2009KTH Publication Database DiVA (KTH Royal Institute of Technology)Open access

Issues related to the driver distraction detection algorithm AttenD

Katja Kircher, Christer Ahlström

Open full text 37 citations

Abstract

Driver distraction is a contributing factor to many crashes and a real-time distraction warning system has the potential to mitigate or circumvent many of these crashes. The objective of this paper is to thoroughly describe the distraction detection algorithm AttenD and explain the theory underlying different design choices. Future aspects and distraction warning strategies will be discussed as well. In summary, AttenD is an eye-tracker based distraction detection algorithm which identifies visual distraction in real-time based on single long glances as well as repetitive glances. The core idea of the algorithm is a 2-second time buffer which is decremented when the driver looks away from the road and incremented when the driver looks back at the road. If the buffer runs empty, the driver’s state is classified as distracted.

About this research paper

What this paper is about

Driver distraction is a contributing factor to many crashes and a real-time distraction warning system has the potential to mitigate or circumvent many of these crashes. The objective of this paper is to thoroughly describe the distraction detection algorithm AttenD and explain the theory underlying different design choices. Future aspects and distraction warning strategies will be discussed as well. In summary, AttenD is an eye-tracker based distraction detection algorithm which identifies visual distraction in real-time based on single long glances as well as repetitive glances. The core idea of the algorithm is a 2-second time buffer which is decremented when the driver looks away from the road and incremented when the driver looks back at the road. If the buffer runs empty, the driver’s state is classified as distracted.

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OpenAlex reports 37 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Driver distraction is a contributing factor to many crashes and a real-time distraction warning system has the potential to mitigate or circumvent many of these crashes. The objective of this paper is to thoroughly describe the distraction detection algorithm AttenD and explain the theory underlying different design choices. Future aspects and distraction warning strategies will be discussed as well. In summary, AttenD is an eye-tracker based distraction detection algorithm which identifies visual distraction in real-time based on single long glances as well as repetitive glances. The core idea of the algorithm is a 2-second time buffer which is decremented when the driver looks away from the road and incremented when the driver looks back at the road. If the buffer runs empty, the driver’s state is classified as distracted.

Key concepts: Distraction, Distracted driving, Computer science, Computer security, Psychology, Cognitive psychology

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