ITSC 2024 Paper Abstract

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Vallinder, Gustav (Scania CV AB, KTH Royal Institute of Technology), Mårtensson, Jonas (KTH Royal Institute of Technology), Lima, Pedro F. (KTH Royal Institute of Technology), Bhat, Sriharsha (KTH Royal Institute of Technology; Scania CV AB)

Model Predictive Control for Autonomous Driving: Comparing Kinematic and Dynamic Models of Tractor-Trailer Systems

Scheduled for presentation during the Regular Session "Control of heavy vehicles" (FrAT4), Friday, September 27, 2024, 12:10−12:30, Salon 7

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Keywords Theory and Models for Optimization and Control, Automated Vehicle Operation, Motion Planning, Navigation

Abstract

Investigations of kinematic and dynamic models of tractor-trailer systems have historically been performed for stability analysis or state estimation. In this work, we present and evaluate kinematic and dynamic tractor-trailer models for model predictive control (MPC). We show in open-loop simulations that a kinematic and a dynamic model are equivalent at low speeds and short discretization time steps. A zero speed singularity and stiff dynamics prevents the usage of the dynamic model in control design, where discretization time steps are longer. A method of discretization is proposed to resolve the low speed feasibility of the dynamic model. In closed-loop simulations, the real-time applicability of the kinematic and dynamic models in a nonlinear MPC is verified.

 

 

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