ADAS achieves its goals by integrating complex subsystems such as obstacle avoidance, overtaking advice, lane changing assistance, planning shortest routes, parking assistance, automatic gear shifting, etc., using the emerging technologies. Under the condition of a given strength reduction coefficient, the calculated results obtained through FE modeling can show the development of the equivalent plastic zone in the form of cloud diagrams.Įmergence of communication technologies made the automotive industries across the globe to embrace Advanced Driver Assistance Systems (ADAS) by considerable investments to ensure accident-free travel, reduction of pollution, fuel conservation. The mutation point of the relationship curve between the displacement generated in the slope and the reduction coefficient can be used as the criterion. The results showed that the slope stability analysis model established by the strength reduction method can characterize the stability of the slope by calculating the slope safety coefficient. At the same time, the sensitivity analysis of the factors affecting the slope stability was carried out through parametric studies, including the elastic modulus, cohesion, internal friction angle, and slope rate. The strength reduction method was adopted to establish an analysis model of slope stability. A finite element (FE) model was constructed to simulate the high-filled road subjected to the actual self-weight load. The present study is to investigate the stability of the backfill subgrade on the lower bearing capacity foundation. Moreover, the comparative study also shows that the proposed BSMC-LMIs controller has the best tracking performance when compared to the Model Predictive Control (MPC), conventional Sliding Mode Control (SMC), and the cubic Proportional-Integral (PI) controller. Finally, the robustness, feasibility, and effectiveness of the proposed BSMC-LMIs controller for velocity-tracking are verified by simulation tests in various working scenarios, which shows satisfying results when dealing with the lumped uncertainties on sloped roads. Besides, a sufficient condition for the existence of the proposed BSMC is derived by using the LMIs, which ensures the t^(-α) asymptotical stability on the sliding surface. The proposed BSMC-LMIs controller for velocity tracking can handle the lumped uncertainties which include the modeling error, parameter perturbation, external disturbances, and noises, and guarantee the reachability of the sliding surface, meanwhile, alleviating the chattering phenomenon inherited from the sliding mode structure. The nonlinear combined slip tire model with the transient behavior is introduced to calculate the tire forces properly, which would be further proven to offer more accurate road slope estimations even in a fierce acceleration or deceleration situation. It includes three key modules, namely, an Extended Kalman Filter (EKF)-based road slope estimation module, a robust BSMC-LMIs velocity-tracking controller based on the input-output feedback linearization, as well as a longitudinal inverse vehicle dynamics module. This paper presents a back-stepping sliding mode controller (BSMC) through linear matrix inequalities (LMIs) for the highly automatic driving vehicle on sloped roads. Automatic driving has received a broad of attention from academia and industry since it is effective in greatly reducing the severity of potential traffic accidents and achieving the ultimate automobile safety and comfort.
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