Systematically modeling take-over performance: Considering the indirect effect of meteorological visibility mediated by drivers’ attention

Abstract

Drivers’ take-over performance in conditionally automated driving is simultaneously affected by multiple factors, making the involved causal relationships complex. Although existing studies have explored the mechanism, there is still a lack of models for comprehensively analyzing drivers’ take-over performance under diverse meteorological visibility and take-over time budget (TB) conditions. This study established a structural equation model to systematically investigate the complicated causal relationships among TB, meteorological visibility, drivers’ attention, and take-over performance. Based on a driving simulation experiment, we developed a measurement model of drivers’ attention and take-over performance via confirmatory factor analysis. We deconstructed take-over performance into three aspects: reaction time, control instability, and safety margin. Subsequently, we revealed the causal relationships among the above factors by using path analysis. Our results demonstrated the significant total effects of meteorological visibility on reaction time and safety margin, where the indirect effects are mediated by drivers’ attention. However, we found that meteorological visibility barely impacts the control instability aspect of take-over performance. Moreover, the direct effects of TB and drivers’ attention on take-over performance were substantial. This study reveals the complex mechanism of take-over performance under diverse conditions and provides a theoretical basis for enhancing the safety and user experience of conditionally automated vehicles.