Abstract-Artificial potential fields and optimal controllers are two common methods for path planning of autonomous vehicles. An artificial potential field method is capable of assigning different potential functions to different types of obstacles and road structures, and plans the path based on these potential functions. It does not however, include the vehicle dynamics in the path planning process. On the other hand, an optimal path planning controller integrated with vehicle dynamics plans an optimal feasible path that guarantees vehicle stability in following the path. In this method, the obstacles and road boundaries are usually included in the optimal control problem as constraints, and not with any arbitrary function. A model predictive path planning controller is introduced in this paper such that its objective includes potential functions along with the vehicle dynamics terms. Therefore, the path planning system is capable of treating different obstacles and road structures distinctly while planning the optimal path utilizing vehicle dynamics. The path planning controller is modeled and simulated on a CarSim vehicle model for some complicated test scenarios. The results show that, with this path planning controller, the vehicle avoids the obstacles and observes road regulations with appropriate vehicle dynamics. Moreover, since the obstacles and road regulations can be defined with different functions, the path planning system plans paths corresponding to their importance and priorities.Index Terms-Path Planning, Autonomous Vehicles, Road Vehicles, Model Predictive Control, Artificial Potential Field, Vehicle Dynamics and Control.
Ride comfort is one of the main indexes of a comfortable vehicle, and engine mounts play an undeniable role in it. In this paper, a simplified model of an engine system is expressed to evaluate the performance of a semiactive MagnetoRheological (MR) engine mount and compare it with that of the passive Hydraulic Engine Mount (HEM) on which engine is originally mounted, to investigate if it is advantageous to be used in engine system instead of the HEM. Two methods are used to control the semi-active system including skyhook and robust μ-synthesis. It is attempted to improve two performance cases via the controlled MR engine mount: to reduce the force transmitted to the chassis initiating from engine forces, and to control the relative displacement of engine mount from road excitation. Considerable improvement is achieved over the HEM by applying the MR mount.
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