A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential

Abstract

In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Model Predictive Controller in which we included a micro-steps discretization approach to accurately linearize the dynamics and produce a prediction suitable for real-time implementation. The stability analysis of the model is presented, as well as a brief description of the overall planning and control scheme which includes an offline trajectory generation pipeline, an online local speed profile planner, and a low-level longitudinal controller. An improvement of the lateral path tracking is demonstrated in preliminary experimental results that have been produced on a Dallara AV-21 during the first Indy Autonomous Challenge event on the Monza F1 racetrack. Final adjustments and tuning have been performed in a high-fidelity simulator demonstrating the effectiveness of the solution when performing close to the tire limits.

Presented at the 2023 IEEE 11th International Conference on Systems and Control, Sousse, Tunisia, December 18-20, 2023

References in corpus (3)

• Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds
• A hierarchical adaptive nonlinear model predictive control approach for maximizing tire force usage in autonomous vehicles
• er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

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