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Towards a Context-D...
Towards a Context-Dependent Multi-Buffer Driver Distraction Detection Algorithm
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- Ahlström, Christer, 1977- (författare)
- Statens väg- och transportforskningsinstitut,Linköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten,Människan i transportsystemet, MTS
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- Georgoulas, George (författare)
- Univ Patras, Greece; DataWise Data Engn LLC, GA 30318 USA,University of Patras
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- Kircher, Katja, 1973- (författare)
- Statens väg- och transportforskningsinstitut,Linköpings universitet,Psykologi,Filosofiska fakulteten,Människan i transportsystemet, MTS
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(creator_code:org_t)
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022
- 2022
- Engelska.
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1524-9050 .- 1558-0016. ; 23:5, s. 4778-4790
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This paper presents initial work on a context-dependent driver distraction detection algorithm called AttenD2.0, which extends the original AttenD algorithm with elements from the Minimum Required Attention (MiRA) theory. Central to the original AttenD algorithm is a time buffer which keeps track of how often and for how long the driver looks away from the forward roadway. When the driver looks away the buffer is depleted and when looking back the buffer fills up. If the buffer runs empty the driver is classified as distracted. AttenD2.0 extends this concept by adding multiple buffers, thus integrating situation dependence and visual time-sharing behaviour in a transparent manner. Also, the increment and decrement of the buffers are now controlled by both static requirements (e.g. the presence of an on-ramp increases the need to monitor the sides and the mirrors) as well as dynamic requirements (e.g., reduced speed lowers the need to monitor the speedometer). The algorithm description is generic, but a real-time implementation with concrete values for different parameters is showcased in a driving simulator experiment with 16 bus drivers, where AttenD2.0 was used to ensure that drivers are attentive before taking back control after an automated bus stop docking and depot procedure. The scalability of AttenD2.0 relative to available data sources and the level of vehicle automation is demonstrated. Future work includes expanding the concept to real-world environments by automatically integrating situational information from the vehicles environmental sensing and from digital maps.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Farkostteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Vehicle Engineering (hsv//eng)
Nyckelord
- Vehicles; Roads; Mirrors; Monitoring; Gaze tracking; Visualization; Computer vision; AttenD; classification; detection; driver distraction; driver state estimation; inattention
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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