This work concentrates on the problem of vehicular adaptive cruise control (ACC) in complicated driving conditions especially in low-adhesion road situations, and an ACC control scheme based on real-time estimation of road adhesion is proposed. The ACC controller isdesigned based on the model predictive control (MPC) method and the steady-state inter-vehicle spacing, relative velocity and the acceleration limits are incorporated into the MPC controller as the constraints. Thereby, the MPC problem is converted into the problem of optimal control with constraints and a receding-horizon approach is utilized to compute the desired vehicle acceleration. The real-time estimation of road adhesion coefficient is accomplished by the recursive least square (RLS) method. A four-degree-of-freedom (4DOF) nonlinear vehicle model is established based on the Lagrangian approach to act as the actual vehicle in the ACC system. The proposed ACC scheme is evaluated by simulations respectively in high and low adhesion conditions. The results reveal that collisions may occur in low adhesion condition if a fixed acceleration limit constraint is employed in the MPC control law. While the proposed adhesion-estimation based ACC system can accomplish the desired inter-vehicle distance safely.
Study on Vehicular Adaptive Cruise Control in Complicated Driving Conditions
2018-06-01
3028093 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
STUDY ON VEHICULAR ADAPTIVE CRUISE CONTROL IN COMPLICATED DRIVING CONDITIONS
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