| Issue |
E3S Web Conf.
Volume 253, 2021
2021 International Conference on Environmental and Engineering Management (EEM 2021)
|
|
|---|---|---|
| Article Number | 02054 | |
| Number of page(s) | 6 | |
| Section | Big Data Environment Management Application and Industry Research | |
| DOI | https://doi.org/10.1051/e3sconf/202125302054 | |
| Published online | 06 May 2021 | |
An execution time prediction model for crew information processing in new special vehicles
1 School of Aeronautic Science and Engineering Beihang University Beijing China
2 School of Aeronautic Science and Engineering Beihang University Beijing China
3 School of Aeronautic Science and Engineering Beihang University Beijing China
4 China North Industries Group Corporation Limited China North Vehicle Research Institute Beijing China
5 China North Industries Group Corporation Limited China North Vehicle Research Institute Beijing China
a zy1805305@buaa.edu.cn
b* Corresponding author: liushuangbh@163.com
c 13121252759@163.com
d christie_xie@163.com
e clubjully@sina.cn
Task execution time prediction modeling is of great significance to the safety of special vehicle crew and maintenance of overall combat effectiveness. In our study, a task execution time prediction model for crew information processing task is proposed considering the characteristics of information processing task, as well as the interaction mode of man-machine system of special vehicles. In addition, a model validation experiment was conducted adopting 20 subjects facing to two kinds of representative tasks, and both of them have two levels of complexities. The result shows that there is a highly positive correlation (r = 0.999, p = 0.001) between the model prediction and the experimental results of four tasks, which indicates that the model has a good applicability. Based on the rationality of model validation, the application research of the model was conducted. The result shows that for the sub-tasks with more objects and visual searching difficulty, the speech interaction mode can reduce the operation duration to a great extent; for simple subtasks with less operation steps and strong coherence, the touch interaction mode has certain advantages.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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