LPV-MPC for Lateral Control in Full-Scale Autonomous Racing

2026-03-13

AI Summary

This work presents the first successful application of Linear Parameter-Varying Model Predictive Control (LPV-MPC) to lateral control of a full-scale, high-speed autonomous race car under stringent computational constraints and high track-testing costs. By integrating LPV modeling, efficient parameter identification, and an acados-based optimization framework implemented in Python, the authors achieve a controller design that balances real-time feasibility with high performance. Experimental validation on the IAC AV-24 platform demonstrates stable vehicle operation at 71.5 m/s (160 mph), confirming the effectiveness and robustness of the proposed approach under extreme dynamic conditions.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Machine Learning: Large Multimodal Models (LMMs)

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

Autonomous racing has attracted significant attention recently, presenting challenges in selecting an optimal controller that operates within the onboard system's computational limits and meets operational constraints such as limited track time and high costs. This paper introduces a Linear Parameter-Varying Model Predictive Controller (LPV-MPC) for lateral control. Implemented on an IAC AV-24, the controller achieved stable performance at speeds exceeding 160 mph (71.5 m/s). We detail the controller design, the methodology for extracting model parameters, and key system-level and implementation considerations. Additionally, we report results from our final race run, providing a comprehensive analysis of both vehicle dynamics and controller performance. A Python implementation of the framework is available at: https://tinyurl.com/LPV-MPC-acados

Problem

• autonomous racing
• lateral control
• computational constraints
• track time limitation
• high-speed stability

Innovation

• LPV-MPC
• autonomous racing
• lateral control
• model predictive control
• real-time implementation