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• W2170973929 abstract "This paper presents a novel vehicular adaptive cruise control (ACC) system that can comprehensively address issues of tracking capability, fuel economy and driver desired response. A hierarchical control architecture is utilized in which a lower controller compensates for nonlinear vehicle dynamics and enables tracking of desired acceleration. The upper controller is synthesized under the framework of model predictive control (MPC) theory. A quadratic cost function is developed that considers the contradictions between minimal tracking error, low fuel consumption and accordance with driver dynamic car-following characteristics while driver longitudinal ride comfort, driver permissible tracking range and rear-end safety are formulated as linear constraints. Employing a constraint softening method to avoid computing infeasibility, an optimal control law is numerically calculated using a quadratic programming algorithm. Detailed simulations with a heavy duty truck show that the developed ACC system provides significant benefits in terms of fuel economy and tracking capability while at the same time also satisfying driver desired car following characteristics." @default.
• W2170973929 created "2016-06-24" @default.
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• W2170973929 date "2011-05-01" @default.
• W2170973929 modified "2023-10-17" @default.
• W2170973929 title "Model Predictive Multi-Objective Vehicular Adaptive Cruise Control" @default.
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• W2170973929 doi "https://doi.org/10.1109/tcst.2010.2049203" @default.
• W2170973929 hasPublicationYear "2011" @default.
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