Evaluating the impacts of situational awareness and mental stress on takeover performance under conditional automation |
| |
| Affiliation: | 1. Department of Sociology, Anthropology and Criminal Justice, Clemson University, Clemson, SC, United States;2. School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, United States;1. Daimler AG, Research and Development, Hanns-Klemm-Str. 45, D-71032 Böblingen, Germany;2. Heinrich Heine University Düsseldorf, Department of Experimental Psychology, Universitätsstr. 1, D-40225 Düsseldorf, Germany;1. Chair of Ergonomics, Technical University of Munich, Munich, Germany;2. Department Intelligent Vehicles, Delft University of Technology, Delft, The Netherlands;1. Human-centered Mobility Research Center, National Institute of Advanced Industrial Science and Technology, Japan;2. DENSO CORPORATION, Japan;1. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Beijing 100191, China;2. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University Road #2, Nanjing 211189, China;3. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;4. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China |
| |
| Abstract: | Several safety concerns emerge for the transition of control from the automated driving system to a human driver after the vehicle issues a takeover warning under conditional vehicle automation (SAE Level 3). In this context, recent advances in in-vehicle driver monitoring systems enable tracking drivers’ physiological indicators (e.g., eye-tracking and heart rate (HR) measures) to assess their real-time situational awareness (SA) and mental stress. This study seeks to analyze differences in driver’s SA and mental stress over time (i.e., successive experiment runs) using these physiological indicators to assess their impacts on takeover performance. We use eye-tracking measures (i.e., on-road glance rate and road attention ratio) as indicators of driver’s SA during automated driving. Further, we use the pre-warning normalized HR (NHR) and HR variability (HRV) as well as the change in NHR and HRV after the takeover warning as indicators of mental stress immediately before and the change in mental stress after the takeover warning, respectively. To analyze the effects of driver state (in terms of SA and mental stress) on the overall takeover performance, this study uses a comprehensive metric, Takeover Performance Index (TOPI), proposed in our previous work (Agrawal & Peeta, 2021). The TOPI combines multiple driving performance indicators while partly accounting for their interdependencies. Results from statistical analyses of data from 134 participants using driving simulator experiments illustrate significant differences in driver state over successive experiment runs, except for the change in mental stress after the takeover warning. Some significant correlations were found between the physiological indicators of SA and mental stress used in this study. Takeover performance model results illustrate a significant negative effect of change in NHR after the takeover warning on the TOPI. However, none of the other physiological indicators show significant impacts on takeover performance. The study findings provide valuable insights to auto manufacturers for designing integrated in-vehicle driver monitoring and warning systems that enhance road safety and user experience. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
