Drivers' visual-distracted take-over performance model and its application on adaptive adjustment of time budget

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.

Automated summary

This study focuses on the issue of visual distraction during take-over in automated driving systems, proposing an evaluation method based on face orientation and implementing adaptive time budget adjustment through a regression model.