Random network delay will introduce uncertainty into trajectory tracking model of the autonomous vehicle, which seriously deteriorates the vehicle's control system stability and trajectory tracking accuracy. In this paper, considering steering angle oscillation caused by random network delay, trajectory tracking system robustness and stability is analyzed and a linear uncertain time-delay system is established. Comprehensively considering control system accuracy, robustness, and computational efficiency in the rolling optimization of Model Predictive Control (MPC), Adaptive Model Predictive Control for Uncertain model (UM-AMPC) algorithm is proposed to predict control variables for the next sampling time and alleviate the target angle discontinuity. This is achieved by operating target angle signal and augmented state variables, which are received by the lower nodes during the period from the current sampling time to network delay upper bound. The hardware-in-the-loop simulation results show that the proposed algorithm can effectively guarantee system stability and tracking accuracy of the autonomous vehicle under random network delay.

Compared to traditional chassis systems, the integrated wheel end (IWE) offers independent control of each wheel, but network delays in the CAN system challenge its high-precision cooperative tracking control. Therefore, this work proposes a coordinated tracking control strategy for the IWE system based on a generalized instantaneous steering center (ISC) constraint. Firstly, the model of controlled objects based on ISC is established. It transforms the coordination problem of multiple IWE systems into the tracking control problem of single variable ISC to reduce the computational complexity. Secondly, considering the time-delay characteristics of multi-actuator asynchronous communication, the event trigger condition based on the generalized ISC boundary is designed, and the generalized event-triggered IWE model predictive control (GET-MPC) strategy for time-delay systems is proposed. Its characteristic is that the control input time-delay factor is not only considered in the new controlled object model, but the influence of time-delay on tracking control performance is also further reduced by the generalized ISC trigger condition. The hardware-in-the-loop experiment results show that in the comprehensive test scenario, the average tracking error of the GET-MPC algorithm proposed in this paper is reduced by 26.59%, effectively improving the system’s tracking accuracy under the network communication delay.

The four-wheel independent steering(4WIS) system has the characteristic of wholly independent and controllable fourwheel steering angles. It can achieve new modes such as wedge driving (with the same four-wheel steering angle) or even lateral driving (with all four-wheel steering angles of 90 degrees) through four-wheel steering angle coordination, making its stability judgment and control method completely different from traditional four-wheel steering systems. This poses challenges to the design of the steering angle coordination controller. To solve the above problems, the control requirements under different steering modes, such as 4WIS conventional/unconventional, are discussed, and a control objective design method is established considering the asymptotic evolution characteristics of the 4WIS critical stability boundary. Considering that the dynamic acquisition and control of 4WIS control objectives need online optimization, which will consume many computing resources, an event-triggered stability control method is proposed based on the dynamic redistribution of lateral force. The results show that the method proposed in this paper can make the 4WIS system self-adaptive and fast and smooth switching mode. The stability can be ensured by redistributing the lateral force so that the system can meet both the manoeuvrability and stability requirements.

This work proposes an active collision avoidance between autonomous driving vehicle and pedestrian with motion uncertainty under urban road. A candidate trajectory planning method considering spatial and time sequences is proposed, which combines the polynomial path planning and the velocity planning with variable safety velocity. Then, a pedestrian-vehicle interaction model is constructed, which takes the pedestrian's uncertain motion as a superposition of the Markov process without interference and the motion caused by the vehicle, and predicts the pedestrian's motion probabilistically. On these bases, the optimal trajectory is evaluated from the candidate trajectories by safety, stability, and efficiency, as well as different driving styles. The proposed collision avoidance strategy is verified in conventional and emergency simulation scenarios. Simulation results show that it can effectively plan a safe, stable and efficient trajectory under normal and emergency conditions.

In order to meet the requirement of a higher safety level for the steer-by-wire system, this article proposes a dual-motor steer-by-wire (DMSBW) system to realize its safety redundancy function. Aiming at the problem of vehicle tracking performance degradation when the steering motors of the DMSBW system have serious failures, a performance-guaranteed adaptive switching fault-tolerant control strategy is designed. First, considering the actuator faults and the caused load disturbance, the DMSBW system switching control model is established. Then, to guarantee the tracking performance of DMSBW system before and after switching fault-tolerant control, the performance-guaranteed adaptive backstepping switching controller based on the extended state observer (ESO-PABSC) is designed. The expanded state observer estimates the state of the system and the perturbation of the load torque. Considering the parameter uncertainties existing in the system, the control output of the DMSBW system is solved by the performance-guaranteed adaptive backstepping controller, and the dynamic switching controller is designed to perform dynamic switching when the steering motor fails, which ensures that the tracking error of the system is within the prescribed performance. Finally, the effectiveness of the proposed control strategy under the actuator stuck fault is verified by the simulation and experiment. The results show that proposed ESO-PABSC algorithm improves the vehicle tracking performance by 56.7% and 72.9% compared to the PBSC and Hinf algorithms.

In order to promote the safety redundancy of steer-by-wire system, a dual-motor steer-by-wire (DMSBW) system is designed in this paper. However, when one of the steering motors fails seriously, the vehicle's angle tracking performance is affected, which is exacerbated by load fluctuation and limited CAN communication bandwidth in the control system. Therefore, we innovatively establish DMSBW switching control model and propose an event-triggered adaptive fuzzy switching fault-tolerant control strategy. Firstly, the interval type-2 fuzzy state observer is used to estimate the state of the nonlinear DMSBW system and the time-varying fluctuation of the load torque before and after switching. Then, the prescribed performance adaptive backstepping controller is designed to solve the control output by fusing the error and fault event-triggered controller to realize the unification of switching fault tolerance and accurate tracking while reducing communication resources. And the switching fault-tolerant performance under both transient and steady state is guaranteed by proving Lyapunov stability and boundedness. Finally, hardware-in-the-loop experiments show that the proposed method is effective.