I Drive My Car and My States Drive Me: Visualizing Driver's Emotional and Physical States
Journal
Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Type
journal article
Date Issued
2018
Author(s)
Abstract
Drivers' emotional and physical states have a big impact on their driving performance. New technological sensing methods are currently investigated and will soon allow to automatically detect the driver's state. Yet, how to communicate the detected state to the driver is less well understood. In an iterative design process, we developed two concepts to increase the driver's awareness of this issue:
(1) a dashboard which provides a continuous overview of four potentially safety-critical states, namely drowsiness, aggressiveness, high workload, and hypoglycaemia, and
(2) on-time warnings which alert the driver to an immediate safety risk. We then let 70 drivers experience both concepts in a driving simulation and collected their qualitative feedback in post-study interviews. We found that participants preferred to receive only safety-critical notifications of the driver's state but appreciated a progressive status indicator for easier interpretation. Based on our findings, we suggest first recommendations for visualizing driver's states.
(1) a dashboard which provides a continuous overview of four potentially safety-critical states, namely drowsiness, aggressiveness, high workload, and hypoglycaemia, and
(2) on-time warnings which alert the driver to an immediate safety risk. We then let 70 drivers experience both concepts in a driving simulation and collected their qualitative feedback in post-study interviews. We found that participants preferred to receive only safety-critical notifications of the driver's state but appreciated a progressive status indicator for easier interpretation. Based on our findings, we suggest first recommendations for visualizing driver's states.
Language
English
Keywords
Driver’s State
Qualitative Feedback
Visualization
Refereed
Yes
Publisher
ACM
Start page
198
End page
203
Official URL
Division(s)
Eprints ID
264554
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Name
3239092.3267102.pdf
Size
297.79 KB
Format
Adobe PDF
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