Multi-objective dynamic coordinated Adaptive Cruise Control for intelligent electric vehicle with sensors fusion

Adaptive Cruise Control (ACC) is a multi -objective control problem, where the balance of the ride comfort and safety performance of vehicles is a challenge. This paper proposes a multiobjective dynamic coordinated ACC based on variable weight model predictive control (MPC). The weight coefficients are regulated according to the inter distance and relative speed between the front vehicle and ego vehicle through a fuzzy controller. To improve the object detection accuracy, the decision -level sensors fusion scheme based on millimeter wave radar and camera is designed. The upper and lower layers of the hierarchical ACC controller are implemented. The proposed ACC control system is tested on a smart electric vehicle. The dynamic coordinated ACC can increase the tracking accuracy of the safe inter distance to enhance the vehicle safety in scenarios where there is possible risk of collision, such as when the inter distance is small and the relative speed is negative. In some safe conditions, the dynamic coordinated ACC can reduce the acceleration and jerk to improve the ride comfort. The performance of driving safety and ride comfort are dynamically coordinated and adapted to the changing driving conditions through the implementation of the dynamic ACC. The ACC has the ability to adapt to these changes and respond accordingly.