application, integrated with a driver's distraction classifier.