This paper presents a novel adaptive multiple-model predictive control (MPC) scheme for Four-Wheel Independent Drive (4WID) autonomous vehicles with a holistic structure. Firstly, the combined vehicle-path model is established. To ensure the real-time performance of MPC, the coupling relationships in the control output and the longitudinal/lateral motions are well decoupled, in this way a linear integrated model is utilized as the internal model of the controller. Then, the holistic MPC is proposed to acquire the steering angle and the force on each corner. Based on the advantages of the proposed structure, a weight adaptive mechanism is introduced to improve the handling ability of the controller to various driving conditions, especially some extreme conditions. For the uncertainties in tire cornering stiffness, a multiple-model adaptive law is designed with its convergence proved by Lyapunov theory. Numerical results based on Carsim-Simulink co-simulation platform demonstrate the effectiveness and superiority of the proposed control method in both normal and extreme driving conditions.

Trajectory tracking and stability control are two essential functions of autonomous vehicles, and there is inevitable mutual interference between them, especially under extreme conditions. Towards addressing this challenge, this paper proposes a novel cooperative strategy of trajectory tracking and stability control for four-wheel independent drive (4WID) autonomous vehicles. An adaptive trajectory tracking controller is designed based on the model predictive control (MPC) theory, in which the tire cornering stiffness is modified in real-time leverages the lateral force estimated by the square-root cubature Kalman filter (SCKF). Then, the vehicle stability controller is designed based on the sliding mode control (SMC), in which the tire force saturation constraint and the relative weight of yaw rate and sideslip angle are considered. Furthermore, a weight adaptive criterion with normalized stability index is defined to develop the cooperative strategy of trajectory tracking and stability control. The feasibility and adaptability of the proposed method to different extreme conditions are verified by hardware-in-the-loop (HIL) test and CarSim-Simulink co-simulation. Finally, an experimental case is presented to demonstrate the realizability of the proposed method.

Aiming at the difficulty of vehicle lateral control in high-speed condition, a comprehensive control method that integrates active steering (AS) and direct yaw moment control (DYC) systems is proposed for four-wheel independent driving and four-wheel independent steering (4WID/4WIS) vehicle. According to the characteristics of lateral dynamics in high-speed conditions, different principles are adopted in different steering conditions. In a slight or moderate steering, a decoupling control method is proposed, and a penalty function is used to allocate the involvement of AS and DYC for the over-actuated characteristics of 4WID/4WIS vehicle. While in a large steering, based on sideslip phase plane, handling-oriented and stability-oriented control are proposed in order to realise a fine trade-off between handling and stability performance. A transient layer is introduced in the phase plane to further improve the performance of this controller. And the allocation of active yaw moment is also discussed. Simulation results demonstrate that the proposed integrated control method can effectively improve the lateral dynamics performance of the vehicle in high-speed condition as compared to previous control methods.

In the research of autonomous vehicles, most existing studies treat the decision/planning and control as two separate problems. This idea originates from robotics. But since there are essential differences between robot and autonomous vehicle, the structure in Robotics may not be suitable for autonomous vehicles. Considering decision/planning and control separately may affect the performance of autonomous vehicle under complex driving conditions. To fill in the research gap, this paper proposes a novel scheme which considers the local motion planning and control in a combined manner. Firstly, the local motion planning is transformed into the longitudinal control problem based on the proposed scenario adaptive MPC, by which the motion behavior (driving along the global path, car-following, lane-change) can be automatically decided. Then, the lateral MPC controller is designed to track the global path and conduct the local motion commands. To ensure the performance of the path tracking control and a smooth lane-change process simultaneously, an adaptive weight mechanism is introduced in the lateral controller. Comprehensive case studies including both straight and curve road are conducted based on Carsim-Simulink co-simulation platform. The results show that the proposed algorithm can not only ensure the vehicle safety in complex driving conditions, but also ensure that the vehicle can drive at its desired velocity as much as possible by intelligently judging the most proper motion behaviors.

In order to identify the road friction coefficient of the left and right sides of the vehicle more accurately, this paper presents an estimation framework based on a novel tyre model and modified square-root cubature Kalman filter (SCKF). To begin with, a novel tyre model is proposed by adaptively calculating the longitudinal and lateral stiffness and the effective friction coefficient. The tyre forces calculated by this model are more accurate than those calculated by the Brush model. Then, to avoid the influence of abnormal measurement noise on the estimation effect, we develop an improved SCKF (ISCKF) algorithm based on the maximum correntropy criterion. The algorithm can update the measurement noise covariance adaptively. Furthermore, a real-time estimation scheme of road friction coefficient is designed by combining the vehicle dynamics model with the proposed novel tyre model and ISCKF algorithm. Finally, the performance of the presented method is verified by the co-simulation of CarSim and MATLAB/Simulink. The results show that the designed estimation scheme not only has excellent robustness in the case of abnormal measurement noise interference but also has good adaptability to the uncertainty of road friction coefficients distribution.

The vehicle stability involves many aspects, such as the anti-rollover stability in extreme steering operations and the vehicle lateral stability in normal steering operations. The relationships between vehicle stabilities in extreme and normal circumstances obtain less attention according to the present research works. In this paper, the coupling interactions between vehicle anti-rollover and lateral stability, as well as the effect of road excitation, are taken into account on the vehicle rollover analysis. The results in this paper indicate that some parameters influence the different vehicle stabilities diversely or even contradictorily. And it has been found that there are contradictions between the vehicle rollover mitigation performance and the lateral stability. The direct cause for the contradiction is the lateral coupling between tyres and road. Tyres with high adhesion capacity imply that the vehicle possesses a high performance ability to keep driving direction, whereas the rollover risk of this vehicle increases due to the greater lateral force that tyres can provide. Furthermore, these contradictions are intensified indirectly by the vertical coupling between tyres and road. The excitation from road not only deteriorates the tyres’ adhesive condition, but also has a considerable effect on the rollover in some cases.