User-Centric Intelligibility of Autonomous Vehicles (HCIK 2018, A.I. Basic Research)
User-Centric Intelligibility of Autonomous Vehicles (HCIK 2018, A.I. Basic Research)
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Goal
Goal
Exploring the modality that positively influenced the driver’s attitude when providing the combination of ‘Why message’ (e.g. construction site) and ‘How message’ (e.g. decrease driving speed) according to the behavior of the vehicle in the autonomous driving situation.
Procedure
Procedure
Design contextual message types, scenario-specific modality distribution and different messages by notification type
Provide messages to autonomous HVI (Human-Vehicle Interaction) test bed according to four kinds of situations and scenarios
Interim-Q for measurement of driver’s attitude (driver’s feeling and vehicle reliability)
Measurement of Eye-tracking, physiological data
Result
Result
Driver’s attitude index is low when ‘How message’ is not provided --> Negative emotions and credibility
‘How’ message shows the most positive response when visual + auditory message is given
Show less active eye tracking despite plenty of information (visual > visual + auditory)
--> Positive results are shown without much visual load compared to the driver’s attitude index
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