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arXiv · 2102.01211

MPC path-planner for autonomous driving solved by genetic algorithm technique

Stefano Arrigoni·Francesco Braghin·Federico Cheli
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Abstract

Autonomous vehicle's technology is expected to be disruptive for automotive industry in next years. This paper proposes a novel real-time trajectory planner based on a Nonlinear Model Predictive Control (NMPC) algorithm. A nonlinear single track vehicle model with Pacejka's lateral tyre formulas has been implemented. The numerical solution of the NMPC problem is obtained by means of the implementation of a novel genetic algorithm strategy. Numerical results are discussed through simulations that shown a reasonable behavior of the proposed strategy in presence of static or moving obstacles as well as in a wide rage of road friction conditions. Moreover a real-time implementation is made possible by the reported computational time analysis.

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Stefano Arrigoni, Francesco Braghin, Federico Cheli. 2021-02-01. MPC path-planner for autonomous driving solved by genetic algorithm technique. https://doi.org/10.1080/00423114.2021.1999991

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