Autonomous driving motion planning with obstacles prioritization using lexicographic optimization. (August 2018)

• Record Type: Journal Article
• Authors: Rasekhipour, Yadollah; Fadakar, Iman; Khajepour, Amir
• Is Part Of: Control engineering practice. Volume 77(2018)
• Page Start: 235
• Page End: 246
• Publication Date: 2018-08
• Subjects: Motion planning -- Autonomous vehicles -- Obstacle avoidance -- Model predictive control -- Lexicographic optimization -- Vehicle dynamics and control; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.04.014
• Languages: English
• ISSNs: 0967-0661

Abstract

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. Highlights: A method for avoiding obstacles based on their importance is introduced. A motion planning MPC is presented for prioritized obstacles avoidance. Lexicographic optimization is applied on MPC to prioritize obstacle constraints. When a crash is unavoidable, presented method avoids higher priority obstacles.