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The introduction of automated driving systems raised questions about how the human driver interacts with the auto-mated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its coun-terpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This pa-per describes the modelling of a human driver’s steering interac-tion with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is ad-opted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated sys-tem’s steering performance. It is found that when a driver inter-acts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her perform-ance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation co-operative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s ad-option of non-cooperative Nash strategy. This in t enables the vehicle to ret from a lane-change maneuver to straight-line driving swifter.