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The main contribution of this article is the development of a controller for tracking of the driver intended path of an integrated driver/vehicle system. The controller receives heading and lateral deviation errors as well as the driver input and determines a corrective steering angle and a direct yaw moment to be applied to the vehicle so that a desired path is achieved. A genetic algorithm procedure is utilized in order to adapt a set of optimized controller parameters suitable for various driving styles, road conditions and the initial errors of vehicle position and orientation. The sensitivity of driver/ vehicle system response to the driver model, road and vehicle initial conditions is investigated. Computer simulations are performed to study the effectiveness of the proposed controller in different driving conditions, namely single-and double-lane changes, J-turn and other desired tracks. Simulation results demonstrated that the proposed controller was able to effectively keep the vehicle path very close to the desired path even in the presence of the driver commands.

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In accordance with the worldwide trend for developing energy-efficient vehicles and meeting environmental regulations, there exists a large potential for decreasing energy losses due to tyre rolling resistance and significantly reduce fuel consumption and greenhouse gas emissions and also improve tyre tread durability. To achieve a quantitative estimate of tyre rolling resistance force, in the present paper, we carry out rolling resistance modelling in order to introduce a comprehensive relation for predicting rolling resistance force variations with speed taking into account the most influential parameters. To accomplish this goal, full three-dimensional finite element modelling of a visco-hyperelastic inflated rubber tyre under the deformation of vertical loading is performed and validated by making use of available test data. Free rolling simulations are performed and rolling resistance diagrams at various vehicle speeds and inflation pressures are extracted by analysing the results. According to the simulation results, a general formula is suggested to predict the tyre rolling resistance force in terms of the influential factors such as velocity, inflation pressure and tyre load. Results obtained using the proposed equation compared with recorded coast down test data clearly indicate excellent agreement between the results, confirming the validity of the relation. The presented solution can be built into models for comprehensive techno-economic evaluation of vehicle performance and fuel economy where changes in velocity, load and inflation pressure can be considered.