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insight - Autonomous vehicle control
Enhancing Safety and Efficiency in Mixed Autonomous and Human-Driven Vehicle Platoons through Learning-Based Modeling and Predictive Control
A novel learning-based approach is proposed to model the behavior of human-driven vehicles (HVs) by integrating a first-principles model with a Gaussian process (GP) component. This enhanced HV model is then leveraged to develop a chance-constrained model predictive control (GP-MPC) strategy that improves safety and operational efficiency in mixed-traffic environments.
Enhancing Safety in Mixed Traffic: A Gaussian Process-based Model Predictive Control for Autonomous and Human-Driven Vehicle Platooning
A novel learning-based model predictive control strategy that integrates Gaussian process models to effectively manage the uncertainties associated with human-driven vehicles, thereby enhancing safety and efficiency in mixed-traffic scenarios.