A Hierarchical Adaptive Nonlinear Model Predictive Control Approach for Maximizing Tire Force Usage in Autonomous Vehicles

Author:

Dallas JamesORCID,Thompson MichaelORCID,Goh JonathanORCID,Balachandran AvinashORCID

Abstract

The ability to reliably maximize tire force usage would improve the safety of autonomous vehicles, especially in challenging edge cases. However, vehicle control near the limits of handling has many challenges, including robustly contending with tire force saturation, balancing model fidelity and computational efficiency, and coordinating inputs with the lower level chassis control system. This work studies nonlinear model predictive control for limit handling, specifically adapting to changing tire-road conditions and maximally allocating tire force utilization. We present a novel hierarchical framework that combines a single-track model with longitudinal weight transfer dynamics in the predictive control layer, with lateral brake distribution occurring at the chassis control layer. This vehicle model is simultaneously used in the unscented Kalman filter for online friction estimation. Comparative experiments on a full-scale vehicle operating on a race track at up to 95% of maximum tire force usage demonstrate the overall practical effectiveness of this approach.

Publisher

Field Robotics Publication Society

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Safe Stability Envelopes and Shared Control for Active Vehicle Safety;2024 IEEE Conference on Control Technology and Applications (CCTA);2024-08-21

2. An observer robustified control barrier function filter for vehicle control at the limits of handling;2024 IEEE Conference on Control Technology and Applications (CCTA);2024-08-21

3. Beyond the stable handling limits: nonlinear model predictive control for highly transient autonomous drifting;Vehicle System Dynamics;2024-02-21

4. A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differential;2023 IEEE 11th International Conference on Systems and Control (ICSC);2023-12-18

5. Shared Control for Giving Ordinary Drivers Expert Level Drifting Skills;2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2023-10-01

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