Adaptive cruise control strategy based on fuzzy logic variable weights
NIU Jigao
ZHANG Tailu
WANG Dongqiang
JIN Kunming
Abstract：To address the issue of insufficient adaptability to preceding vehicle spacing in traditional Adaptive Cruise Control(ACC)systems under following scenarios,an optimized control strategy based on fuzzy logic dynamic weight adjustment is proposed.By adopting a model predictive control integrated with a feedback correction mechanism,a multi-objective optimization function encompassing following performance,safety,and fuel economy is constructed.The weight coefficients are dynamically adjusted using fuzzy logic,enabling the ACC vehicle system to adaptively balance each control objective according to real-time driving conditions.To validate the control effectiveness,a CarSim-Simulink co-simulation platform is developed,testing typical scenarios such as constant speed,sinusoidal variable speed,and stop-and-go conditions of the preceding vehicle.Simulation results demonstrate that the proposed method effectively maintains a safe following distance,and ensures smooth transitions of weight coefficients,significantly enhancing the robustness of ACC in following scenarios.
Keywords：model predictive controldynamic weight adjustmentfuzzy controladaptive cruise controloptimization of vehicle-following performance
Publication Date：2025-12-25
Online Publishing Date：2026-01-27(First online date of this platform, not the publication date of the document)
Pages：8( 7-14 )