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Real-Time Adaptation of Driving Time and Rest Periods in Automated Long-Haul Trucking : Development of a System Based on Biomathematical Modelling, Fatigue and Relaxation Monitoring

Ahlström, Christer, 1977- (author)
Linköpings universitet,Statens väg- och transportforskningsinstitut,Människan i transportsystemet, MTS,Avdelningen för medicinsk teknik,Tekniska fakulteten,Swedish Natl Rd & Transport Res Inst VTI, S-58195 Linkoping, Sweden
van Leeuwen, Wessel (author)
Stockholms universitet,Stressforskningsinstitutet,Stockholm University, Sweden,Stockholm Univ, Sweden
Krupenia, Stas (author)
Scania CV AB, Sweden
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Jansson, Herman (author)
Smart Eye AB, Sweden
Finér, Svitlana (author)
Smart Eye AB, Sweden
Anund, Anna, 1964- (author)
Linköpings universitet,Statens väg- och transportforskningsinstitut,Människan i transportsystemet, MTS,Avdelningen för prevention, rehabilitering och nära vård,Medicinska fakulteten,Swedish Natl Rd & Transport Res Inst VTI, S-58195 Linkoping, Sweden; Stockholm Univ, Sweden
Kecklund, Göran (author)
Stockholms universitet,Stressforskningsinstitutet,Stockholm University, Sweden,Stockholm Univ, Sweden
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 (creator_code:org_t)
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2022
2022
English.
In: IEEE transactions on intelligent transportation systems (Print). - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1524-9050 .- 1558-0016. ; 23:5, s. 4758-4766
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Hours of service regulations govern the working hours of commercial motor vehicle drivers, but these regulations may become more flexible as highly automated vehicles have the potential to afford periods of in-cab rest or even sleep while the vehicle is moving. A prerequisite is robust continuous monitoring of when the driver is resting (to account for reduced time on task) or sleeping (to account for the reduced physiological drive to sleep). The overall aims of this paper are to raise a discussion of whether it is possible to obtain successful rest during automated driving, and to present initial work on a hypothetical data driven algorithm aimed to estimate if it is possible to gain driving time after resting under fully automated driving. The presented algorithm consists of four central components, a heart rate-based relaxation detection algorithm, a camera-based sleep detection algorithm, a fatigue modelling component taking time awake, time of day and time on task into account, and a component that estimates gained driving time. Real-time assessment of driver fitness is complicated, especially when it comes to the recuperative value of in-cab sleep and rest, as it depends on sleep quality, time of day, homeostatic sleep pressure and on the activities that are carried out while resting. The monotony that characterizes for long-haul truck driving is clearly interrupted for a while, but the long-term consequences of extended driving times, including user acceptance of the key stakeholders, requires further research.

Subject headings

SAMHÄLLSVETENSKAP  -- Psykologi (hsv//swe)
SOCIAL SCIENCES  -- Psychology (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Farkostteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Vehicle Engineering (hsv//eng)
SAMHÄLLSVETENSKAP  -- Psykologi -- Tillämpad psykologi (hsv//swe)
SOCIAL SCIENCES  -- Psychology -- Applied Psychology (hsv//eng)

Keyword

sleep
vehicles
fatigue
heart rate variability
regulation
automobiles
real-time systems
hours of service regulations
fatigue modelling
relaxation detection
sleep detection
vehicle automation
truck
psykologi
Psychology

Publication and Content Type

ref (subject category)
art (subject category)

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