The effects of automation and workload on driver performance, subjective workload, and mood

The effects of vehicle automation, drive difficulty, workload transitions, and subjective state on drivers' performance efficiency and mood were assessed. This combination of driving variables is likely to play a key role in automotive safety in the future as in-vehicle technologies increase. Two levels of drive difficulty (straight, curved) were combined factorially with three levels of vehicle-automation (manual, continuous-automation, intermittent-automation) to produce six experimental conditions (N = 20 per condition). In the straight roadway condition, road curvature was absent from the drive. The road in the curved condition was a continuous set of 's-curves,' which required participants to make constant steering inputs. Participants in the continuous-automation condition drove in a simulated automated vehicle, which controlled drivers' lateral position and longitudinal speed. Participants in the intermittentautomation condition drove in a mix of manual and automated vehicle control, which required frequent control transitions. Participants in the manual condition completed the drive without automated vehicle control. Performance during the experiment was assessed on several indices, including a monitoring task which required participants to detect pedestrian hazards. Participants completed the Driver Stress Inventory (DSI; Matthews, Desmond, Joyner, & Carcary, 1997) a measure of stress vulnerability in a driving context, the Dundee Stress State Questionnaire (DSSQ, Matthews, et al., 1999; 2002), a measure of subjective mood state, and the NASA-Task Load Index (TLX; Hart & Staveland, 1988), a measure of the perceived mental workload associated with a task. Results of the experiment indicated that curved roadways impaired driver performance, but did not influence workload. Automation facilitated performance, but the effect was transient and only observed in the continuous-automation condition. Automation did not reduce driver workload; perceived workload was actually elevated in the intermittent-automation condition. Workload transition effects were found to relate to impaired lateral vehicle control, and increased driver errors. Several DSI factors and DSSQ task engagement were found to be predictive of post-task subjective state and several indices of task performance. Overall, results indicated that vehicle automation may facilitate driver performance, but transitions between manual and automated vehicle control may pose substantial safety risks. Human factors implications and solutions are discussed.