The increasing automation of road transport promises significant safety improvements. However, the transition from automated to manual control at SAE Levels 2 and 3 poses critical safety challenges, particularly during Take-Over Requests (TORs). Understanding the factors influencing Take-Over Time (TOT) is crucial for ensuring effective and safe driver responses, especially under varying road, traffic, and Human-Machine Interface (HMI) conditions. This study systematically investigates how TOT is affected by road environments, traffic volumes, SAE levels, HMI designs, and TOR alerts. It also examines how TOT influences driving performance and safety metrics, such as, acceleration, lane position, and crash rates after TOR. Using the PRISMA framework, 51 studies were systematically reviewed. Meta-regression and sensitivity analyses were conducted to quantify the effects of key factors on TOT. Heads-Up Displays (–14.8 %), TOR alerts (–64.7 %), and higher traffic volumes (–10.8 % per increase from free flow to high traffic volume) were associated with shorter TOT, while urgent TORs (+36.7 %), unequal gender distribution (+14.3 %), increased time budgets (+1.8 % per second), and additional lanes (+14.2 % per lane) were associated with longer TOT. TOT varied significantly across road types and traffic volumes, with highways exhibiting longer TOT and high traffic volumes resulting in shorter TOT, likely due to heightened driver attentiveness. Driving performance metrics revealed significant correlations between shorter TOT and higher maximum longitudinal and lateral accelerations, greater lane variability, and a moderate increase in crash rates, highlighting potential safety concerns. This study highlights the critical role of adaptive systems tailored to specific driving contexts, road conditions, and automation levels.
| ID | pj264 |
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