Abstract
The use of touchscreen-based in-vehicle information systems (IVIS) is increasing. To ensure safe driving, it is important to evaluate IVIS task performance during driving situations. Therefore, we proposed a model to assess the task completion time (TCT) of IVIS tasks while driving using a keystroke-level modeling (KLM) technique. The basic assumptions and heuristic rules of driver behaviors were considered. In addition, based on the characteristics of visual and manual IVIS interactions, we determined the basic unit operators (i.e., visual, manual, and mental operators). User experiments were conducted to determine the individual execution times of unit tasks and to measure the TCT of IVIS tasks while driving. Based on the heuristic rules for model development and individual task execution times, we derive a predictive model for the TCT of IVIS tasks. We used a regression analysis to validate the modeling procedure, showing that the observed TCT was found to have a strong positive correlation with the predicted time from the modeling process. The findings showed that the task completion time needed to perform a secondary task in a driving context can be predicted by KLM. This study provides meaningful insights into the design of touchscreen-based IVIS to enhance driving safety.
| Original language | English |
|---|---|
| Pages (from-to) | 252-260 |
| Number of pages | 9 |
| Journal | International Journal of Industrial Ergonomics |
| Volume | 72 |
| DOIs | |
| State | Published - Jul 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Human performance modeling
- In-vehicle information system (IVIS)
- Keystroke level modeling (KLM)
- Touchscreen
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