A workload adaptive haptic shared control scheme for semi-autonomous driving

• We develop a shared control scheme that adapts to the human operator's workload in real time. propose heuristic design of adaptive based on factors theories. estimate operators’ by using HMM analyze their gaze trajectory. The haptic results significantly lower workload, higher trust autonomy, better driving task performance and smaller effort. Haptic is used manage authority allocation between an autonomous agent semi-autonomous driving. Existing schemes, however, do not take full consideration agent. To fill this research gap, study presents eyes road input torque conducted human-in-the-loop experiments with 24 participants. In experiment, operator autonomy module for navigation simulated notional High Mobility Multipurpose Wheeled Vehicle (HMMWV) at fixed speed. At same time, performed target detection task. could be either or non-adaptive above-mentioned factors. Results indicate resulted