Literature DB >> 25794922

What determines the take-over time? An integrated model approach of driver take-over after automated driving.

Kathrin Zeeb1, Axel Buchner2, Michael Schrauf3.   

Abstract

In recent years the automation level of driver assistance systems has increased continuously. One of the major challenges for highly automated driving is to ensure a safe driver take-over of the vehicle guidance. This must be ensured especially when the driver is engaged in non-driving related secondary tasks. For this purpose it is essential to find indicators of the driver's readiness to take over and to gain more knowledge about the take-over process in general. A simulator study was conducted to explore how drivers' allocation of visual attention during highly automated driving influences a take-over action in response to an emergency situation. Therefore we recorded drivers' gaze behavior during automated driving while simultaneously engaging in a visually demanding secondary task, and measured their reaction times in a take-over situation. According to their gaze behavior the drivers were categorized into "high", "medium" and "low-risk". The gaze parameters were found to be suitable for predicting the readiness to take-over the vehicle, in such a way that high-risk drivers reacted late and more often inappropriately in the take-over situation. However, there was no difference among the driver groups in the time required by the drivers to establish motor readiness to intervene after the take-over request. An integrated model approach of driver behavior in emergency take-over situations during automated driving is presented. It is argued that primarily cognitive and not motor processes determine the take-over time. Given this, insights can be derived for further research and the development of automated systems.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Keywords:  Automated driving; Driver distraction; Driver take-over; Driving simulator; Eye movements; Visual attention

Mesh:

Year:  2015        PMID: 25794922     DOI: 10.1016/j.aap.2015.02.023

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  4 in total

1.  The effect of varying levels of vehicle automation on drivers' lane changing behaviour.

Authors:  Ruth Madigan; Tyron Louw; Natasha Merat
Journal:  PLoS One       Date:  2018-02-21       Impact factor: 3.240

Review 2.  Underload on the Road: Measuring Vigilance Decrements During Partially Automated Driving.

Authors:  Thomas McWilliams; Nathan Ward
Journal:  Front Psychol       Date:  2021-04-15

3.  How Does Approaching a Lead Vehicle and Monitoring Request Affect Drivers' Takeover Performance? A Simulated Driving Study with Functional MRI.

Authors:  Chimou Li; Xiaonan Li; Ming Lv; Feng Chen; Xiaoxiang Ma; Lin Zhang
Journal:  Int J Environ Res Public Health       Date:  2021-12-31       Impact factor: 3.390

4.  Westdrive X LoopAR: An Open-Access Virtual Reality Project in Unity for Evaluating User Interaction Methods during Takeover Requests.

Authors:  Farbod N Nezami; Maximilian A Wächter; Nora Maleki; Philipp Spaniol; Lea M Kühne; Anke Haas; Johannes M Pingel; Linus Tiemann; Frederik Nienhaus; Lynn Keller; Sabine U König; Peter König; Gordon Pipa
Journal:  Sensors (Basel)       Date:  2021-03-08       Impact factor: 3.576

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.