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This research proposes a novel practical hybrid control scheme - learning agent-based MPC (LAMPC), combining the model-based AMPC approach and data-based learning methods to improve the holistic vehicle performance for multi-agent systems.
A novel car-following model that considers the social preferences and predictive capabilities of real drivers based on the classical intelligent driver model, which improves the intelligence level of environment vehicles, and creates more realistic traffic environment for the autonomous driving simulation.
