4.7 Article

Modeling takeover behavior in level 3 automated driving via a structural equation model: Considering the mediating role of trust

Journal

ACCIDENT ANALYSIS AND PREVENTION
Volume 157, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.aap.2021.106156

Keywords

Level 3 automation; Simulator experiment; Takeover behavior variation; Trust; Structural equation modeling

Funding

  1. National Natural Science Foundation of China [U1664262]
  2. National Key R&D Program of China [2018YFB1600500]

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This study used a structural equation model to analyze the variation in drivers' takeover performance in Level 3 automated vehicles, revealing the complex relationships among takeover time budget, trust, driver characteristics, environmental characteristics, and vehicle characteristics. The findings emphasized the crucial role of trust in the change in takeover behavior and highlighted the importance of subjective trust level and monitoring strategy in the function design of takeover process.
The takeover process in level 3 automated driving determines the controllability of the functions of automated vehicles and thereby traffic safety. In this study, we attempted to explain drivers' takeover performance variation in a level 3 automated vehicle in consideration of the effects of trust, system characteristics, environmental characteristics, and driver characteristics with a structural equation model. The model was built by incorporating drivers' takeover time and quality as endogenous variables. A theoretical framework of the model was hypothesized on the basis of the ACT-R cognitive architecture and relevant research results. The validity of the model was confirmed using data collected from 136 driving simulator samples under the condition of voluntary non-driving-related tasks. Results revealed that takeover time budget was the most critical factor in promoting the safety and stability of takeover process, which, together with traffic density, drivers' age and manual driving experience, determined drivers' takeover quality directly. In addition, the pre-existing experience with an automated system or a similar technology and self-confidence of the driver, as well as takeover time budget, strongly influenced the takeover time directly. Apart from the direct effects mentioned above, trust, as an intermediary variable, explained a major portion of the variance in takeover time. Theoretically, these findings suggest that takeover behavior could be comprehensively evaluated from the two dimensions of takeover time and quality through the combination of trust, driver characteristics, environmental characteristics, and vehicle characteristics. The influence mechanism of the above factors is complex and multidimensional. In addition to the form of direct influence, trust, as an intermediary variable, could reflect the internal mechanism of the takeover behavior variation. Practically, the findings emphasize the crucial role of trust in the change in takeover behavior through the dimensions of subjective trust level and monitoring strategy, which may provide new insights into the function design of takeover process.

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