Young Drivers Fatigue Development and Takeover Behaviors under Level 2.5 Automated Driving with Different Workload

Abstract

Vehicle crashes are the leading cause of death and injury for teens. However, only a limited number of studies have assessed the drivers’ fatigue status and takeover behaviors during semi-automated driving, especially for young drivers. This study measured fatigue development and takeover behavior based on drivers’ ages, workload, and driving mode. A total of five research hypotheses were investigated in this study: First, young drivers might develop fatigue faster and more severely compared with adult drivers for both automated driving and manual driving. Second, young drivers’ fatigue development was expected to be more severe under manual high workload compared with manual low workload. Third, young drivers’ fatigue development was expected to be more severe under automated compared with manual driving. Fourth, young drivers’ fatigue development was expected to be more severe under automated low workload compared with automated high workload. Last, young drivers’ takeover performance was expected to be worse than that of adult drivers. Two studies were conducted to research the fatigue and takeover differences among young drivers and other driver groups. Study one was performed to understand if young drivers are different from adult new drivers in fatigue development and takeovers, 9 participants were recruited for the study. Study two performed statistical hypotheses testing between young drivers and adult drivers on fatigue development and takeover behaviors, 32 participants were recruited for the study. A 2 by 2 by 3 design with 2 levels of driving modes, 2 levels of workloads, and 3 levels of participant groups was used for study one. A 2 by 2 by 2 design with 2 levels of driving modes, 2 levels of workloads, and 2 levels of participant groups was used for study two. Electroencephalography (EEG), heart rate variability (HRV), video recording, and perceived fatigue and discomfort questionnaires were used to measure the fatigue and takeover behavior in this study. Analysis of variance (ANOVA) and Kruskal-Wallis were used to test the hypotheses in this study. Study one found that adult new drivers are not significantly different from adult experienced drivers. They both develop fatigue more slowly and have better takeover performance compared with young drivers. Results from study two confirmed four out of five hypotheses: young drivers develop fatigue faster and more severely compared with adult drivers for both automated driving and manual driving; young drivers’ fatigue development was more severe under automated driving mode compared with manual driving mode; young drivers’ fatigue, especially mental fatigue was more severe under automated low workload compared with automated high workload; and young drivers’ takeover performance was worse than adult drivers. HRV data were not used to conclude this study since the breathing pattern may have an impact on HRV and cause inaccurate results. EEG data were used only for study one due to the difficulties in cleaning the equipment. Future works should focus on statistical tests on study one to confirm that adult new drivers were statistically different from young drivers in fatigue development and takeover performance. Participants should be guided on their breathing while they are driving in order to use the HRV analysis. Also, more participants could be recruited to perform factorial ANOVA to analyze the interactions between the main effects.