Modeling takeover time based on non-driving-related task attributes in highly automated driving

This study aims to investigate the effects of non-driving-related tasks (NDRTs) on the transition of control in highly automated driving (HAD) by investigating the effects of NDRT physical, visual, and cognitive attributes during transition of control. A conceptual model of the takeover process is proposed by dividing this process into motor and mental reactions. A laboratory experiment was conducted to evaluate the effects of each NDRT attribute on the corresponding stage of the process of taking over control. A prediction model was developed using the results of multiple linear regression analysis. Additionally, a validation experiment with nine NDRTs and a baseline condition was conducted to determine the extent to which the developed model explains the takeover time for each NDRT condition. The results showed that the timing aspects of the transition of control in HAD largely consist of participant motor reactions that are affected by the physical attributes of NDRTs. •The proposed model of takeover categorized driver's reaction into motor and mental reaction.•A regression model approach was applied to estimate the time taken to takeover based on non-driving related task attributes.•A driving simulator study was conducted to validate the developed prediction model.•Physical attributes of non-driving related task have significant effect on motor reaction of takeover.•Gaze and cognitive attributes of non-driving related task have significant effect on mental reaction of takeover.