Abstract
There are driving situations that avoiding all obstacles is infeasible. In such situations, an autonomous vehicle should avoid vulnerable obstacles like pedestrians. In this paper, a motion planning method is presented that avoids obstacles according to their priority orders. The method utilizes a model predictive controller with obstacle constraints and applies lexicographic optimization to the controller to prioritize the constraints, and subsequently, prioritize the obstacles. The proposed method is simulated on a high fidelity CarSim vehicle model. The results show that when avoiding all obstacles is not feasible, the proposed method avoids the obstacles with the highest priority orders.
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