Resilient platooning control for connected automated vehicles under V2V communication disruptions
This study addresses the platooning control problem for connected automated vehicles, explicitly considering nonholonomic vehicle dynamics, curved roads, unknown platoon reference parameters, and intermittent jamming attacks on vehicle-to-vehicle (V2V) communication. Our central aim is to establish a discrete-time distributed cooperative control framework that emphasizes safety and energy efficiency as well as jamming resilience for the platoon. Toward this aim, an adaptive and resilient distributed estimator is first developed for each vehicle over a directed network topology, which robustly tracks unknown time-varying platoon reference and effectively operates under uncertain jamming, with formal guarantees on estimation error stability and maximal resilience. Second, a comprehensive discrete-time longitudinal and lateral platooning model is established to capture nonholonomic vehicle dynamics, curved road geometry, and uncertain reference trajectories. Third, a two-stage control scheme is devised such that both platoon safety and energy minimization can be preserved. This integrated scheme enables feasible longitudinal spacing regulation and lateral path following objectives, while simultaneously achieving jamming-resilient, collision-free, and energy-efficient maneuvering requirements. Stability of the resulting closed-loop platoon control system is formally proven. Numerical experiments are finally presented to demonstrate the effectiveness of the proposed approach across diverse curved-road driving and V2V communication scenarios.
Authors
- Xiaohua Ge (ORCID: https://orcid.org/0000-0003-0180-0897)
- Tianrun Liu (ORCID: https://orcid.org/0000-0002-2626-8617)
- Yang-Yang Chen
Institutions
- Hohai University (CN)
- Swinburne University of Technology (AU)
- Southeast University (CN)
Publication Details
- Journal
- Robotics and Autonomous Systems
- Published
- 2026-11-01
- DOI
- https://doi.org/10.1016/j.robot.2026.105838
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 0.00