Low-Cost and High-Performance Adaptive Cruise Control Based on Inertial-Triggered Mechanism and Multi-Objective Optimization

Jianfeng Chen, Yicai Ye, Qiang Wu, Reza Langari, Chuanye Tang

Abstract: The “accelerating-decelerating” logic adopted by the traditional adaptive cruise control system fails to exploit vehicle's inertial energy. This paper proposes a high-performance adaptive cruise control system with common hardware configuration based on inertial-triggered mechanism and multi-objective optimization. In the control strategy, a simple method is adopted to predict preceding vehicle's acceleration. On the basis of the zero-crossing points extracted from the predicted acceleration, the inertial-triggered mechanism is established to reasonably configurate host vehicle's “accelerating-inertial driving-decelerating” logic. Then, within the framework of model predictive control algorithm, multiple objectives are optimized by properly releasing the kinetic energy stored in vehicle inertia. Verification results show that when the proposed control strategy is employed, fuel economy can achieve relatively evident growth while braking time is decreased by 16.4% to efficiently improve vehicle safety.