Work

Design and Implementation of Parameterized MPC Strategies for Lane Keeping Assist Systems in Real-Time HIL Architecture

Year: 2025

Type: article

Abstract: The Lane Assist System (LAS) helps drivers stay within their road lanes. It uses cutting-edge technology (such as a camera system) to monitor marks for lane-following applications. The Lane Keeping Assist System (LKAS), a LAS with steering control, ensures appropriate lateral vehicle dynamics, avoiding unexpected steering operation. Despite LKAS solutions promoting comfort driving, robust steering control is lacking, requiring constant driver intervention, sometimes with premature LKAS deactivation. For this reason, this paper investigates parameterized Model-Predictive Control (MPC) solutions for real-time LKAS applications. The parameterized MPC calculates control actions for a constrained dynamic system, making it a potential candidate for robust LKAS. A sideslip and lateral speed bicycle model with three MPC formulations and various Quadratic Programming Solvers were considered. Trajectory tracking, lateral displacement and yaw angle regulation experimental tests were run through Hardware-In-the-Loop (HIL) Architecture. Experimental results, along with comparative performance and robustness analyses, demonstrate satisfactory results and provide valuable insights into the application of MPC for lane-keeping assist systems.

Source: IEEE Access

DOI: 10.1109/access.2025.3582149

Authors: James Duvan Garcia Montoya, André Murilo, Evandro Leonardo Silva Teixeira, Rafael Rodrigues da Silva, Bruno Augusto Angélico

Institutions: Universidade Federal de Lavras, Universidade de Brasília, Universidade de São Paulo

Language: English

Topic: Vehicle Dynamics and Control Systems

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,075

Funder: Fundação de Desenvolvimento da Pesquisa