2022
DOI: 10.1007/s10010-021-00576-6
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Modeling driver-vehicle interaction in automated driving

Abstract: In automated vehicles, the collaboration of human drivers and automated systems plays a decisive role in road safety, driver comfort, and acceptance of automated vehicles. A successful interaction requires a precise interpretation and investigation of all influencing factors such as driver state, system state, and surroundings (e.g., traffic, weather). This contribution discusses the detailed structure of the driver-vehicle interaction, which takes into account the driving situation and the driver state to imp… Show more

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Cited by 9 publications
(5 citation statements)
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“…At the limit of 0, for both λ and ω, equation (17) will reduce to equation (16). This is due to the zero probability of failure.…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…At the limit of 0, for both λ and ω, equation (17) will reduce to equation (16). This is due to the zero probability of failure.…”
Section: Methodsmentioning
confidence: 99%
“…At ΔTprocessing = 0 and ΔTresponse = 0, and Pprocessing failure = 0  Equation (15) becomes equation (16).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…CLARION, on the other hand, outlines a cognitive architecture where modules for perception, action, motor functions, emotion, and goal synergistically interact to shape driver behavior. Considering insights from all three models results in a driver model that underpins the selection of pertinent driver state factors 25 . Human information processing takes place in three stages: sensory perception, decision-making, and motor response.…”
Section: Background and Summarymentioning
confidence: 99%
“…Human information processing takes place in three stages: sensory perception, decision-making, and motor response. The factors that determine the driver state are visual attention for sensory perception, emotion, attention, and workload for decision-making, and the driver’s activity and the position of body parts for motor response 25 . Table 2 offers a comprehensive overview of these driver state factors, the associated measuring sensors, and potential scaling features.…”
Section: Background and Summarymentioning
confidence: 99%