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.
In this paper, an optimal torque distribution approach is proposed for electric vehicle equipped with four independent wheel motors to improve vehicle handling and stability performance. A novel objective function is formulated which works in a multifunctional way by considering the interference among different performance indices: forces and moment errors at the centre of gravity of the vehicle, actuator control efforts and tyre workload usage. To adapt different driving conditions, a weighting factors tuning scheme is designed to adjust the relative weight of each performance in the objective function. The effectiveness of the proposed optimal torque distribution is evaluated by simulations with CarSim and Matlab/Simulink. The simulation results under different driving scenarios indicate that the proposed control strategy can effectively improve the vehicle handling and stability even in slippery road conditions.
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