Qiuhao Wen | Searcharxiv

arXiv2026

An Adaptive Longitudinal Platooning Design Based On Concurrent Learning

This work proposes a new adaptive longitudinal platooning strategy in the framework of concurrent learning. Adaptive refers to vehicles facing uncertainty in powertrain parameters via on-line estimation; concurrent learning refers to using both current and past data in the estimation. The proposed platooning strategy advances existing ones since convergence to the true powertrain parameters is guaranteed without imposing persistence of excitation on the vehicle behavior: it suffices the presence of a single non-zero data sample. Meanwhile, the concurrent learning proof we give advances existing ones since it takes into account an extra unknown gain in the error dynamics.

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arXiv2026

Correct Online Estimation of the Powertrain Time Constants in Adaptive Vehicular Platooning

In longitudinal platooning, some key sources of uncertainty are the powertrain time constants of the vehicles. Because such time constants appear in the input matrix of the platooning dynamics, their correct estimation is either impractical with methods requiring persistence of excitation, or impossible with methods requiring the input matrix to be known. This work proposes a novel adaptive longitudinal platooning method with correct estimation of the powertrain time constants. To achieve correct estimation, the composite adaptive control framework and its stability analysis are suitably modified to handle the time constant uncertainty in the design of the adaptive law. The result is a platooning protocol that guarantees convergence of the estimated time constants to their true values without the need for persistence of excitation: it is sufficient the derivative of the acceleration to be nonzero over a possibly short transient, an extremely relaxed excitation condition. Comparisons with state-of-the-art platooning solutions reveal advantages such as no required measurements of acceleration derivative nor collection of past data. The robustness and practicality of the proposed design is also verified with CarSim-based platooning experiments.

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