The point load test is an effective and rapid way to predict rock strength. Regarding the investigation of point load strength and the failure characteristics of rock, the point load test’s advantages and application scopes are introduced in this paper. According to the three main components—the rock itself, the size effect, and the loading cross-sectional area—the point load strength’s influencing factors and mechanisms on rock failure were analyzed, followed by expounding the significant effect of the technology of the point load test on evaluating engineering safety and stability. Based on previous scholars’ research results, there is a strong correlation between the point load strength and the uniaxial compressive strength. The parameters of the rocks from different regions and different sediments were summarized via substantial field and indoor testing. The functional relationship (mainly including the linear function, quadratic function, exponential function, power function, and logarithmic function) between the point load strength and the uniaxial compressive strength was obtained by mathematical statistical analysis. Finally, the challenges regarding the point load test were discussed, and accordingly, suggestions for future research were provided.

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An adaptive cruise control (ACC) system can improve safety and comfort during driving by taking over longitudinal control of the vehicle. It requires the coordination between the upper-layer controller and the lower-layer actuators. In this paper, a hierarchical anti-disturbance cruise control architecture based on electronic stability control (ESC) system is proposed. The upper-layer controller outputs the desired longitudinal acceleration or deceleration to the lower-layer actuators. In order to improve the accuracy of model prediction and achieve the coordinated control of multiple objectives, an upper-layer model prediction cruise controller is established based on feedback control and disturbance compensation. In addition, based on the hydraulic control unit (HCU) model and the vehicle longitudinal dynamics model, a lower-layer nonlinear model predictive deceleration controller is proposed in order to solve the problems of pressure fluctuations and the low accuracy of small decelerations when ESC is used as the actuator for the ACC system. Finally, the simulation and experimental tests were carried out. The results show that the proposed control architecture can improve the stability and comfort of the cruise control process. Moreover, compared with the traditional PID deceleration controller, it effectively improves the deceleration control accuracy.

Surrogate safety measures (SSM) are used to assess the risk for autonomous emergency braking system (AEBS). Developing appropriate SSM and accurately executing the braking request are the key issues. Time‐to‐collision (TTC) is a typical time‐based SSM with limitations. By analyzing the braking process, this paper proposes a new SSM based on deceleration rate to avoid collision (DRAC). As the brake actuator, vehicle electronic stability control (ESC) system has many problems, such as large overshoot and pressure fluctuation. Considering the model of hydraulic control unit (HCU) and vehicle, a deceleration controller based on non‐linear model predictive control (NMPC) is proposed. Based on this, a layered AEBS architecture is proposed. The upper‐layer AEBS controller calculates the expected deceleration based on modified DRAC (MDRAC), and transmits it to the lower‐layer NMPC deceleration controller. Finally, the simulation and experimental tests are carried out. The results show that the system has a fast and stable response. In addition, the performance of the proposed AEBS strategy is tested according to the Euro‐NCAP test protocol. Comparing the results with the TTC method, the proposed method can improve the stability of the distance margin by more than 0.55 m, which ensures the safety and improves the stability of the vehicle.

Recent investigations of the electric braking booster (E-Booster) focus on its potential to enhance brake energy regeneration. A vehicle’s hydraulic system is composed of the E-Booster and electric stability control to control the master cylinder and wheel cylinders. This paper aims to address the independent closed-loop control of the position and pressure as well as the maintenance of the pedal feel. To track both the reference signals related to piston displacement and the wheel cylinder pressure, an explicit model predictive control (MPC) is developed. First, the new flow model is introduced as the foundation for controller design and simulation. Next, in accordance with the operational conditions, the entire system is divided into three switchable subsystems. The three distributed MPCs are constructed based on the linearized subsystems, and a state machine is used to perform the state jump across the controllers. A linear piecewise affine control law can then be obtained by solving the quadratic program (QP) of explicit MPC. Afterwards, the non-linear extended Kalman filter including the recorded time-variant process noise is used to estimate all the state variables. The effectiveness of the explicit MPC is evidenced by the simulations compared with a single MPC in regenerative and dead-zone conditions. The proposed controller decreases the latency significantly by 85 milliseconds, which also helps to improve accuracy by 22.6%. Furthermore, the pedal feel remains consistent, even when factoring in the number of vibrations caused by the inherent hydraulic characteristic of pressure versus volume.