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Self-Driving Cars: Nonlinear MPC for Steering, Throttle and Brake Control

Gianmarco Picariello

Self-Driving Cars: Nonlinear MPC for Steering, Throttle and Brake Control.

Rel. Stefano Alberto Malan. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2023

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Abstract:

This Master's Thesis work takes inspiration from the Bosch Future Mobility Challenge 2022, a challenge organized by the Bosch Engineering Center Cluj and concerns the development of algorithms for the autonomous driving on a 1:10 scale vehicle model. The goal of this document is to present the development of control strategies based on a Nonlinear Model Predictive Control (NMPC) for Perpendicular Autonomous Parking manoeuvres: - Perpendicular Parking using a Nonlinear Model Predictive Controller - Perpendicular Parking using a Multistage NMPC. - Perpendicular Parking using a NMPC with Trajectory Planning performed via an RRT* algorithm. The algorithms are re-elaborated from those provided by The MathWorks, Inc. in the case of Parallel Autonomous Parking.

Relators: Stefano Alberto Malan
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 146
Subjects:
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/26721
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