Model Predictive Control of Autonomous Vehicles With Integrated Barriers Using Occupancy Grid Maps

Cho, Minsu; Lee, Yeongseok; Kim, Kyung-Soo

doi:10.1109/lra.2023.3236586

Cited by 9 publications

(1 citation statement)

References 41 publications

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“…Among the uses of this method is the trajectory tracking of autonomous vehicles. The MPC deals with both linear and nonlinear systems and requires online optimization problems to be solved at each prediction sampling time [80]. A real-time non-linear MPC with improved inequality constraint handling and an economic penalty function to plan cost-effective cruising speed online is introduced in [81].…”

Section: Model-based Controllersmentioning

confidence: 99%

Advancing autonomous vehicle control systems: An in‐depth overview of decision‐making and manoeuvre execution state of the art

Abdallaoui,

Ikaouassen,

Kribèche

et al. 2023

The Journal of Engineering

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This abstract discusses the significant progress made in autonomous vehicles, focusing on decision‐making systems and control algorithms. It explores recent advances, challenges, and contributions in the field, emphasizing the need for precise navigation and control. The paper covers various methodologies, including rule‐based methods, machine learning, deep learning, probabilistic approaches, and hybrid approaches, examining their applications and effectiveness in ensuring safe navigation. Additionally, it reviews ongoing research efforts, emerging trends, and persistent challenges related to decision‐making and manoeuvre execution in autonomous vehicles, addressing complex topics such as sensor measurement uncertainty, dynamic environment modelling, real‐time responsiveness, and safe interactions with other road users. The objective is to provide a comprehensive overview of the state of the art in autonomous vehicle navigation and control for readers.

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Section: Model-based Controllersmentioning

confidence: 99%