Anti-Rollover Path Tracking Control for an Autonomous Semi-Trailer Tank Truck
This study focuses on the anti-rollover control problem for autonomous semi-trailer tank trucks and proposes an anti-rollover path tracking control algorithm suitable for autonomous driving scenarios. A simplified semi-trailer tank truck model is established in the controller, modeling liquid as a single pendulum considering both lateral and roll inputs, and an anti-rollover path tracking algorithm that utilizes it is developed based on multi-constraint model predictive control (MPC). The equivalent lateral load transfer rate (LTR), liquid sloshing angle, and angular velocity are used as constraints to achieve multi-objective optimization for path tracking, sloshing suppression, and rollover prevention. A vehicle-fluid coupling co-simulation platform based on computational fluid dynamics (CFD) is built to verify the control performance under extreme scenarios of left turning, high-speed single-lane change (SLC), and short-distance double-lane change (DLC). Additionally, the similarity principle for experimental validation using a down-scale model tank truck is derived, and experiments are conducted on the model semi-trailer tank truck under the DLC scenario. Through simulation and experimental verification, the proposed anti-rollover path tracking algorithm demonstrates acceptable tracking performance while ensuring that no rollover is carried out under extreme conditions, limiting the angle of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$|LTR|<0.75$</tex-math></inline-formula> and sloshing within -20∘-20∘, reducing the angle of sloshing by a maximum of 42% in the experiment. Moreover, the real-time capability of the proposed algorithm meets the requirements for practical applications with a peak time consumption of one control step less than 20 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ms</i> in the controller tested.
Authors
- Bolin Gao
- Wei Zhong (ORCID: https://orcid.org/0000-0001-8206-1242)
- Yugong Luo (ORCID: https://orcid.org/0009-0003-5278-0491)
- Xiaojing Qi (ORCID: https://orcid.org/0009-0004-6128-8498)
Institutions
- Tsinghua University (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2025-05-09
- DOI
- https://doi.org/10.1109/tits.2025.3563475
- Citations
- 3
- Primary Topic
- Vehicle Dynamics and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 2.05
Funders
- National Key Research and Development Program of China