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Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.

Abstract In-phase rear-wheel steering, where rear wheels are steered in the same direction of front wheels, has been widely investigated in the literature for vehicle stability improvements along with stability control systems. Much faster response can be achieved by steering the rear wheels automatically during an obstacle avoidance maneuver without applying the brakes where safe stopping distance is not available. Sudden lane change movements still remain challenging for heavy articulated vehicles, such as tractor and semitrailer combinations, particularly on roads with low coefficient of adhesion. Different lateral accelerations acting on tractor and semi-trailer may cause loss of stability resulting in jackknifing, trailer-swing, rollover, or slip-off. Several attempts have been made in the literature to use active steering of semi-trailer’s rear wheels to prevent jackknifing and rollover.

Abstract Unstable articulated vehicles pose a serious threat to the occupants driving them as well as the occupants of the vehicles around them. Articulated vehicles typically experience three types of instability: snaking, jack-knifing, and rollover. An articulated vehicle subjected to any of these instabilities can result in major accidents. In this study a Nonlinear Model Predictive Control (NMPC) that applies brake-based torque vectoring on the trailer is developed to improve the articulated vehicle stability. The NMPC formulation includes tire saturation and applies constraints to prevent rollover. The controller output is a left and right brake force allowing the longitudinal velocity change to be incorporated into the model. Simulations were conducted to instigate snaking and jack-knifing and show the NMPC controller result compared to a simple proportional controller.

Abstract Rubber elements present highly nonlinear mechanical properties affected by frequency and amplitude of excitation, prestrain and temperature, etc. Finite element (FE) models and lumped parameter models can be distinguished in the development of constitutive models of rubbers. Based on the concept of overlay model, different kinds of viscoelastic, or frequency-dependent models, and elastoplastic/friction, or amplitude-dependent models, are compared in terms of their modelling approach, parameters identification process and applications. Prestrain-dependent models and temperature-dependent thermo-mechanical models are also reviewed, including some special models which are not based on the concept of the overlay model. Experimental and computational studies of cylindrical bushings subjected to coupled deformation modes are analyzed and discussed.

Abstract Due to their large volume structure, when a heavy vehicle encounters sudden road conditions, emergency turns, or lane changes, it is very easy for vehicle rollover accidents to occur; however, well-designed suspension systems can greatly reduce vehicle rollover occurrence. In this article, a novel semi-active suspension adaptive control based on AdaBoost algorithm is proposed to effectively improve the vehicle rollover stability under dangerous working conditions. This research first established a vehicle rollover warning model based on the AdaBoost algorithm. Meanwhile, the approximate skyhook damping suspension model is established as the reference model of the semi-active suspension. Furthermore, the model reference adaptive control (MRAC) system is established based on Lyapunov stability theory, and the adaptive controller is designed.

Abstract Several accidents on the highways are due to strong crosswind conditions. The effectiveness of wind-break fences on a sudden strong crosswind has been investigated for a generic truck model. Two wind-break fences have been designed for stretching the rise time of aerodynamic loads. The dynamic response of the vehicle to crosswind while exiting a tunnel is simulated. Moving mesh CFD simulations and vehicle dynamics simulations are used to assess the effectiveness of the fences based on a safety index and the maximum lateral displacement of the vehicle. The proposed fences mitigate sudden aerodynamic loads and avoid the rollover of the vehicle.

Abstract In this article, safe driving methods for large articulated vehicles passing roundabouts are presented using the design of experiment (DOE) method. First, the roundabout driving safety evaluation based on the rollover propensity index calculated with the tire loads was performed through various PC-Crash simulation analysis. And, using the Taguchi method, which is a representative DOE method, major factors affecting the rollover index were set by type and the sensitivity analysis results were quantitatively obtained. Finally, safe driving methods at roundabouts for large articulated vehicles through systematic reduction of rollover propensity were presented, demonstrating that they can be directly applied to advanced driver assist systems.

Abstract Parking an articulated vehicle is a challenging task that requires skill, experience, and visibility from the driver. An automatic parking system for articulated vehicles can make this task easier and more efficient. This article proposes a novel method that finds an optimal path and controls the vehicle with an innovative method while considering its kinematics and environmental constraints and attempts to mathematically explain the behavior of a driver who can perform a complex scenario, called the articulated vehicle park maneuver, without falling into the jackknifing phenomena. In other words, the proposed method models how drivers park articulated vehicles in difficult situations, using different sub-scenarios and mathematical models.