4.8 Article

MILE: Multiobjective Integrated Model Predictive Adaptive Cruise Control for Intelligent Vehicle

期刊

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 19, 期 7, 页码 8539-8548

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2022.3220842

关键词

Adaptive cruise control (ACC); crash avoidance (CA); driver-in-the-loop (DiL) test; speedgoat

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The multiobjective adaptive cruise control proposed in this article is based on a novel integrated structure, which consists of an adaptive controller and switching mechanism. The controller combines upper and lower layers for switching modes to avoid collisions and maintain tracking capability in complex driving scenarios. The effectiveness, real-time performance, and robustness of the integrated structure are validated through complex scenarios.
Adaptive cruise control (ACC) systems currently face the challenge of balancing tracking performance and avoiding collisions with arbitrary cut-in vehicles from different lanes. The multiobjective ACC proposed in this article is based on a novel integrated structure. The novel integrated ACC structure consists of an adaptive controller and the associated switching mechanism. The controller combines the upper and lower layers, which are common in today's hierarchical controllers. The switching mechanism is designed to switch between different modes to avoid collisions and maintain tracking capability in complex driving scenarios. Complex scenarios are designed to validate the integrated structure's effectiveness, real-time performance, and robustness, and a driver-in-the-loop platform is established. The results indicate that the novel integrated structure is capable of tracking the preceding vehicle accurately while avoiding colliding with the surrounding vehicle from various directions, thereby ensuring vehicle stability under varying road adhesion and system uncertainties.

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