@article{ref1,
title="Drivers' visual-distracted take-over performance model and its application on adaptive adjustment of time budget",
journal="Accident analysis and prevention",
year="2021",
author="Li, Qingkun and Hou, Lian and Wang, Zhenyuan and Wang, Wenjun and Zeng, Chao and Yuan, Quan and Cheng, Bo",
volume="154",
number="",
pages="e106099-e106099",
abstract="There are certain situations that automated driving (AD) systems are still unable to handle, preventing the implementation of Level 5 AD. Thus, a transition of control, colloquially known as take-over of the vehicle, is required when the system sends a take-over request (TOR) upon exiting the operational design domain (ODD). An adaptive TOR along with good take-over performance requires adjusting the time budget (TB) to drivers' visual distraction state, adhering to a reliable visual-distraction-based take-over performance model. Based on a number of driving simulator experiments, the percentage of face orientation to distraction area (PFODA) and time to boundary at take-over timing (TTBT) were proposed to accurately evaluate the degree of visual distraction based on merely face orientation under naturalistic non-driving related tasks (NDRTs) and to evaluate take-over performance, respectively. In order to elucidate the safety boundary, this study also proposed an algorithm to set a suitable minimum value of the TTBT. Finally, a multiple regression model was built to describe the relationship among PFODA, TB and TTBT along with a corrected coefficient of determination of 0.748. Based on the model, this study proposed an adaptive TB adjustment method for the take-over system.<p /> <p>Language: en</p>",
language="en",
issn="0001-4575",
doi="10.1016/j.aap.2021.106099",
url="http://dx.doi.org/10.1016/j.aap.2021.106099"
}