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The research in advanced driver assistance systems (ADAS) has progressed to design architectures for driver specific performance. Personalised ADASs in this aspect have been developed with adaptation to driver attributes, state, style, behaviour, skill and so on. For the lane keeping task, the driver driving style while navigating a high/low curvature track plays an important part in the design of a lane keeping assist system. Considering this aspect, a robust co-operative control approach is formulated to design a personalised lane keeping assist with adaptation to driver style. Based on statistical analysis of lateral jerk and steer feel, a fuzzy rule based identification procedure for the classification of the driver style as clam, moderate, aggressive or very aggressive is designed. Using the identified driving style, a modulation function is proposed to adapt the assist torque. The assist torque is generated based on a robust higher order sliding mode approach as a feedback control for the driver-vehicle system. Closed-loop stability of the proposed driver-vehicle design in the presence of disturbances is established. Co-operative control between human driver-autonomous controller for the lane keeping task over the Satory test track with adaption to driver style is then shown for validation of the proposed architecture.

In this work, a human-centred steering assist controller based on dynamic allocation of control authority between driver and automatic e-copilot has been proposed for lane keeping systems. Cooperative control between driver and steering assist controller is addressed taking into consideration human driving behaviour. The vehicle steering controller for lane keeping is designed using a driver model for representation of the conflict between the driver and the controller. The steering controller is designed employing the integrated driver-vehicle model using Takagi-Sugeno control technique coupled with Lyapunov stability tools. The proposed design is robust to longitudinal speed variations and involves a trade-off between the lane following performance and ratio of negative system interference. The proposed approach was implemented on dynamic vehicle simulator SHERPA and the results presented in this study demonstrate the effectiveness of the proposed structure for cooperative control action between human driver and the steering assistance system. Based on indices such as energies spent by driver, driver satisfaction level and contradiction level between driver and autonomous controller the proposed optimal approach shows 93.48% and 89.30% reductions in expended driver energy and contradiction levels. Further, the satisfaction level of driver increased by 67.80% while performing a lane change manoeuvre.