In this paper, we propose a progressive model predictive control scheme (PMPCS) by considering the cooperative control of local planning and path tracking for intelligent vehicles. An improved particle swarm optimization (IPSO) based model predictive control (MPC) method is developed to solve the planning and tracking problem. With the PMPCS, the total computational burden can be reduced sharply because of the seamless connection and mutual promotion between the optimization of two layers. Besides we also propose a novel planning algorithm, which can take traffic lights and overtaking time constraint into account. To solve these problems, we first combine model predictive control with artificial potential field (APF) to get a collision-free path by treating the timevarying safety constraints as the scope of the repulsive force and an asymmetrical lane potential field function. Furthermore, the pseudo velocity planning method is adopted to take traffic lights into account in the planning module. Simulation results show the reliability of the proposed algorithm and the advantages of the scheme compared with general hierarchical algorithm.

Security problem is a fundamental issue for autonomous vehicles. Trajectory planning is a significant component of autonomous vehicle system, which directly influences the automated traffic safety. In this paper, the motion prediction of other traffic participants is considered. We use Monte Carlo simulation to predict the probabilistic occupancy of the object, and give a map from probability statistics to actual scenarios. The non-time based reference trajectory can be obtained by using high precision map (HD map) and lane detection. Then model predictive control (MPC) is utilized to optimize the reference trajectory according to the current state of autonomous vehicle. Different prediction horizons and coordinate transformation are adopted to optimize the planning. By doing so, the constraint conditions can be easily involved and the result is more intuitive. The probabilistic occupancy of other traffic participants are computed offline and then the obtained results are used in real time application. Therefore, the real-time computational burden is reduced. The crash probability is put forward to verify the feasibility of real-time trajectory in safety assessment module. Two typical scenarios are analyzed: lane change on the straight road and turning at the intersection. The simulation results illustrate the efficiency of our method.

This article studies the stabilization problem for switched systems in the presence of denial-of-service (DoS) attack using the event-triggered scheme. Unlike the traditional switching signal design with DoS attack, some challenges arise in the joint influence on the constraints of DoS duration/frequency, and the asynchronous behavior caused by the controller and the subsystem mode. To this end, a novel multiple Lyapunov function involving the joint effects of DoS attack and controller mode is constructed. This allows that there are no events between two consecutive switching instants. By incorporating the dwell-time switching signal with the event-triggered scheme, the considered system can be globally exponentially stabilizable when the frequency and duration of DoS attack meet certain requirements. It also shows that apart from the codesign associated with the event-triggered parameters with controller gain, the maximum allowable sampling period can be offline calculated. Moreover, the Zeno behavior is eliminated by calculating a lower bound of the event-triggered interval, over which the DoS attack is inactive. Finally, simulations are carried out to verify the effectiveness of the theoretical results.

A novel integral sliding mode control (ISMC) strategy combining with disturbance observer (DO) for vehicle-following systems is presented in this paper. The vehicle platoon includes a leading vehicle and multiple following vehicles subjected to unknown acceleration uncertainties. Firstly, the ISMC based on DO and the constant time headway (CTH) policy is constructed to realize the string stability of the whole vehicle platoon in finite time, under the condition of zero initial spacing errors. The uncertainties of the vehicular system can be well estimated by extending DO even if the bounds of the uncertainties are not known exactly. In order to alleviate the chattering problem of the traditional ISMC, a continuous sliding surface including sign function is designed for the proposed ISMC strategy. Then, a modified constant time headway (MCTH) policy is proposed to overcome the requirement of zero initial spacing errors. In addition, the developed MCTH policy can effectively improve the string stability and safety of the vehicle platoon system. Finally, the effectiveness and advantages of the proposed algorithm are verified by the simulations and experiments.

The stabilization problem for switched linear systems with quantization and event-triggered control is addressed in this article. The state information is quantized and transmitted to the controller. An event-triggered mechanism is presented in terms of the quantizer parameter. The updating law of the dynamic quantizer is suggested for the purpose of guaranteeing the state operating within the quantization range. Meanwhile, the contour line of the Lyapunov function is developed to provide an efficient way for system performance improvement. A co-design strategy is put forward to determine the event-triggered parameter and the quantization scheme simultaneously. The asynchronization issue between the controller and the subsystem is solved by designing a suitable switching signal. The Zeno behavior is eliminated by calculating a lower bound of the event-triggered interval. In the end, a strategy for finding the initial value of the quantization parameter is discussed. Simulations are carried out to demonstrate the efficiency of the proposed method.